Report on test conditions and evaluation criteria for

Transcription

Safe Small Electric Vehicles
through Advanced Simulation Methodologies
Collaborative Project
Grant Agreement Number 314265
st
Start date of the project: October 1 , 2012, Duration: 36 months
Deliverable D2
Report on test conditions and evaluation criteria for occupant and vulnerable
road user protection of small electric vehicles
Status: Version 3: 11 Dec. 2013
Lead contractor for this deliverable: Chalmers
Due date of deliverable: 30.09.2013
Actual submission date: 12.12.2013
Coordinator:
Dipl.-Ing. Andreas Teibinger
Virtual Vehicle Kompetenzzentrum
Das Virtuelle Fahrzeug Forschungsgesellschaft mbH (ViF)
Inffeldgasse 21/A/I – A-8010 Graz – Austria
Phone
+43 316 873 9087, Fax
+43 316 873 9002
E-mail
[email protected]
Project co-funded by the European Commission within the 7th Framework Programme (2007–2013)
Dissemination Level
PU
Public
x
PP
Restricted to other programme participants (including the Commission Services)
SEAM Restricted to partners of the SEAM Cluster (including the Commission Services)
RE
Restricted to a group specified by the consortium (including the Commission Services)
CO
Confidential, only for members of the consortium (including the Commission Services)
2
EXECUTIVE SUMMARY
The objective of this study is the specification of test configurations for vulnerable road user and occupant
protection assessment (incl. compatibility) in accidents involving small EV’s in urban areas. Small EV’s in
SafeEV in particular concern vehicles in the mass category of so-called L7e vehicles, where currently hardly
any safety requirements exist.
The test conditions are based on the results of WP1 of SafeEV, recent regulatory trends and new developments
in the field of consumer testing (NCAP). The assessment of pre-crash based injury reduction systems is also
taken into account. The work includes specification of the (virtual) tools to be used like impactors, virtual
models, crash dummies, integrated experimental/virtual methods etc…
Concerning evaluation of pre-crash and active safety systems, discussed in Chapter 2, it was concluded that the
future focus in SafeEV will be on passive safety pedestrian and crash sensors and the according requirements
for sensor evaluation tests. For pedestrian safety sensors it was shown that through their geometry SEVs pose a
challenge on the setup of the sensors as well as on the sensor and trigger time of in-crash safety systems for
pedestrians. Further it was concluded that only simulation/virtual tools will allow a continuous observation and
evaluation of integrated safety systems in terms of a benefit based assessment.
For VRU (i.e. pedestrian and cyclist) safety evaluation in SafeEV, presented in Chapter 3, simulations are
proposed using human body models (HBM) in the following 4 sizes: 6 year old child, 5% Female, 50% Male
and 95% Male. Simulations concern impacts of a pedestrian against the vehicle front at 2 speed ranges: 25
km/h to 30 km/h (lower boundary) and 45 km/h to 50 km/h (upper boundary). Also simulations for cyclist
protection are proposed.
Occupant protection is discussed in Chapter 4. The following accident types have been addressed: frontal, side,
rollover, rear, compatibility and Multiple Impact Crashes (MIC’s).
For frontal occupant protection for L7e class vehicles a test (simulation with HBM) with an oblique impact
configuration (30 degrees) is proposed. One option here is that also accounts for compatibility aspects, is a test
with at a test speed of 30-40 km/h against a movable barrier that represents the average opponent vehicle mass
(1125 kg in GIDAS analysis). Such a configuration also adapts automatically the effect of variations in SEV
mass. The option for a full virtual test method here has high potential due to the fact that for crash barriers
already validated models are available. Verification and Validation issues concerning the vehicle model are in
general addressed by the IMVITER project and should be taken into account.
Concerning future frontal compatibility protection of M1 vehicles the ODB offset test configuration proposed
by the FIMCAR project as well the FWDB test, are identified as most suitable tests to be used within the
SafeEV project. The quantification of the use potential of a test configuration using a movable barrier for
compatibility tests addressing SEV-to-SEV and SEV-to-M1 vehicle front crash behaviour will be an aspect
addressed within the project work package 3.
For side impact occupant protection in L7e vehicles a test (simulation with HBM) using the latest MDB with a
mass of 1100kg reflecting typical future car masses, is proposed. The barrier will hit the vehicle with a speed
of 40 km/h at an angle of 90º. The impact location is moved backwards reflecting a short bonnet in a car body.
Rollover protection is not an important accident scenario in Europe (compared to the USA). Within SafeEV it
is proposed that the SSF (Static Stability factor) and AST (Airbag standing Time) are calculated. For this no
simulations or tests are needed. Eventually if these values exceed certain critical values it could be considered
to perform so-called Fishhook and ESC tests which can be done by simulations. An Inverted Roof Crush test
could be considered as well but will not be addressed within SafeEV.
Concerning rear impacts the introduction of AEB and introduction of seat concepts aimed at lowering the risk
of WAD (Whiplash Associated Disorders) will reduce the number and risk of WAD in future rear-end impacts.
However WAD will remain frequent and the consequences will continue to lead to large societal costs and
personal suffering. Additional and improved test tools and sled test conditions are under development. Among
these are a female dummy and associated limits and an adult 95Th percentile dummy. Also there is potential for
simulations with HBM’s. Initial positioning of the occupant is a parameter having a large influence.
A final accident condition that was considered are the Multiple Impact Crashes (MIC’s), in which a vehicle
experiences at least 2 impacts after each other. Although the frequency and injury severity of MIC’s will
decrease due to the trends presented in WP1, a strong need to protect people in MIC’s remains due to the large
frequency of these crashes and the relative high injury risk.
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EXECUTIVE SUMMARY
Recommendations concerning future work in SaveEV (WP3 etc...) concerning MIC’s are: (1) Inclusion of
occupant simulations (virtual testing) with active HBM of extreme controlled vehicles manoeuvres that are
aimed to reduce the risk of or the severity of second (or more) impacts in a MIC. The aim of such simulations
is to study the effect on human position changes during such manoeuvres and the resulting risk on OOP’s and
(2) Inclusion of occupant simulations aiming of optimization of reversible and irreversible restraint systems
during MIC’s.
Chapter 5 deals with criteria to be used in the various test (simulation) conditions. A distinction is made
between injury criteria, compatibility criteria and fire and electric safety criteria.
The overview of injury criteria is rather extensive. Most important body parts and future trends are addressed
(including the need to have better criteria for children and elderly). Both global criteria (criteria that also can be
determined at physical crash dummies) and criteria on tissue level to be determined on human body models are
described. Also a distinction is made between criteria for vulnerable road users (pedestrians and cyclists) and
car occupants.
The compatibility evaluation criteria defined within the FIMCAR project for the FWDB and the ODB test
are initially identified as also suitable for the assessment of small electric vehicles. But it should be realized
that FIMCAR didn’t integrate a force compatibility assessment criterion into the final metric proposal, so this
may need some additional attention.
Concerning fire and electric safety criteria an overview of current regulations for crash safety of Battery
Electric Vehicles (BEV) is given. All requirements are for an experimental evaluation procedure, focusing on
frontal, side and rear impacts. A virtual assessment of these criteria is not considered yet. Possible reasons
might be the limited knowledge of or the experience with the crash safety of BEV and the lack of suitable
simulation models. A review of trends in this field did not predict big changes in the current requirements for
2025.
4
APPROVAL STATUS
Company/Organisation
Name
Date
WP Leader approval Chalmers University of
Technology
Jac Wismans
Date: 11 Dec. 2013
Approval on behalf
of the PSC
Jürgen Gugler
Date: 5 Dec. 2013
Graz University of
Technology
Date:
CONTRIBUTING PARTNERS
Company/Organisation
Document Manager
Chalmers University of Technology
Partner 1
Partner 2
Partner 3
Partner 4
Daimler AG
Graz University of Technology
Bosch
VIF
Partner 5
IKA
Partner 6
UNISTRA
Name
Jac Wismans, Johan Davidsson, Anna
Carlsson (General Chapters, Chapter 4.5
and 4.6)
Christian Mayer (Chapter 2, 4.1 and 5.1)
Peter Luttenberger (Chapter 4.4)
Gian Antonio Daddetta (Chapter 2)
Krzysztof Michal Hinc (Chapter 4.2)
Ernö Dux (Chapter 4.3 and 5.2) ,
Frederic Nuss (Chapter 5.3)
Remy Willinger (Chapter 3)
REVISION TABLE
Document version
Version 3
Date
9 Dec. 2013
Modified sections - Details
Review comments from project reviewer Juergen Gugler
5
Table of Contents
Glossary ...................................................................................................................................... 9
1
Introduction ...................................................................................................................... 10
2
Evaluation of Pre-Crash and Active Safety Systems ....................................................... 11
2.1
Current status of Pre-Crash & Active Safety evaluation ........................................... 11
2.2
Evaluation of safety systems – component and sensor level ..................................... 16
2.2.1
Pedestrian safety..................................................................................................... 16
2.2.2
Occupant safety using surround sensing ................................................................ 22
2.3
Trends & Options for Virtual Evaluation .................................................................. 25
2.4
Discussion and conclusions ....................................................................................... 27
3
VRU (Pedestrian and cyclist) protection ......................................................................... 29
3.1
Relevant current regulation (s) test methods etc.. ...................................................... 29
3.2
Most important trends from WP1, regulations, EuroNCAP etc.. .............................. 30
3.3
Future test conditions ................................................................................................. 34
3.4
Discussion and conclusions ....................................................................................... 38
Occupant protection in small EV’s .................................................................................. 40
4
4.1
Frontal impacts .......................................................................................................... 40
4.1.1
Relevant Current Regulation(s) Test Methods etc. ................................................ 40
4.1.2
Most Important Trends from WP1, Regulations, EuroNCAP etc.. ........................ 47
4.1.3
Future Test Conditions ........................................................................................... 50
4.1.4
Discussion and Conclusions ................................................................................... 51
4.2
Side Impacts ............................................................................................................... 51
4.2.1
Relevant Current Regulation(s) Test Methods etc.. [43] ....................................... 52
4.2.2
4.2.3
4.2.4
4.3
Compatibility ............................................................................................................. 59
4.3.1
Relevant Current Regulation(s) Test Methods etc.. ............................................... 61
4.3.2
4.3.3
4.3.4
6
4.4
Rollover ..................................................................................................................... 69
4.4.1
4.4.2
4.4.3
4.4.4
4.5
Rear End .................................................................................................................... 76
4.5.1
4.5.2
4.5.3
4.5.4
4.6
Other Accident Modes ............................................................................................... 81
4.6.1
4.6.2
4.6.3
4.6.4
5
Criteria for assessments of SEV safety in crashes ........................................................... 84
5.1
Injury Criteria ............................................................................................................ 84
5.1.1
Current Criteria for VRU protection ...................................................................... 84
5.1.2
Current Criteria for Occupant Protection ............................................................... 87
5.1.3
Trends and Future Injury Criteria......................................................................... 108
5.1.4
Discussion and Conclusion .................................................................................. 129
5.2
Compatibility ........................................................................................................... 130
5.2.1
Current criteria ..................................................................................................... 130
5.2.2
Most important trends .......................................................................................... 131
5.2.3
Criteria for future test conditions ......................................................................... 133
5.2.4
Discussion and conclusions.................................................................................. 133
5.3
6
Fire, Electric Safety etc. incl. Criteria ..................................................................... 134
5.3.1
Relevant current regulation(s) .............................................................................. 136
5.3.2
Most important trends from WP1, regulations, EuroNCAP etc.. ......................... 136
5.3.3
Future test conditions ........................................................................................... 137
5.3.4
Discussion and conclusions.................................................................................. 138
Discussion and Conclusions........................................................................................... 139
7
List of Figures ......................................................................................................................... 142
List of Tables .......................................................................................................................... 147
Acknowledgements ................................................................................................................ 149
References .............................................................................................................................. 150
8
Glossary
ADAC
Allgemeiner Deutscher Automobil-Club
ADAS
Advanced Driver Assistance System
DDY
Digital Derivative in Y-Direction
ECE
(United Nations) Economic Commission for Europe
EEVC
European Enhanced Vehicle-Safety Committee
EU
European Union
Euro NCAP
European New Car Assessment Programme
FIMCAR
Frontal Impact and Compatibility Assessment Research
FWDB
Full Width Deformable Barrier
FWRB
Full Width Rigid Barrier
GIDAS
German In-Depth Accident Study
GRSP
Working Party on Passive Safety
IMVITER
Implementation of Virtual Testing in safety Regulations
LCW
Load Cell Wall
LTV
Light Trucks and Vans
MPDB
Mobile Progressive Deformable Barrier
NCAP
New Car Assessment Programme
NHTSA
National Highway Traffic Safety Administration
ODB
Offset Deformable Barrier
OOP
Out Of Position
PDB
Progressive Deformable Barrier
RMDB
Research Mobile Deformable Barrier
SafeEV
Safe Small Electric Vehicles through Advanced Simulation
SEVs
Small Electric Vehicles
SOI
Small Overlap Impact
UNECE
United Nations Economic Commission for Europe
US
United States of America
VRU
Vulnerable Road User
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1 Introduction
The objective of the work described in this report is the development of test configurations for
vulnerable road user and occupant protection assessment (incl. compatibility) in accidents
involving small EV’s in urban areas. Small EV’s in SafeEV in particular concern the vehicles
in the mass category of so-called L7e vehicles, where currently hardly any safety
requirements exist.
More specifically the work described here concerns the specification of the methodologies
and tools for safety assessment in the proposed test set-ups (experimental, virtual as well as
hybrid approaches) and the assessment of the applicability of current evaluation criteria for
small EVs in urban areas and promote the development of new criteria where current criteria
are inadequate to address small EVs safety, especially in urban areas. This concerns both
vehicle based criteria incl. fire and electrical safety criteria and injury assessments criteria.
The work was carried out within WP2 of the SafeEV project. WP2 is divided into 3 tasks:



Task 2.1 deals with future test configurations for pedestrian protection in future small
electric vehicles,
Task 2.2 deals with definition of test conditions for occupant protection (incl.
compatibility) assessment in crashes involving small EVs
Task 2.3 focuses on criteria for assessment of small EV safety in crashes in various
test conditions.
The test conditions are based on the results of WP1 of SafeEV and regulatory trends and new
developments in the field of e.g. NCAP were taken into account, as well as the assessment of
pre-crash based injury reduction systems. The work includes specification of the (virtual)
tools to be used (e.g. impactors, virtual models, crash dummies, integrated
experimental/virtual methods).
The test conditions will be applied in WP3 and WP4 of SafeEV for the Reference Electric
Vehicles Models (REVMs) developed and used there. Experience using these REVMs in
these WP’s may result in further refinements and updates of the proposed test conditions.
The original SafeEV project description defined 3 deliverables as a result of the work in WP2:



D2.1 Report presenting the test conditions for vulnerable road users
D2.2 Report on test conditions for compatibility and occupant protection
D2.3 Report on evaluation criteria
A number of the topics described in the above deliverables are very closely linked to each
other or even quite identical like injury criteria to be used and the evaluation of sensor
systems in active safety systems. Therefore it was decided to integrate the results of these
deliverables into the current single deliverable D2.
The next Chapter 2 specifically deals with evaluation of pre-crash and active safety systems
incl. sensor evaluations tests both for pedestrians and vehicles. Chapter 3 deals with methods
for the evaluation of VRU (Pedestrian and cyclist) protection and Chapter 4 with methods for
the evaluation of occupant protection. Chapter 5 deals with criteria to be used in the
evaluations including injury criteria, criteria for compatibility and criteria for fire and electric
safety. Each of the topics described in these chapters will start with an overview of the current
status, followed by, where relevant, with future trends in accident conditions, regulatory
trends and new R&D findings and finally, if possible, a prediction of the evaluation method to
be used for the year 2025. Chapter 6 finally provides a brief discussion and conclusion of the
work carried out in WP2.
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2 Evaluation of Pre-Crash and Active Safety Systems
There is no doubt that Active Safety Systems will play a major role in further reduction of
accidents and mitigation of their consequences in the road transport area. Meanwhile several
visions and targets [1] (see also D1.2) concerning reduction of number of fatalities or injured
road users are formulated.
Especially in urban areas accident severity and configurations might change fundamentally
if Active Safety or Integrated Safety Systems will reach higher market shares.
Since one decade assistance and fully autonomous systems like autonomous braking systems
(AEB) are introduced to the market – mostly together with integrated and also pre-active
restraint system or systems to protect VRU.
Within the APROSYS project [2] (Figure 1) a principle method to evaluate these integrated
safety systems was developed and drafted in terms of a possible transfer to development
guidelines, consumer assessment programs or regulations.
Figure 1. APROSYS – Generic assessment methodology for advanced systems [2].
This approach is now even more specified and worked out in detail by several initiatives
worldwide and was recently transferred and harmonised to be used within future EuroNCAP
protocols.
Due to the fact, that consumer test programs are seen as a main market driver for new
systems, the current status of these protocols is reviewed in this chapter. Specific focus is
given to the addressed conflict situation and test scenarios. In the following also evaluation
methods on system and component level are reviewed and discussed. This particularly is done
with regard to implement such evaluation and especially virtual methods to the projected
SafeEV tool-chain.
2.1 Current status of Pre-Crash & Active Safety evaluation
As mentioned already in the introduction, it is widely recognised that active safety systems or
finally integrated vehicle safety systems will make a large contribution to improve road
safety. Along with the marked introduction of such systems also the development and
harmonisation of appropriate evaluation methods and tools were initiated. Figure 2 gives an
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overview on the most relevant research initiatives and collaborative projects worldwide. Most
of them are practically completed or recently presented their results.
Figure 2. Overview of current / recently finished research initiatives & collaborative projects
concerning development of active / integrated vehicle safety assessment methodology.
According to the EuroNCAP roadmap which has now defined testing and assessment of
Autonomous Emergency Braking systems from 2014 respectively 2016 onwards, a
Harmonisation Platform has been established [3]. The main objective was to exchange
findings, key (test) scenarios and related test parameters and give recommendations for test
procedure and further development of test equipment. Communication and exchange of
information with US (NHTSA) and GRSP was addressed as well (Figure 3).
Within the before mentioned Euro NCAP protocol the following test procedures and test
parameters are now formulated and agreed. For SafeEV “AEB City” and “AEB Pedestrian”
will be the most relevant test set-ups (Figure 4).
As indicated “AEB City” is focusing on a typical inner city accident scenario and will help in
reducing the amount of rear end collisions. According to the Euro NCAP protocol the system
performance will be assessed only when such a system is fitted as standard in the vehicle.
Thereby the test speed range will be between 10–50 km/h. “Avoidance” of rear end collisions
up to 20 km/h is expected. The “Mitigation” score in case a collision cannot be avoided but a
lower impact speed is achieved will follow a linear interpolation of speed. Also HMI aspects
and whiplash performance will be evaluated.
The procedures for the “AEB Inter-Urban” test cluster are also defined. Focus of this test
scenario is the evaluation of the AEB system performance on rural roads or highways.
Therefore higher impact speeds are included and furthermore the rating of supplementary
warning systems (FCW) will be added
12
Figure 3. Harmonisation Platform and involved stakeholders for the implementation of
Active / Integrated Safety assessment procedures – Vehicle/Occupant & Pedestrian Safety.
Figure 4. Test procedure for AEB within EuroNCAP protocol 2014 / 2016. [3]
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Assessment protocols for lane departure or crossing traffic are under consideration as of 2016.
For this, also the evaluation of “real world based performance” is discussed.
The test procedures for Autonomous Emergency Brake system for Pedestrians are still under
consideration. Proposals from vFSS, AEB, ADAC and the EU project ASPECSS [ASPECSS
project GA No. 285106] were presented and discussed in a workshop in March 2013. So far
for a “phase 1” (as of 2016) two test scenarios for such forward looking sensor based systems
are agreed (Figure 5).
Figure 5. Test scenarios for AEB-Pedestrian within EuroNCAP rating 2016. [3]
More specific test parameters are still under consideration. Figure 6 shows the current
proposal as it was discussed and presented by AsPeCSS during the workshop March 2013.
Figure 6. Proposal for Test scenarios and test parameters [4].
The draft Euro NCAP protocol is displayed in Figure 7. Starting from 2016 additionally to
impactor tests to prove the structural measures of the vehicle front via head form and upper
and lower leg form tests, active safety tests are planned.
14
Figure 7. Draft Euro NCAP protocol 2012–2017 [3].
In the course of the ASPECSS project also a method for integrated evaluation for combined
autonomous systems and protective devises upon impact was developed as it was suggested
by APROSYS as well. Along with this, theoretical boundary conditions for avoidance and
mitigation capability of a forward looking system were formulated and presented with a socalled “shark´s fin curve”, see Figure 23. Finally a possible speed reduction is calculated
considering different performance levels of the system and correlated with the respective
physical parameters (brake onset, brake force build-up, etc.). This applies in particular for the
“obstruction” scenario. A possible procedure for the pedestrian impact case is detailed in
section 2.2.1, see Figure 9.
Another main objective of the before mentioned initiatives was also the development and
harmonisation of test devices and equipment.
High amount of work has taken place in the development of a target representing a pedestrian.
Also these activities and recommendations are now harmonised within the dedicated
Harmonisation Platform to arrive at technology-independent test procedure and devices.
Figure 8. Example for test equipment for AEB-Pedestrian assessment – propulsion systems
and pedestrian targets evaluated within ASPECSS, AEB & vFSS. [5]
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2.2 Evaluation of safety systems – component and sensor level
2.2.1 Pedestrian safety
Accident scenarios
The two relevant pedestrian safety scenarios from Euro NCAP test protocol for 2016 include
the scenarios “Unobstructed pedestrian walking 90° from near side” as shown in Figure 2
(left) and “Obstructed pedestrian running 90° from near side” (right). Basis is the use of an
Automatic Emergency Braking (AEB) System for pedestrian detection. The testing details are
to be published soon. Further scenarios are to be introduced later.
Starting with the availability of surround sensing in the last decade primary safety measures
(e.g. accident avoidance via pre-crash sensors) augment the overall safety level of the
secondary safety measures (passive safety). Although measures of integrated vehicle safety
may allow for the lowering of the level of passive safety measures, it has already been
announced that a lowering of the passive safety measures will not be acceptable for the future.
In a recent publication the activities of a joint research project of IKA/FKA Aachen and the
German Insurers Accident Research on the integrated pedestrian safety assessment was
reported ( Figure 9).
The presented procedure enables an integrated assessment of active and passive pedestrian
safety measures on one scale for both children and adults. Thereby structural characteristics of
a vehicle front are combined with accident kinematics and accident research data. One key is
the correlation between collision speed and head index value that forms the interface between
active and passive safety. This index value indicates the risk for an AIS3+ head injury due to
the primary impact depending on the collision speed. Possibly this procedure may be included
into a SafeEV safety assessment.
Figure 9. Integrated Pedestrian Safety Assessment: Assessment methodology for adults (left),
simulation models of generic vehicle class representatives (upper right), safety assessment
overview for adults (lower right). [6]
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From WP1 it becomes clear that in urban traffic in 2025 with most of the cars equipped with
active safety measures focusing on automatic emergency braking functionality various
pedestrian accident scenarios won’t occur anymore. The most critical pedestrian collision
impact case in 2025 will be the obstructed pedestrian case, e.g. a pedestrian crossing the street
between two parked vehicles. This means that the pedestrian detection based on state-of-theart forward looking sensor systems will pose a great challenge and possibly impacts are not
avoidable in all cases. As a result the impact point in these cases will skip from the centre line
of the car in direction to the obstructed pedestrian side, see Figure 10.
Figure 10. Analysed impact positions from WP1.
The outcome of the on-going AsPeCSS project is a suite of tests and assessment methods as
input to future regulatory procedures and consumer rating protocols. Implementation of such
procedures and/or protocols up to the end of this decade will enforce widespread introduction
of surround sensing systems in the vehicle fleet. Tests with advanced prototype vehicle shows
only limited performance for the obstructed pedestrian case, since the time from visibility to
braking is lower than 250 ms, the time for brake force build-up lower than 350 ms and a brake
onset is needed even before a pedestrian reaches the vehicle path ( Figure 11). Thus the
scenario show in Figure 10 will represent a challenging task.
Figure 11. Test results of 2016 AEB-Pedestrian scenarios (left) and obstructed scenario with
running child (right). [4]
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Sensor evaluation tests
The output of active safety systems based on surround sensing systems is a trigger signal for
actuators. The following sensor principles are available for pre-crash pedestrian safety
systems: Mono/stereo cameras, short-range radars (SRR, 24 Ghz) or long-range radars (LRR,
77 GHz), Photonic Mixing Device (PMD) or Infrared (IR) Photonic Mixing Device and Light
Detection And Ranging (LIDAR) sensors. In the classical AEB case the trigger signal as
result of surround sensors will induce a braking manoeuvre. However, in the future also
steering manoeuvres may be triggered. Depending on the system also warning signals can be
triggered before. Alternatively passive safety measures at the vehicle may be triggered, i.e. an
active vehicle hood actuator or a window bag as well as some active front structure measures
may be activated. Typically an active hood or a-pillar based safety systems is triggered based
on contact sensors, e.g. in the front structure of the vehicle. For actuators integrated in the
front structure pre-crash systems are needed, i.e. reversible structures require a “pre-fire”
system while an irreversible structure/airbag requires a “pre-trigger” system. It should be kept
in mind, that pre-crash activation of irreversible safety measures for a following impact with a
pedestrian are critical in view of robustness. Therefore this line of action is not followed up
here.
The trigger signals are the outcome of complex sensor model and algorithms and have to be
verified by an extensively validation basis in order to guarantee a high robustness of the
decision making. The simulation of active safety sensors can be done based on geometric
considerations. The main challenge for evaluation tests of surround sensors is the validation
of the robustness. Typically this is done through validation drives over lots of kilometres.
Thus, a pure simulative validation and evaluation of the respective sensors without inclusion
of “real data” makes no sense. Therefore, in the following the focus is laid on passive safety
pedestrian sensors and the according requirements for sensor evaluation tests.
Pedestrian safety sensors
In Figure 12 the systematic and definition of test setups for actuator based in-crash safety
systems is described and in Figure 13 the respective impact zones according to Euro NCAP
test protocol are given. Based on simulation runs the hardest to detect pedestrian size has to be
identified and the appropriate Pedestrian Detection Impactor (PDI) has to be chosen. In total
around 200 tests are needed, whereby the velocity, the test object and the impact points are
varied.
Figure 12. Assessment of vehicles with active bonnets:
Methodology of testing (left), definition of test setup (right) [7]
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Figure 13. Impactor test procedure according to Euro NCAP test protocol [8]
Crucial point for a sensor evaluation in view of a correct pedestrian detection in the front
bumper is the weight of the respective impactor. A Lower Leg Impactor (LLI) as upper limit
has a weight of 13.4 kg, while the 1st Generation Pedestrian Detection Impactor PDI-1 as
lower limit test representing a small child weights 9.9 kg. In order to have one impactor that
represents the worst case for the sensor triggering („hardest to detect“) and that can be used
for all vehicle categories, the 2nd Generation Pedestrian Detection Impactor PDI-2 is currently
being evaluated. Its weight is around 6.8 kg. The impactor development is driven by a joint
initiative of the European Automobile Manufacturers’ Association (ACEA) and Concept Tech
Group (Austria) under consideration of input by the German Federal Highway Research
Institute (BASt) and safety sensing systems’ supplier IEE. Along with a lower weight of the
impactor for different pedestrian sizes the requirements for the respective sensor system will
further increase. An overview of different impactors is given in Figure 14.
Figure 14. Pedestrian impactors: FlexPLI (left), PDI-1 (middle), PDI-2 (right) [7]
State of the art pedestrian safety systems consist of one or more sensors, an electronic control
unit including an algorithm and reversible or irreversible actuators, see Figure 15 (left). These
systems have been primarily introduced in order to cope with the inclusion of pedestrian
protection in Euro NCAP rating in the last decade. To fulfil these requirements pedestrian
safety actuators have been developed. Examples are active hood systems or front window/apillar airbags (outside), see Figure 16. In case of a pedestrian impact the hood is lifted to
19
increase the deformation zone between the pedestrian and the engine compartment, see
Figure 15 (right).
Figure 15. General logic of pedestrian safety system (left) and schematic of
in-crash triggering of active bonnet (dummy only used for visualization) (right [212].
Figure 16. Pedestrian safety actuators: Reversible hood lift-up Mercedes C-Class (left),
irreversible hood lift-up by window airbag in Volvo V40 (2012) (right).
Various sensor principles are available like acceleration sensor based systems or pressure tube
based systems.
In the case of acceleration sensors these are typically integrated in the front bumper. The
micromechanical acceleration sensors employed in the system work with a technology that
has already been well established in crash sensing for years. In this way pedestrian protection
electronics can reliably and cost-effectively fulfil the requirements of pedestrian protection.
Furthermore this type of system is simple to integrate and does not alter the appearance of the
front end of the vehicle. In future the system will additionally make use of signals from
vehicle surround sensors to react even faster by pre-calculating the impending collision.
Since the introduction of irreversible actuators for hood lifting and airbags the requirements
for pedestrian protection sensing increased significantly, improved sensing system with even
higher performance and - even more important - higher robustness have been developed.
Thereby it is crucial that the object detection is robust, e.g. that the case pedestrians and
cyclists versus trash can be discriminated. Air hose based Pedestrian Collision Detection
Sensors allow for a higher robustness, see Figure 17. These systems consist of an air hose
that is laid across the entire width of the car in its front bumper situated directly behind a
foam block that is fitted at the front of the vehicle to absorb energy. Standardized pressure
sensors are installed at either end of the air-filled pressure hose. When a vehicle collides with
an obstacle, the resulting pressure creates a typical waveform that is detected by the two
20
sensors at the ends of the hose and forwarded to the airbag control unit. The signal
propagation time also allows conclusions to be drawn about the location of the impact.
Figure 17. Pressure-hose based pedestrian safety system:
Schematic consideration (left) and integration in front bumper (right). [9]
In WP1 subtask “Pedestrian Kinematics Analysis”, see Chapter 6 of SafeEV D1.1 [68], a
methodical approach for analysing pedestrian accident scenarios involving Small Electric
Vehicles (SEVs) in the coming years was derived. The objective was the analysis of the
pedestrian kinematics and head impact conditions using multi-body systems considering four
Electrical Vehicle (EV) geometries, a number of pedestrian sizes and positions and a number
of car impact velocities. Apart of the main outputs in view of head impact conditions also the
time difference between the first body contact with the impacting vehicle (leg vs. bumper) and
the second body contact (head vs. windscreen) was investigated. In Figure 18 a table with
different time differences for adult and child pedestrians impacted by two vehicle types
(“inclined” and “flat”) are given in relation to the impact velocity.
Figure 18. Time between first body contact and head impact on windscreen for flat and
inclined car geometries - Relevant case 11.1m/s ~ 40 km/h, WP1. For examples of flat and
inclined car geometries see Table 6, Safe EV D1.1 [68]
As can be seen the minimal required time for the relevant case of a 40 km/h impact between
first contact and thus detection of a contact and the second contact is tmin = 19 ms (26 ms – 7
ms). The minimal case is obtained for a flat front geometry vehicle impacting a child. For
adult pedestrians a minimal value tmin = 57 ms (59 ms – 2 ms) is obtained. This represents the
time for detecting a possible impact td, plausibilisation of the impact tp, activating a pedestrian
safety actuator ta and finally having this actuator in full function tf. Thus
t = td + tp + ta+ tf < tmin
td and tp depend on the sensor system and the algorithmic capabilities. ta depends on the delay
time of the actuator after triggering and finally tf depends on the performance of the actuator.
For example if the actuator is a window bag this time defines the time for fully inflating the
window bag or in case of an active a-pillar the time needed for fully reducing the according
21
contact stiffness. It becomes clear that a realization of an in-time activation of the passive
safety system requires efforts on the sensor system and according intelligence (td + tp) as well
as on the actuator (ta+ tf).
Generally sensors are not separately evaluated. An evaluation is solely done in view of the
complete system and the function. Thus, starting from the (performance of the) safety
function a decision cascade is set up. In view of virtualization of sensor tests, the same
considerations as described in the paragraph concerning sensor evaluation tests are valid.
2.2.2 Occupant safety using surround sensing
Accident scenarios
The two relevant AEB safety scenarios from Euro NCAP test protocol for 2014 include the
scenarios “AEB City” and “AEB Inter-Urban” as shown in Figure 4. Basis is the use of an
Automatic Emergency Braking (AEB).
One outcome of WP1 is that frontal impacts in a typical rear-end collision situation for the
SafeEV target vehicle will diminish until 2025. Furthermore the collision velocity in these
cases will diminish. It can be derived, that side crashes will cover a greater share of accidents
with SEVs in 2025, see Figure 19. Thus, additional AEB scenarios covering crossing
scenarios may be introduced at the end of this decade.
Figure 19. Extracted from SafeEV Deliverable D1.2, Fig. 21 [53]
Sensor evaluation tests
Similar as for the AEB pedestrian case the output of active safety systems based on surround
sensing systems is a trigger signal for actuators, e.g. a braking manoeuvre will be induced. As
explained before the trigger signals are the outcome of complex sensor model algorithms and
have to be verified by an extensively validation basis in order to guarantee a high robustness
of the decision making. Comparable to the pedestrian safety case a pure simulative validation
and evaluation of the respective sensors without inclusion of “real data” from validation
drives of a car equipped with the according sensors, makes no sense. However, as alternative
to an active safety sensor evaluation a field of effect analysis, comparable to the procedure
presented in SafeEV WP1 may be carried out. Via a stochastic accident prediction approach
based on identified accident types various accident simulations are performed and accident
parameters such as collision velocity have been analysed. Finally, the field of effect of certain
22
functions can be evaluated. The procedure, shown in Figure 24, allows for a field of effect
analysis that may be used for a sensor layout design. One may use the generic sensor
information in combination with the geometric considerations of the (real) accident scene and
analyse the field of effect of a new safety system based on accident analysis retrospective
data.
In the following the focus is laid on in-crash sensors and the corresponding requirements for
sensor evaluation tests. Classical in-crash sensors are inertial acceleration sensors, for
example included with the electronic control unit or a sensor unit within the vehicle.
Acceleration sensors represent a state-of-the-art sensing principle for crash detection and are
used as inertial sensors as well as satellite sensors (up-front) at the front or side structure of a
vehicle. Additionally pressure sensors included in the doors or b-pillars are used for a
detection of side crashes. The relevant occupant safety related sensor layout is displayed in
red in Figure 20.
Figure 20. E/E architecture including occupant safety related sensor layout (in red [211]
Occupant Safety Sensors
State of the art occupant safety systems consist of a sensor layout as introduced above, an
electronic control unit including an algorithm and reversible or irreversible actuators, see
Figure 21 (left). Various reversible an irreversible systems may be triggered. In-crash
detection typically triggers irreversible systems, like variable airbags, belt retractor, belt load
limiter, seat-included system etc.
A crucial element for optimal occupant protection is the matching of the airbag deployment
with the occupant's forward position. An optimal seat-belt protection requires that the seatbelt tensioners are triggered as early as possible in co-ordination with the airbag.
23
Figure 21. General logic of occupant safety system (left) and
typical in-crash triggered restraint systems (right [212]
After frontal impact, today side impact is the second most frequent type of impact. To allow
sufficient time for the deployment of the lateral protection systems after a collision, the airbag
control unit has to determine in less than 5 milliseconds, dependent on the type and severity of
the impact, whether triggering is required or not. Rear collisions even at low speeds
frequently lead to whiplash associated disorders. Airbag control units offer the possibility of
deploying active headrest systems. Many crashes with fatal outcome for vehicle occupants are
associated with the vehicle rollover.
The most relevant cases for the target SEV within an urban environment in 2025 are [68]:



Side crashes in crossing/intersection accidents
Front crashes (head-on collisions) with lower velocity due to active safety systems
Oblique front crashes at crossings and intersections
Therefore, the focus for the sensor related evaluation in view of occupant protection will be
laid on these scenarios.
Front Crash
The type of front crash will change throughout the next years along with the introduction of
AEB systems. We will encounter a skip from front crashes of the type “rear-end crash” to
more oblique frontal crashes, e.g. due to left-turn or right-turn (UK, IRL) accidents at
crossings etc. Theses crashes could be reflected by barrier tests with an inclined vehicles
position, see Figure 22 (left) and Chapter 4.1.
Figure 22. Oblique Moving Deformable Barrier (MDB) test according to FMVSS 208 [10]
Side Crash
Regulation and consumer information requires side impact crash tests with barriers (ECER95, 96/27/EG, Euro NCAP, IIHS) and with a pole (Euro NCAP, US NCAP, FMVSS201,
FMVSS 214). According to SafeEVs WP1 estimations of accident situations in urban
environment for SEVs in 2025 pole crashes will possibly be less important. In particular if
one takes into account that Electronic Stability Control (ESC) systems will limit lateral
movement in urban driving situations and possibly side crashes with signal lights will only
appear as result of an initial side crash if additional systems like a Multi Collision Brake
24
(MCB) system that applies the brakes to prevent or mitigate a subsequent impact have not
taken effect. For “classical” car geometries as todays A-/B-segment vehicles in the barrier
tests the vehicle doors and the B-pillar are both hit. The crash impulse is directly transferred
to the B-pillar of the vehicle. Sufficiently fast crash detection with a system composed by
only one acceleration sensor located in the B-pillar is a challenge. Therefore in most cases the
in-crash side crash detection is based on front door-integrated pressure sensors. In these cases,
the outer door panel is pushed inwards and creates an excess pressure inside the door. If the
change in air pressure inside the door exceeds a certain threshold limit, the sensor will transfer
a corresponding signal to the airbag control unit. Depending on the vehicle class additional
acceleration sensors may be fitted in the vicinity of the C-pillars so that a more robust
detection can be realized.
Starting in the beginning of the 2000s the increasing amount of SUVs (sport utility vehicles)
on European roads influences the accident picture in crashes with higher mass vehicles
drastically compared to above crash tests. Thus, the classical mass and geometry
incompatibility problem is not sufficiently encountered by conventional side impact tests. In
the case of a side crash of a larger and heavier vehicle with a SEV a higher percentage of the
SEV side is impacted compared to a “standard” A-/B-segment vehicle. In addition to the
(front) doors and the B-pillar, also A- and/or C-pillars as well as one of the axes of the SEV
will be impacted. Thus, more of the vehicles’ structural components will experience a crash
impulse transfer, making the solely use of acceleration sensors at B- and A- or C-pillar apart
from inertial sensors within the control unit more reliable. Furthermore local intrusion in the
door region will often be smaller in small shorter EV’s compared to “standard” A-/B-segment
vehicles letting more space for side crash relevant restraint systems. However, on the other
side the requirements for the triggering of the restraint system will increase, i.e. faster
triggering and thus faster and more robust detection is needed.
2.3 Trends & Options for Virtual Evaluation
In general it can be stated, that performance testing of active safety systems has to be done by
applying hardware tests as described under 2.1. Due to the nature and specific focus of
performance aspects like target & object recognition based on different environmental sensor
technologies on the one hand and complex decision taking algorithms and triggered measures
like autonomous braking on the other hand, a test set-up in a real environment seems to be the
only way.
However, if the scope of assessment is extended to an integrated system evaluation or
efficiency analysis in terms of system impact in real life, virtual testing and methods might
become a crucial and indispensable part in the future.
As already applied partly within WP1 and shown in general in Figure 13 and Figure 16 only
simulation respectively supplementary virtual tools will allow a continuous observation and
evaluation of an integrated system in terms of benefit based assessment as it is formulated e.g.
within AsPeCSS.
Within SafeEV WP1 an assessment methodology based on a stochastic analysis was
developed that allows an estimation of the impact of future drive assistance systems on
different recent and future crash scenarios, see Figure 24, left. In WP1 a focus was laid on the
use of generic information in combination with geometric considerations of the accident
scene, see Figure 24, right.
25
Figure 23. Exemplary depiction of a complete virtual tool chain for integrated system
evaluation – Simulation of active safety systems in real world scenario and derived effective
physical parameters for “avoidance“ & “mitigation” (velocity, time to collision etc. - here
displayed with “shark´s fin curve” from AsPeCSS project) > Transfer of initial “mitigation”
parameters to crash simulation and evaluation of injury risk).
Currently also a specific pre-crash time period (before the crash event) in view of an
integrated safety functionality is identified and discussed in particular for an application of
virtual evaluation methods that include the use of appropriate virtual active human body
models. This time period is typically larger than the classical “pre-crash” phase and is related
to the occupant kinematics due to vehicle dynamics as well as the interaction of the active
human model with restraint systems. A relevant time frame covers up to approximate 2 sec
before the crash event occurs. Three research groups and initiatives (OM4IS, SAFER, TNO &
University Delft) are working on basic research and related simulation methodology to
implement realistic active human behaviour and muscle reaction in human body models.
This research and development is based on the broadly converging view, that this time period
will only be accessible by virtual methodology (see also section 5.1 – injury criteria) and not
through real pre-crash tests and crash tests with hardware dummies.
The simulation of complete crash scenarios including the pre-crash phase is a topic of ongoing research. First commercial products that allow simulations of driver assistance,
collision avoidance but also crash severity and occupant injuries are available now, see
Figure 26. Crucial point for a validation of the occupant injuries is a correct representation of
the vehicle and – even more important – the occupant in the pre-crash phase. In order to
capture the occupant kinematics correctly a further development of active human models is
needed.
26
Figure 24. Co-simulation including generic surround sensor models from SafeEV WP1.
[Peter Luttenberger, Ernst Tomasch, TU Graz]
Figure 25. Overview on current research initiatives and development concerning
implementation of human behaviour / active muscle reaction to human body models
(OM4Is [12], SAFER [13] and TNO [14].
2.4 Discussion and conclusions
High amount of work has taken place in the previous decade through European projects like
ASSESS and finally ASPECSS in view of an integrated evaluation for combined autonomous
systems and protective devices. For Pedestrian Safety aspects finally a harmonized target
representing a pedestrian and recommendations that arrived at technology-independent test
procedure and devices were elaborated. For vehicle to vehicle collision avoidance procedures
for “AEB City” on typical inner city accident scenarios and the “AEB Inter-Urban” for higher
test speeds have been defined.
27
Figure 26. Co-simulation of passive and active simulation tools during pre-crash phase. [15]
It was shown that the output of active safety systems based on surround sensing systems are
the outcome of complex sensor model algorithms and have to be verified by an extensively
validation basis in order to guarantee a high robustness of the decision making. The
simulation of active safety sensors can be done based on geometric considerations. The main
challenge for evaluation tests of surround sensors is the validation of the robustness. Typically
this is done through validation drives over lots of kilometres. The simulative validation and
evaluation of the respective sensors is not feasible (yet). Therefore, the focus in this work was
laid on passive safety pedestrian and crash sensors and the according requirements for sensor
evaluation tests in which simulations can be used.
For pedestrian safety sensors we have shown that through their geometry SEVs pose a
challenge on the setup of the sensor layout as well as on the sensor itself and trigger time of
in-crash safety systems for pedestrians. Since the most relevant cases for the target SEV
within an urban environment in 2025 are side crashes in crossing/intersection accidents as
well as oblique front crashes at crossings and intersections the classical mass and geometry
incompatibility problem has to be sufficiently encountered by the crash sensors as well as the
restraint systems.
Finally we have shown that only simulation respectively supplementary virtual tools will
allow a continuous observation and evaluation of integrated safety systems in terms of a
benefit based assessment.
28
3 VRU (Pedestrian and cyclist) protection
In WP1 an overall future pedestrian scenario definition has been developed, combining
statistics, numerical simulations and a Delphi Method. The final goal within the project is to
define a virtual tool chain for the assessment of small electric vehicles for different impact
conditions in “2025”. In this chapter vulnerable road users are in the focus for the definition
of testing proposals. In Figure 27 the most relevant inputs and outcomes are shown. Relevant
issues will be discussed below.
Figure 27. Methodology for the definition of the vulnerable road user test proposal.
3.1 Relevant current regulation (s) test methods etc..
There are currently no regulations which include all groups of vulnerable road users (e.g.
cyclist, with/without helmet), but for pedestrian accidents they are well defined which can be
seen in Table 1.
All of these test conditions focus on three “body part groups”, namely head, lower leg, upper
leg. In Figure 28 all currently used or developed impactor geometries are shown.
These impactors are used on defined positions at the front of a vehicle for evaluation of the
injury risk. These tests and impactors were derived from statistical aggregation and were
further developed (e.g. FlexPli) to show a better biofidelity. The regulations are defined for a
M1 vehicle class. These impactors are available as FE-models too which are used in the
vehicle development process.
29
Table 1. Current Regulation and Standards for pedestrian testing.
Regulation & Standards Information
ECR 78/2009 EC
“Regulation (EC) No 78/2009 of the European Parliament with regard
to the protection of pedestrians and other vulnerable road users.”
ECR 631/2009 EC
“Commission regulation (EC) No 631/2009 of 22 July 2009 laying
down detailed rules for the implementation of Annex I to Regulation
(EC) No 78/2009.”
GTR No. 9
“Global technical regulation No. 9, Pedestrian Safety (Established in
the Global Registry on 12 November 2008)”
EuroNCAP
“Pedestrian Testing Protocol (Acceptable models and codes are
detailed in Technical Bulletin TB013)”
KNCAP
Korean NCAP
JNCAP
Japan NCAP
Trias 63
Japan Homologation
Figure 28. Current impactors which are used or planned for pedestrian testing [16].
3.2 Most important trends from WP1, regulations, EuroNCAP etc..
In WP1 the final scenario was described as near and far side crossing accident while the
vehicle is going straight. The pedestrian could be obstructed or not. The most frequent and
relevant impact speed was found to be between 25km/h to 30km/h, supported by the Delphi
method and stochastic simulations, but also accidents with a higher velocity will occur due to
sensor failure, obstruction of the VRU, bad weather conditions or there is no AEB system in
use.
A second loop of the stochastic analysis was performed to get results regarding the impact
location on the vehicle front-end. Therefore the same set-up was used, which is described in
D-1.1[17]. The results for impact speeds between 25 km/h to 30 km/h and 45 km/h to 50 km/h
is shown in Figure 29 (including different pedestrian walking speeds). It can be seen that the
focus for pedestrian testing, with a future SEV equipped with an AEB system should be set to
30
the nearside front end, where nearside is defined as the side where the vehicle geometry is
nearer to the street side boundary. In more than 60% of the accidents the pedestrian is hit
within the first 20% of the vehicle. 90 % of all cases are located between the vehicle sides up
to 60% of the vehicle front end in y-direction depending on near- or farside accidents.
Figure 29. Stochastic pedestrian impact analysis showing the location of first contact of the
pedestrian on the vehicle front for nearside collisions and two vehicle speed ranges.
Reviewing testing protocols and projects
In EuroNCAP [18] the possibilities for virtual testing of pedestrian protection are increasing.
The body parts of interest are head and legforms which are tested against the vehicle front.
In the EU project IMVITER [19] a HBM was compared against standard impactors and a
validation procedure for numerical models was developed. The most important issues which
were defined as Requirements, are overall model quality, material data, mesh quality and joint
models. The comparison between the leg impactors (Lower Leg (TRL), FlexPli) and the full
HBM showed that the impactor should be modified in height as proposed in APROSYS and
an upper body mass should be attached to improve kinematics. As the impactor simulates only
one leg the contact forces were different compared to the full HBM because of a second
contact with the other leg which influenced the results of the struck side leg.
Maki et al [20] analysed pedestrian and bicycle accidents from Japan and came to the
conclusion, regarding the head impact locations, that these next to a-pillar and near the
windscreen edges are more severe because of the stiffer vehicle parts. Due to left hand traffic
in Japan the first nearside half seems to be the most frequent impact area. Another study from
Sturgess et al [21] showed a similar trend. The analysed pedestrian accidents, showed an
accumulation of head impacts points near the a-pillar where for UK data the side was
changed, because of the left hand traffic.
For cyclist accidents, Maki et al [20] found that a 90% of all accidents happened with a cyclist
speed below 10km/h and a higher injury risk (>50 %) occurred when the cyclist was struck by
the side. The location of the cyclist at an impact against a motorized vehicle with a head
impact on the front was found to be with a saddle position between the first two thirds of
31
travelling direction on the vehicle front end and with a cyclist speed below 10km/h. Boufous
et al [22] did a database analysis for cyclist accidents in Victoria (Australia) and showed that
94.6 % are Urban accidents where one of the most frequent and more severe accident was an
adjacent type at intersections. 82.6% of all accidents occurred at a maximum vehicle speed
limit of 60 km/h. Van Schijndel et al found that the average car velocity at an impact was
35 km/h and most frequently occurred in crossroads (Dutch cases) [23]. Combining this with
D1.1 results a reduction of impact speed is possible due to active systems and more 30 km/h
speed zones. Therefore the lower speed range should be in focus for the proposal. However,
pedestrians should be tested with a higher speed range anyway, which means there will be
certain protection for cyclist too.
Amoros et al [24] analysed cyclist accidents in France (Rhone). From the published statistics
it can be derived that MAIS 1 and MAIS 2 are the most frequent injury classifications which
is in the worst case a possible moderate injury. The work from Bauer et al [25] showed the
injury possibility in direct comparison to pedestrians. The “chance” to have a non-fatal injury
is 3 times higher whereas for fatal injuries it is less than one-third of all pedestrian accidents.
An additional issue which was shown in Amoros et al was the AIS 2+ injury description for
teenagers and adults involved in inner-city cyclist to motor vehicle accidents. There the three
most frequent and ascertainable injuries are fractures (56.6 %), internal organ injuries (17 %)
and “dislocations, sprains and strains” (5.1 %).
Töro et al compared cyclist and pedestrian against vehicle occupant injuries. The results
showed a higher risk for skull fractures, brain contusion and haemorrhage, respectively for the
heads. Other described injuries were heart contusion, aorta laceration, rib fractures, liver
contusion, pelvic fracture and upper/lower limbs contusion or fractures. [26]
These injury types are really difficult or impossible to predict with actual impactors as shown
above (e.g. “steel head”, LowerLeg or FlexPli) and therefore would prefer the use of a full
HBM model for future cyclist and pedestrian test methods.
In a recent study, Bourdet et al 2012 [27] a total of 24 bicyclists’ accident cases with head
injuries have been reconstructed. For each accident case, body kinematic has been simulated
using MADYMO.
Figure 30 represents the distribution of vehicle and bicycle velocities just before impact.
These velocities were obtained from the validated numerical accident reconstructions. It can
be observed that for most of the cases the bicycle velocity was between 5 to 15 km/h.
Figure 30. Distribution of vehicle and bicycle velocity before impact.
The results show that the head is impacted more often on top parietal zone, and the mean
impact velocity is 7 m/s with 5.5 m/s and 3.4 m/s for normal and tangential components
32
respectively. All reconstructed head impact gave results in accordance with the damage
actually incurred to the victims.
In order to evaluate the head impact condition in case of bicyclist accidents against vehicle, a
parametric study was performed as depicted in Figure 31. A total of 5184 accident scenario
were simulated on the four vehicle shape selected from WP1.
Figure 31. Description of the parametric study.
Except for the out wheel shape, most of the head impacts are located on the windscreen, as
reported in Table 2. The normal relative head impact velocity varies from 5.2 m/s for the
inclined shape to 7.6 m/s for the bonnet shape for a mean car velocity about 10 m/s.
In order to implement model based head injury criteria an attempt was made by Bourdet et al
2011 [28] in which the Strasbourg University Finite Elements Head Model (SUFEHM) is
used in conjunction with a lumped model of the impact point at bonnet level. The approach
consists in proposing a lumped model of the bonnet based on the experimental response of a
pedestrian ISO headform impacting the bonnet surface at a velocity of 11 m/s and an impact
angle of 60°. During this experimental tangential headform impact, both linear and rotational
headform acceleration are recorded, and these data allow to characterize the mechanical
properties of the bonnet lumped model.
Table 2. General results of the bicyclist collision parametric study.
Bonnet
Inclined
Flat
Out-wheels
Car velocity [m/s]
10.1 ± 4.6
10.2 ± 4.5
10.0 ± 4.6
9.3 ± 3.6
Resultant velocity [m/s]
Normal velocity [m/s]
Tangential velocity [m/s]
Head Impact Angle [deg]
10.1 ± 4.7
7.6 ± 3.2
6.2 ± 4.1
36 ± 14
8.9 ± 4.5
5.2 ± 2.5
7.0 ± 4.1
50 ± 13
9.4 ± 5.3
6.4 ± 3.9
6.7 ± 4.0
47 ± 13
7.2 ± 4.0
3.1 ± 1.6
6.3 ± 4.2
60 ± 15
Head Impact Points
Car Impact Points
33
As a demonstrator the approach was conducted numerically on a car bonnet FEM which was
impacted by an ISO headform FEM. The validation of the method consists in simulating the
impact of the finite element model of the headform-bonnet lumped model and comparing its
response to the headform FEM impact against the complete bonnet FEM simulation in terms
of resultant linear and rotational acceleration. In a last step the SUFEHM is used for the
simulation of the impact against the above defined bonnet lumped model in order to assess the
injury risk for the impact point under study. The procedure test is illustrated in Figure 32.
Step 1: Validation procedure
Step 2: FE test procedure
Real pedestrian test
Predictif head FE
model
Y Ro ta ti o na l He ad Ac cel e ra tio n [ra d/s²]
Re s u l ta n t Li n ea rHe ad Acc el era ti o n [m /s ²]
6 head accelerations
1500
1250
1000
750
500
250
0
0
10
20
30
Ti m e [ms ]
6000
4000
2000
0
-2 0 0 0
-4 0 0 0
-6 0 0 0
40
-8 0 0 0
0
50
10
20
30
40
50
Ti m e [ms ]
« Bonnet point »
validated model
Resultant Linear Head Acceleration [m/s²]
« Bonnet point » validation
Normale Force [N]
Force-displacement curves computed
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
0
1500
Finit Element Model
Lumped Model
10
20 30 40
50
Displacement [mm]
60
70
1250
1000
750
Pedestrian test simulation
500
250
0
0
10
20
30
40
50
Injury risk based
on biomechanical
criteria
Time [ms]
Figure 32. Representation of procedure test of bonnet and windscreen severity
using the combination of experimental test and FE simulation.
Concerning lower limb, a study published by Arnoux et al.[29], [30] suggests an evaluation
of injury risk for knee using a lower limb FE model. This study shows how numerical
simulation can be used to conduct injury mechanism analysis and then to postulate on a knee
injury criteria under lateral impact. It focuses on relationships between ultimate lateral
bending and shearing at knee level and potential ligament damage, based on subsystem
experimental tests. These ultimate knee lateral bendings and shearings for potential failure of
ligaments (posterior cruciate, medial collateral, cruciates and tibial collateral) were estimated
at 16° and 15 mm in pure lateral shearing and bending impact tests respectively. Finally this
methodology was applied on a full test of pedestrian impact, as illustrated in Figure 33.
3.3 Future test conditions
The introduction of Small Urban Electric Vehicles requires, due to new vehicle front-end
designs and technological improvements in active safety systems updated test methods for
vulnerable road user protection. In this section two proposals for pedestrian protection and
one for cyclists protection are defined.
Pedestrian proposals.
A virtual testing proposal which has two main paths has been developed, focusing on full
body or body part evaluation supported by a “sensor effectiveness” evaluation which was
intended to run parallel and effects the overall scoring of the pedestrian testing, either in a
positive or negative way.
34
Figure 33. Lateral and frontal view of the pedestrian impact situation.
With respect to the information mentioned before, the body part path was excluded as there
are only head and lower leg FE models available (e.g. Standard impactors, human leg [31],
human head [32]) but nothing which could be used for thorax, hip, internal organs or upper
extremities evaluation. As it was discussed that full body kinematics would be preferable a
standard impactor again cannot fulfill this issue. Also different vehicle designs will be
available (flat, inclined, short bonnet, outstanding wheels) which are influencing the impact
speeds and locations shown in the deliverable 1.1 of this project.
For the second path regarding the full body model with a predefined vehicle speed two
options were proposed, but as one of these would have again focused on body parts it was not
appropriate to investigate this much longer than it is shown in Figure 34. The last path was
chosen due to best fitment for future safety needs. There, the vehicle is supposed to impact the
pedestrian (full HBM) with a predefined speed. The speed boundaries were derived from
D.1.1 results:


Minimum lower boundary: 25 to 30 km/h (with AIS2 injury risk)
Maximum upper boundary: 45 to 50 km/h
The actual proposed vehicle speeds for “virtual assessment” which will be used in the project
for further investigation are in the range of 25 km/h to 30 km/h and 45 km/h to 50 km/h.
The lower velocity range focuses on the majority of expected cases considering AIS2 injury
in future accident scenarios as described in more detail in Deliverable 1.1. A second group
was defined to include accidents with a higher risk for severe injuries, because of AEB system
failures, obstructed pedestrians and other road surface conditions with less friction. For the
higher impact speed range less FEM simulations are planned and higher threshold values for
criteria should be defined.
For the assessment process 4 sizes of HBM´s are included: 6 year old child, 5% Female, 50%
Male, 95% Male
For all simulations only one gait should be used which should correlate with the active safety
procedure.
35
Figure 34. Overall testing proposal for vulnerable road users showing different paths
which are discussed and reduced for a final variant (green arrows).
The second issue in pedestrian testing proposal is the positioning of the HBM. Two different
ways were discussed. One would use some kind of grid procedure like in the head impact
protocols. The HBM should be moved in 100 mm steps (y-axis) along the front of the vehicle
for the lower speed range and with a wider grid (factor X) for the higher speed range.
The second option was defined considering the most frequent impact points and define two
head impact zones from 0%-20% (all sizes) and 20%-40% (only for 6yo, 50%) plus the
middle position and both side points reflected to the other side as well. A maximum of 5
impact zones at the vehicle front are needed. This fits the needs for standard vehicles.
Combining these results with a vehicle design that comes up with outstanding wheels and one
seat/row the most frequent impact point would be in the area of the wheel/suspension. This
induces 2 new impact points that should be considered: One at the tire, where it has to be
defined if an ABS locking motion or the original rotational velocity is used and one at the
suspension arms where leg contact for the pedestrian is possible. But both are only for the
lower speed range, as there is no reasonable optimization possibility seen for higher
velocities. For the “small vehicle front” (e.g. VW Nils, Renault Twizy) only 3 impact points
are remaining (Side/Middle/Side). In the future work the passenger compartment width has to
be defined until which width of the vehicle the Side/Middle/Side options is valid (switching to
5 points). Figure 35 shows the selected proposal for pedestrian testing.
36
Figure 35. Final proposal for pedestrian impact locations and the simulation effort.
Cyclist proposals:
The second part for future vulnerable road user protection will cover cyclists. For a more
realistic injury prediction due to the mentioned real life injuries the focus is set to full HBM
assessment. Additionally to the HBM a bike is needed which will, due to a lack of
information, not be further discussed within this proposal, but it should be kept in mind that
the bike can influence the human body kinematic behaviour as well as injury outcomes
(height, weight, design of the bike).
The cyclist velocity is defined with 10km/h. The vehicle speed selection was discussed and
set to the lower range only, which is between 25 km/h and 30 km/h. With the reviewed studies
it can be derived that a side struck is the most relevant case combining the injury risk and
frequency. There are three sizes of HBM´s selected. The 6 year old child impact proposal was
eliminated. From legislation side in the European Union there are big differences in age when
it is allowed to ride a bike. In Switzerland it is coupled with the legal age for going to school.
Denmark allows children of 6 years to go by bike whereas in Germany it is 8 years and 10
years in Poland [33]. In Austria it is allowed at an age of ten years, but with the need of a
special license. For an EU wide safety proposal it would need a harmonization for the
minimum age to go by bike.
The next issue in the cyclist proposal is the definition of the initial position. As shown in
Figure 36 two positions for the cyclist are derived. The saddle position was chosen to be the
relevant factor for the definition of the impact point on the vehicle front-end. One impact
point should be within the first one-third and the second within an area after the first onethird to the vehicle midplane. As these new SEV´s are smaller (y-axis) then conventional
vehicles it was considered as reasonable to shorten the two- thirds (from literature) to one
vehicle half only. An overall description can be seen in Figure 37. For a more detailed
specification the need of numerical simulations with the defined procedure for cyclist testing
would give a better understanding of impact positions, which was not possible in this phase of
the project.
37
Figure 36. Final cyclist impact location on the vehicle front end.
Figure 37. Final cyclist testing proposal and the simulation effort.
3.4 Discussion and conclusions
Main result of this section is the proposal of a full virtual pedestrian and cyclist test method
based on Deliverable 1.1 of the SafeEV project. Different sizes of human body FE models are
impacted virtually with the car FE model at different locations and with two separate
travelling speeds, a lower speed (25 to 30 km/h) and a higher speed (45 to 50 km/h). The
assessment of injury risk will consider model based injury criteria with AIS2 level for the low
speed and AIS 3 for the higher speed.
This report proposed future pedestrian impacts on vehicle front-ends. Due to the future view
certain issues are of course only estimations, but they came from experts supported by a
public survey. All simulations are partly based on some of these estimations (e.g. vehicle
design, AEB market penetration). The virtual full assessment process is actually not included
in a regulation for type approval. In IMVITER the full virtual testing approach was estimated
to start in 2025. Before this year a combination of real and virtual testing was proposed.
However, one big issue will be the validation criteria and numerical stability of HBM´s for
different impact conditions. Almost every OEM works with HBM models, but not with the
same as shown in the technical bulletin of EuroNCAP [34].
The pedestrian proposal 2 seems to be the better option, regarding the D1.1 results and
literature review. For the outstanding wheels an open point are the sizes used for wheel and
38
suspension impact. Reducing it to the child and 50% male could be enough. More important
in this case would be to extend the time to gain results on the second impact. This post impact
should be discussed also for all other tests.
The positioning was defined preliminary with head impact zones. The coming numerical
analysis for pedestrian should identify some exact boundary conditions for the HBM
placement in front of the vehicle. If there will be no overall value found, the head impact
zones can be seen as the most appropriate way for the HBM positioning. This can be the case
for future individual vehicle designs.
For cyclist accidents only a limited amount of research work was found or seen as helpful for
a scenario definition, but as the reviewed literature tends to similar results the overall test
proposal will be a valid start for further improvement. There are big differences between EU
countries of the most frequent accident type, but injuries are seen more sever if the cyclist is
struck by the side. Regarding the test proposal the vehicle and bicycle speed definition can
cause results where no contact between the head and the front-end occurs which may
influence future test proposal-updates for the second mid-vehicle impact, depending on
overall widths of the test-vehicle.
39
4 Occupant protection in small EV’s
4.1 Frontal impacts
4.1.1 Relevant Current Regulation(s) Test Methods etc.
Within this chapter the current, relevant assessment and test methods concerning frontal
impacts and related occupant protection evaluation will be reviewed. Focus will be on latest
changes and proposals for test protocols and tools / ATDs. Relevant EU research initiatives
will be also mentioned respectively are already discussed as reference for regulation and
protocol updates. Structural interaction issues which are, for instance, related with crash
barrier type or offset-/full-width configuration are discussed within the compatibility section
of this report – so the following review will place emphasis on the occupant related aspects of
such an assessment.
Regulations - ECE R 94 > GTR Process
ECE R 94 [35] covers the “uniform provisions concerning the approval of vehicles with
regard to the protection of the occupants in the event of a frontal collision” and represents the
only frontal collision related regulation in Europe currently. It’s also under discussion for an
extensive update within the GTR harmonisation process [36].
Figure 38.
Current configuration of ECE R 94
Test speed 56 km/h, 40 % overlap, 2 H III
Dummies. Source:[43]
For the evaluation of occupant loadings currently two Hybrid III 50% are prescribed within
the test protocol. As performance criteria the following measured values are described:
Head >
Neck >
Thorax >
Femur >
Tibia >
HPC - Head Performance Criteria & Resultant head acceleration
NIC – Neck Injury Criteria (Duration / Force)
Neck Bending Moment
ThCC - Thorax compression
VC - Viscous Criterion (1 m/s)
FFC - Femur Force (Force / Duration)
TI – Tibia Index (Bending / Compression)
As mentioned, the current regulation is under discussion. The following figures indicate the
main suggestions and references for an update with focus on occupant performance criteria
[36].
In general main focus is given to the improved protection of
Female - Introduction of 5% female dummy to the protocol
Elderly Occupants – Improved/modified thorax injury criteria
40
Figure 39. Revision of ECE R94 - Current status of discussion within informal working
group – Relevant parts for occupant performance criteria are highlighted [36].
Figure 40. (cont.) Revision of ECE R94 - Current status of discussion within informal
working group - Relevant parts for occupant performance criteria / ATD are highlighted
[36].
41
Similar Frontal impact test configurations are described in regulations of other countries. Due
to the fact, that currently worldwide harmonisation is ongoing, the above described ECE R94
might exemplify the main trend of occupant performance criteria within regulations and rules.
As parallel or interacting assessment path consumer information programs play a major role
in the definition of the current status and further improvement of traffic and vehicle safety.
Finally the same references in terms of research programs and outcome of working groups
and stakeholder organisations are taken into account for the formulation of regulations or test
protocols within consumer assessment programs (NCAP).
Nevertheless, NCAPs offer usually an even faster update and upgrade process for the
implementation of new tools, criteria or test procedures.
So, the following part will focus on the latest modifications and trends within the worldwide
NCAPs.
Consumer assessment programs - NCAP
For Frontal testing scenarios within the worldwide NCAPs two main test clusters / scenarios
can be distinguished:
> Full Width - 0° rigid barrier (different velocities & occupant / dummy line-up)
Figure 41.
Example of Full Width test, EuroNCAP as of
2015[43]
The next figure gives an overview of current and future worldwide test configurations in this
cluster [37].
Especially the set-up with 5th female dummy / ATD is now updated or will be updated in
most of the protocols. This respectively the intention to improve safety for these kind of car
occupants is comparable to the above indicated topic within the review process of related test
scenarios in regulations.
Occupant performance criteria are focusing on the protection of head & neck and on chest
deflection. All other criteria are the standard H III measured and calculated values for the
related body region:
Head >
HIC - Head Injury Criteria & Resultant head acceleration
Neck >
Euro/Asian NCAP: Bending / Tension / Shearing (Duration / Force)
US NCAP: Nij (Tension /Compression)
Chest/Thorax > Chest deflection
VC - Viscous Criterion (1 m/s)
Femur >
Compression Force (Force / Duration)
Knee >
Displacement
42
Tibia >
TI – Tibia Index (Compression force)
Foot >
X-displacement of braking pedal
For the 5th HIII female the following criteria are defined or currently under discussion
(similar values to 50th HIII male > adapted from female injury risk).
> 2015
Figure 42. Overview of Full Width test configurations – NCAP worldwide [37].
Figure 43. Overview of Full Width test configurations – performance criteria 5th female [37].
43
The second frontal test configuration, which is applied within all/most of the above listed
NCAPs is the:
> Offset Deformable Barrier (Frontal ODB) (different velocities & occupant line-up)
Figure 44.
Example of ODB test- EuroNCAP current protocol
[43]
All occupant performance criteria respectively injury criteria for the standard equipment 50th
HIII dummy are as per current assessment.
For the evaluation of occupant protection on the rear seat in some of the protocols child
safety and child restraint systems (CRS) are assessed.
Beside aspects of usability / misuse, instructions and labelling also injury criteria respectively
so-called kinematic and dynamic assessment is addressed in the protocols. Recently within the
EuroNCAP protocol the P-Dummy Series has now been replaced by the Q-Dummy series
with enhanced biofidelity and instrumentation. Next update is already discussed and planned
as of 2015 with replacing the current Q11/2 & Q3 (11/2 year old & 3 year old child) by Q6 &
Q10 (6 year old & 10 year old child).
Due to the fact, that most of other NCAPs worldwide still proceed with the P-Dummy series,
the following list will focus und the Q-series performance criteria as it is defined for Q11/2
& Q3 and under discussion for Q6 & Q10 [38]:
Head >
Neck >
Chest >
Pelvis >
Peak resultant acceleration // HIC (Q6/Q10)
Neck Tension (Fz) // Neck loads (Q6/Q10)
Chest deflection
Peak resultant acceleration
Acceleration & (Q6/Q10) Lumbar loads
Figure 45. Q-Dummy series [38].
44
Also forward excursion, head contact and ejection risk are evaluated within the test.
IIHS (Insurance Institute for Highway Safety) recently introduced another offset test scenario
in their test catalogue for the US market [37][38]:
> Small Overlap (exclusive load case in IIHS test program)
Figure 46.
Small Overlap test configuration –
The test vehicle is aligned with a
rigid barrier so that the right edge
is offset to left of the vehicle
centerline by 25 percent of the
vehicles width. [38]
This load case is seen to be challenging for the vehicle structure. For this the intrusion on 10
locations of the occupant compartment is evaluated and ranked.
Figure 47. IIHS Small Overlap - Assessment of structural behaviour [37].
45
The occupant performance criteria are assessed by using a standard 50th HIII Dummy.
> Head / Neck
> Chest
> Thigh / Hip
> Leg / Foot
HIC15, Nij (Tension & Compression)
Spine acceleration, deflection / deflection rate, VC
Knee-Thigh-Hip injury risk
Tibia-Femur displacement, TI, Tibia axial force, Foot acceleration.
In addition and in contrast to other NCAP test the head & neck kinematics respectively
(multiple) contacts in the course of the crash event are assessed and ranked for a final rating.
Figure 48. IIHS Small Overlap – Flowchart calculating head & neck injury rating [38].
Along with this, also the restraint performance and dummy kinematics are evaluated. The
rating is finally calculated from demerits which the tested vehicle will get from ranking within
the following categories.
 Interaction with frontal airbag system
 Side head protection airbag with forward coverage
 Excessive head lateral movement
> Front and lateral chest protection
 Vertical and lateral steering wheel movement
> Occupant containment and miscellaneous  Excessive occupant forward excursion
 occupant burn risk
> Overall restraint and dummy kinemtics
> Frontal head protection
> Lateral head protection
Some example for the evaluation of frontal airbag interaction is given in the following figures.
Basically the ranking is carried out by analysing the recorded on board video.
46
Figure 49.
Example
for
dummy-airbag
interaction assessment within
IIHS Small Overlap testing –
ranking was “partial” in this test.
[38]
The “occupant excursion” is also evaluated using an additional measuring system. Two cable
potentiometers are mounted to rigid points behind the driver seat. The cable ends are attached
to the rear of the driver seat back near the top, with one near the centreline of the seat and the
other near the inboard edge. The dummy’s movement away from the seat is measured using
two pull strings or fiberglass measuring tapes.
Figure 50.
Additional measuring system for
dummy excursion (IIHS Small
Overlap testing). [38]
4.1.2 Most Important Trends from WP1, Regulations, EuroNCAP etc..
In most of the regulations or NCAPs considered, focus is given to an improved protection of
(small) female occupants and children. This goes along with a discussion concerning
improved or adapted performance respectively injury criteria, which are, one the one hand,
taken over from the current standard 50th H III (assessed body regions), or, on the other
hand, are discussed for specific use with these occupants or new dummies (children).
Another or parallel trend can be identified with the intention to enhance the evaluation of
thorax and head & neck injuries. This is also related with the aforementioned focus on
female occupant ( rear seat occupant) but covers also the aspect of improved protection of
elderly people (thorax injuries).
Different working groups and research projects already presented additional criteria,
measurement locations or devices to be used with the, so far standard HIII dummy or with the
currently discussed new frontal test device, the THOR dummy:
“THMPR” – thorax multi point measurement
“RibEye” – dynamic thorax measurement & assessment
“DEQ” – deflection equivalent
“NFR” – number of fractured ribs
should be mentioned here exemplarily and will be further discussed within chapter 5.
A new configuration is now presented with Small Overlap which adds kinematic evaluation to
occupant performance.
47
From analysis within WP1 a general reduction of closing and collision speed in urban areas
can be expected due to different reasons. Especially accidents and conflict situations in
longitudinal / parallel traffic will decrease due to the effect of Active Safety and/or AEB
systems.
So far the market share of such systems was in principle uncertain and a quite sensitive
parameter in all prospective analysis. Due to the fact that EuroNCAP recently decided to
implement an Active Safety System assessment to their protocols (see chapter 2), an increase
in its market penetration is certain to continue.
In detail the following results and trends from the different analysis in WP1 has been taken
into account for the proposal of a frontal test condition for SEVs to be further used and
refined in the course of the project:
From the Delhi study a general trend with relevance for car-to-car conflict situations can be
extracted (Deliverable D1.1., Chapter 7):






Approximately 14 % of all passenger cars will be electric propelled and defined as
small city cars.
Average car mass of 1,100 kg.
These vehicles will have one to approximately three seats.
They will be equipped with assistance systems and partly with semi-autonomous
systems.
The main field of application can be seen in urban areas, where speed limits of
50 km/h and less can be expected.
In critical situations this speed limits will further drop in comparison to that from
nowadays.
A more specific trend concerning frontal accident scenarios based on the pos sible impact of
Active Safety is then addressed by “Prognosis for 2025” in deliverable D1.2 [53]:
48
Extract of D1.2 findings of
the “Prognosis for 2025Combining Swedish accident
data and trends in active
safety
systems”
with
relevance for frontal accident
scenarios:
The prognosis shows a
substantial reduction of
front-to-front and front-torear accidents along with
reduction of fatalities in such
crash incidents.
(DeliverableD1.2, Chap.2)
The analysis of the accident occurrence of small urban vehicles (represented by a generic
vehicle “Visio.M” & GIDAS database analysis) confirms this trend respectively a declining
importance of accidents in longitudinal traffic for SEVs:
Extract of D1.2 findings of
the “Analysis of Accident
Occurrence
with
Small
Urban Vehicles”
with
relevance for frontal accident
scenarios:
Visio.M / SEVs are more
represented in intersection
accidents (35% compared to
25%) and less represented in
parallel traffic accidents
(21% compared to 33%).
49
The shift of the impact
distribution in terms of the
direction of the impact
momentum acting on the
vehicle (PDOF – principle
direction of force) from front
to more diagonally from the
front goes along with this.
Finally a prognosis of
(urban) collision
speeds
respectively the relevant EES
was given:
Visio.M / SEV vehicles had
on average a somewhat
lower collision speed than
larger M1 vehicles. The
collision
severity
was
however unchanged due to
the lower vehicle mass of
Visio.M vehicles / SEV.
Future Small Urban Vehicles
are however expected to
have significantly lower
mass than the potentially
Visio.M vehicles ( red
bars) included in the present
GIDAS sample (average
1150 kg). These even lighter
vehicles will likely be
exposed to higher average
speed changes. ( green
bars)
(DeliverableD1.2, Chap. 3)
4.1.3 Future Test Conditions
Based on the aforementioned analysis and discussion of trends a test configuration which
mainly represents the shift of PDOF towards a more oblique impact momentum can be
derived.
The effect of lower vehicle mass of SEVs might be addressed by a test configuration, which
considers also the EES (Energy Equivalent Speed - The equivalent speed at which a particular
vehicle would need to contact any fixed rigid object in order to dissipate the deformation
energy corresponding to the observed vehicle residual crush) and so the collision severity in
the field respectively when confronted with an M1 vehicle. This can be done in a (rigid)
barrier test configuration adapting the collision speed to the EES level.
50
Optional the same collision severity can be simulated with a movable barrier type, which
represents the average opponent vehicle mass (1125 kg in GIDAS analysis). Such a
configuration also adapts automatically the effect of variations in SEV mass.
Finally it was discussed and agreed to combine compatibility issues (Mobile (Progressive)
Deformable Barrier) as well with this suggestion for a frontal oriented test configuration
which will be further investigated in the course of the SafeEV project now:
 Oblique impact configuration ~ 30°
 30-40 km/h (which should represent 90% of the collision speeds)
4.1.4 Discussion and Conclusions
For the purposes of the project and its focus on the evaluation of virtual assessment methods it
could be stated, that for the test configuration suggested above a full virtual test method has
high potential due to the fact that full vehicle and structural crash simulations are widely used
within the development phase of cars. If now consumer assessment or regulation is discussed,
related Verification and Validation issues concerning the (Small Electric) vehicle model are in
general addressed by the IMVITER project [39] and should be taken into account in the
subsequent tasks of SafeEV. Also for crash barriers or dummies already validated numerical
models existing in principle.
For the occupant protection evaluation it can be suggested to follow the main trend already
under consideration for updates of the aforementioned (see 4.1.1) regulations and consumer
assessment programs:


Enhanced thorax and head criteria (female / elderly)
Option for oblique occupant kinematic evaluation / head contact
Also for this, full virtual test methods have high potential, which are now mainly represented
be the application of advanced human body models in course of the project (see also chapter
5).
Finally the use of virtual methods and the application of active human body models (see also
2.3) will allow implementing an assessment of integrated safety systems respectively the
evaluation of pre-crash occupant kinematic and (pre-crash) restraint interaction. This should
be relevant especially for the frontal test cluster due to the fact, that with AEB already active
safety systems are becoming higher market shares now.
4.2 Side Impacts
Today side impacts have a share of around 20% (Figure 51) of all impacts of the roads to
25% taking into account only urban environment [40]. Side impacts are responsible for 50%
of serious and fatal injuries [40]. There is huge afford undertaken to improve occupant safety
in crashes by design appropriate test and choose corresponding injury criteria.
51
In the next decade the number of lateral collisions in urban environment is expected to
increase relatively and reach up to 35% of all crashes [41]. Therefore it is even more
important to properly choose test scenario conditions reflecting this kind of crashes.
Additionally the number of small light electric vehicles (SEVs) used in urban areas will
increase. These SEVs shows huge differences to traditional cars. The external and structural
design differences affect consequences of impacts. One of the possible structural changes is
the lack of a B-pillar. Those conditions are not adequately addressed by current vehicle safety
testing standards.
Figure 51. CCIS – Passenger car accidents by impact type [42].
In this chapter we propose side impact tests scenarios for future small electric vehicles.
4.2.1 Relevant Current Regulation(s) Test Methods etc.. [43]
The most widely used vehicle safety systems worldwide are those modelled after the New Car
Assessment Program (NCAP). The program was initially introduced by the National Highway
Traffic Safety Administration in U.S. in 1979. This procedure was adopted into several
regional programs including Australia and New Zealand (ANCAP), Latin America (Latin
NCAP), China (C-NCAP), Japan (JNCAP), Korea (KNCAP), Southeast Asia (ASEAN
NCAP) and Europe (Euro NCAP). While NCAP programs are most widely spread among
testing and rating organization, another procedure exists including Insurance Institute for
Highway Safety (IIHS), Federal Motor Vehicle Safety Standard (FMVSS), regulations R94
and R95 from United Nations – Economic Commission for Europe (UN-ECE). The following
sections are focused on details implemented in each method.
EuroNCAP – Side Impact
 EuroNCAP conducts side impact test utilizing the EuroSid-2 dummy on the driver
seat. Passengers on the rear seats are represented by two child dummies, a Q1.5
dummy on the seat behind the driver and a Q3 dummy on the opposite side
52
 Stationary vehicle is hit by Moving Deformable Barrier (MDB)– EEVC (European
Enhanced Vehicle-Safety Committee) MDB 950 kg with a speed of 50 km/h at 90º
angle.
 The impact point is chosen based on the dummy driver position. The centre of hip of
95th percentile male dummy indicates impact location.
A schematic test impact scenario is presented in Table 3.
EuroNCAP – Pole Side Impact
 For the pole side impact test EuroNCAP utilizes only the EuroSid-2 dummy as a
driver.
 The vehicle hits 254 mm rigid pole at speed of 29 km/h at 90º angle.
 The impact point is chosen based on the dummy driver position. Impact location is
defined by centre of gravity of driver dummy head.
U.S.NCAP – Side Impact
 U.S.NCAP conducts side impact test utilizing the EuroSid-2re dummy as a driver. The
passenger behind the driver is represented by SID-IIs dummy.
 Stationary vehicle is hit by Moving Deformable Barrier – 1365 kg with a speed of
55 km/h at 90º angle.
 The impact point is chosen based on the dummy driver position. The centre of hip of
the 95th percentile male driver dummy indicates impact location.
U.S.NCAP – Pole Side Impact
 U.S.NCAP utilizes SID-IIs dummy as a driver.
 The vehicle hits 254 mm rigid pole at speed of 32 km/h at 75º angle.
 Impact point is chosen based on the dummy driver position. Impact location is defined
by gravity of driver dummy head.
IIHS – Side Impact
 IIHS conducts side impact test utilizes SID-IIs dummy as a driver. Passenger behind
the driver is represented by SID-IIs dummy.
 Stationary vehicle is hit by Moving Deformable Barrier – 1500 kg with a speed of
50 km/h at 90º angle.
 The centre of hip of the 95th percentile male driver dummy indicates impact location.
UN-ECE [45] – Side Impact
 UN conducts side impact test utilizes EuroSid-2 dummy as a driver. Passenger on the
rear seat is represented by SID-IIs dummy.
 Stationary vehicle is hit by Moving Deformable Barrier – EEVC MDB 950 kg with at
speed of 50 km/h at 90º angle.
Impact point is chosen based on the dummy driver position. The centre of hip of the 95th
percentile male driver dummy indicates impact location
53
Table 3. EuroNCAP, U.S. NCAP, IIHS side impact comparison.
FVMSS – Dynamic [46] Side Impact
 FVMSS conducts side impact test utilizes SID-IIs dummy as a driver. Passenger on
the rear seat is represented by SID-IIs dummies.
 Stationary vehicle is hit by Moving Deformable Barrier –1361 kg with at speed of
52,9 km/h at 90º angle.
 Impact point is chosen based on the dummy driver position. The centre of hip of the
95th percentile male driver dummy indicates impact location.
A detailed test set up is presented in Figure 52.
Figure 52. FVMSS dynamic test setup [46].
54
FVMSS – Static [46] Side Impact
 Rigid cylinder 12” (~305 mm) is pushed into stationary vehicle. The resistance force
at 6”, 12” and 18” is measured.
 The initial (6”) crush resistance shall not be less than 2,250 pounds, with or without
seats installed.
 The intermediate (12”) crush resistance shall not be less than 3,500 pounds or 4,375
pounds with seats installed.
 The peak (18”) crush resistance shall not be less than two times the curb weight of the
vehicle or 7,000 pounds, whichever is less. With seats installed, it shall not be less
than 3.5 times the curb weight or 12,000 pounds, whichever is less.
FVMSS – Pole Side Impact
 Pole Side Impact
 For the pole side impact test FVMSS utilizes ES-2re dummy as a driver.
 Tested vehicle hits 254 mm rigid pole at speed of 20 mph (≈32,2 km/h) at 90º angle.
as transverse plane through centre of gravity of dummy head.
JNCAP – Side Impact
 JNCAP conducts side impact test utilizes EuroSid-2 dummy as a driver.
 Impact point is chosen based on the dummy driver position. Centre of hip of 95th
percentile male dummy indicates impact location.
Schematic test impact scenario is presented in Table 4.
C-NCAP – Side Impact
 C-NCAP conducts side impact test utilizes EuroSid-2 dummy as a driver. Passenger
on the rear seat is represented by SID-IIs dummies.
KNCAP – Side Impact
 KNCAP conducts side impact test utilizes EuroSid-2 dummy as a driver.
KNCAP – Pole Side Impact
 KNCAP utilizes only EuroSid-2 dummy as a driver.
 Tested vehicle hits 254 mm rigid pole at speed of 29 km/h at 90º angle.
ANCAP – Side Impact
 ANCAP conducts side impact test utilizes EuroSid-2 dummy as a driver.
55
ANCAP – Pole Side Impact
 ANCAP utilizes only EuroSid-2 dummy as a driver.
 Tested vehicle hits 254 mm rigid pole at speed of 29 km/h at 90º angle.
Table 4. JNCAP, C-NCAP, KNCAP, ANCAP side impact comparison.
SafeEV work package 1 is focused on future key accident scenarios involving Small Electric
Vehicles (SEVs) in Urban Environment. The results of the scenario analysis are presented in
Deliverable D1.2.
Researchers expect a major reduction in accidents due to improved intersection infrastructure
and increased presence of active systems in vehicles. Most of loss-of-control situation will be
eliminated. In addition, it is expected that impact speed will be decreased by more than 50%.
Accidents related to under-run against heavy truck fleet will be entirely reduced due to
implementation of existing regulations [40].
Starting from 2015 EuroNCAP will update its testing protocol to reflect current side impact
accident scenarios. In all side impact tests the new WorldSid anthropomorphic test device
(dummy) will be used. Also new child dummies Q6 and Q10+ will be utilized. EuroNCAP
will replace the moving deformable barrier by a recently developed Advanced European
Moving Deformable Barrier (AE-MDB) with increased mass to reflect current vehicle fleet.
The update also includes a change of the impact point, 250mm behind 95th percentile adult
male hip point towards the rear end of the vehicle.
56
In the EuroNCAP testing protocols concerning side impact the current pole test will be
updated to. The organization increases the speed to 32 km/h and change the angle of impact to
75º measured from the axis of symmetry of the tested vehicle.
Also KNCAP will update its testing protocol starting 2015. As its European counterpart
KNCAP will use the WorldSid dummy to test vehicle safety regarding side impacts. The
moving barrier will be replaced by AE-MDB. Also the pole test will have an identical
configuration like in the European procedure.
Therefore, except ANCAP, all testing organization will utilize a unified set up for a pole test
[43].
There is another attempt to unify pole side impact tests within all certifying organization [43].
The proposal for the current vehicle fleet also suggests to modify the conditions to an impact
of the pole with 32 km/h at 75º angle. We suggest to reduce the impact speed to 26 km/h for
vehicles with a width of 1,5 m or less.
SafeEV is not the only a research project that tries to predict future accident scenarios for
light urban vehicles. The topic was also elaborated in [44]. In this report the authors
recommend four new crash scenarios, two of which refer to side impacts. The first one is
similar to current side impact protocol with reduced speed of 40 km/h. In addition the reports
suggest that the protocol should assess whether a vehicle has a tendency to rollover and
evaluate occupants’ safety in this scenario. The second scenario reflects impacts against
narrow vehicles (e.g. motorcycles) with focus on vulnerable road user protection.
Impact speed
Current regulations use 50 to 55 km/h as impact speed for lateral collisions. Driving Assistant
Systems (DAS) like Autonomous Emergency Braking (AEB), which should be included in
50% of vehicles, are expected to reduce impact speeds [40]. Most urban speed limits are
50 km/h, so one can expect that impact speed will be slightly lower, e.g. 40 km/h, because of
impact detection and emergency braking.
Some cities (e.g. Barcelona, Graz, Munich, Stuttgart) introduced low speed zones with a
speed limit of 30 km/h, which reduce impact speeds even further. These zones were
introduced mostly to increase pedestrian safety and are shown to reduce the number of
fatalities in some areas by up to 40% [47]. The study shows that the overall number of
accidents and severity was also decreased [48].
Due to insufficient data about the impact conditions in low speed zones from other sources,
authors propose the conservative approach on speed reduction. Finally, we decided to choose
40 km/h as an impact speed for the test procedure.
Side Impact
The test will be conducted using the latest MDB with a mass of 1100kg reflecting typical
future car masses. The barrier will hit the vehicle with a speed of 40 km/h at an angle of 90º.
The impact location should be moved backwards reflecting no or short bonnet in a car body.
An appropriate impact point will allow assessing the structural rigidity for the battery
compartments, which are usually in the underbody substructure (Figure 53) or in the trunk.
57
Figure 53. Smart ED electric drive train.
The authors propose the new impact point defined as 500 mm behind “R-point” towards the
rear end of vehicle. The R-point is defined as the centre of hip of the 95th percentile male.
Nevertheless a 50th percentile male HBM will be used as driver and a 5th percentile female
HBM will represent the passenger. The test setup is displayed in Figure 54.
Figure 54. Side Impact.
Pole Side Impact
SafeEV’s deliverable D1.2 shows low relevance of lateral pole impacts for SEVs in urban
conditions. In addition to the deliverable D1.2 finding, remaining risk of impact to the pole
might be well addressed with ESC (ESP).
58
Therefore pole side impacts will not be assessed in the testing protocol for SEVs for use case
in urban areas.
We propose one crash test scenario to assess occupant safety in side impacts. This scenario
should reflect the most common future impact related to SEVs in the urban environment.
The virtual certification tool chain (test scenarios and conditions, methodology and injury
criteria) is developed for L7e category vehicle in urban environment use case. Different
vehicles classes (e.g. M1) can also benefit from those results if similar use case (urban
environment) is considered.
4.3 Compatibility
Vehicle safety evaluation in front crash situations also has to deal with questions of
compatibility. Front crash compatibility, consisting of several issues of self and partner
protection in vehicle to vehicle front crash situations, can be analysed regarding several
independent characteristics (Figure 55).
The analysed self-protection characteristics of vehicles are the same as in single vehicle crash
safety assessment, focusing on questions of compartment strength, vehicle deceleration and
the behaviour of occupant protecting restraint systems. In addition to these, partner protection
focuses on questions of structural interaction, also called form compatibility, and the
adaptation of front end deformation forces to the crash partner’s requirements, also called
force compatibility.
A good structural interaction between two crash partners in a front to front crash situation is
given, when the front end structures of both vehicles are loaded adequately for crash energy
absorption before intrusions into the passenger compartment occur for any given crash
overlap or impact angle. To fulfil this requirement, vehicle front end structures have to assure
good vertical and horizontal load spreading characteristics, avoiding an over- or underriding
of the crash partner or the occurrence of fork effect in horizontal offset impact situations
(Figure 56).
The adaptation of front end deformation force characteristics to the requirements of the crash
partner is necessary to avoid an overcrushing of the front crash opponent. Deformation force
levels in the front end should be generally designed in a way that the complete front end
deformation length is used up for energy absorption before any deformation of the passenger
compartments occurs. A general aim of force compatibility is to assure that each vehicle has
the ability to absorb its own kinetic energy by front end deformation whatever front crash
constellation, impact speeds and crash partner masses are involved. For further general details
on crash compatibility aspects [49].
Compatibility issues are of major interest, when the mass ratio of two vehicles involved in a
front to front crash is unequal to 1.0. Already accomplished studies on front crash
compatibility focus on the mass range of M class vehicles, therefore dealing with vehicles
with a minimum mass of about 1,000 kg ([51][52]). Previous works recommend compatibility
investigation over a mass ratio of 1:1.6 based on accident database analysis, quantifying the
likelihood of crashes within this mass ratio range as most important for small M class vehicles
[52]. As the vehicle fleet will change with the future appearance of small electric vehicles
(SEVs) having a total mass far below 1,000 kg, the investigation focus of previous studies has
to be reviewed.
59
Figure 55. Compatibility characteristics ([50])
Figure 56. Horizontal (left) and vertical (right) disalignment of front structures [49]
To analyse compatibility issues in front to front crash situations between SEVs and
conventional M class crash partners different performance priorities arise for the two crash
partners: All crash test configurations and performance assessment criteria for the
investigation of crash compatibility between SEVs and conventional M class crash partners
should focus on the promotion of following different compatibility development priorities
(Table 5).
Chapter 4.3.1 presents current regulation test methods on compatibility, while chapter 4.3.2
deals with trends concerning test methods resulting from recent research projects on
compatibility. These different test methods are assessed according to the different
compatibility priorities listed in Table 5 resulting in recommendations for future test
conditions to be analysed during the further duration of the SafeEV project.
60
Table 5. Compatibility priorities for SEVs and their (conventional) crash partners.
Self-protection
Small electric vehicle (SEV)
(Conventional) crash partner
High compartment strength
Conservation of high level of selfprotection (resulting from performance
under current crash regulation and
consumer protection test conditions)
Structural deceleration pulse for restraint
system performance assessment under
realistic conditions
Partner protection
Good structural interaction (also for
futuristic vehicle designs)
Good structural interaction
Front end deformation force adaptation
to SEV requirements
A comparable review and evaluation approach for different compatibility assessment criteria
is the content of chapter 5.2.
Side impact compatibility is a separate issue discussed in chapter 4.2. This research task has a
main focus on self-protection requirements for the impacted vehicle.
Another separate research subject deals with the compatibility requirements for heavy trucks.
This field of research mainly focuses on structural protection measures preventing a front,
side or rear underrun of heavy trucks by passenger cars. For further details on this subject see
[53].
4.3.1 Relevant Current Regulation(s) Test Methods etc..
Crash test configurations for front crash assessment according to current regulation and
consumer protection test protocols only focus on issues of self-protection. For a broad
description of currently tested full width and offset front crash configurations see
chapter 4.1.1.
No current test protocol is designed to explicitly assess aspects of partner protection such as
force and form compatibility of vehicle front end structures.
The EU research project FIMCAR (frontal impact and compatibility assessment research)
discusses a variety of different possible front crash test configurations that should all cover
more compatibility assessment aspects, than those resulting from test protocols currently in
use [51].
The different test configurations investigated in FIMCAR are listed in Table 6.
FIMCAR proposes a combination of two test set-ups consisting of one full-width and one
offset crash test to analyse a wide range of compatibility aspects. A combination of FWDB
test for full-width impacting and ODB test against the EEVC barrier for offset-impacting is
proposed, as issues with the progressive deformable barrier remain requiring further
investigations. The FIMCAR project consortium nevertheless confirms the high potential of
the progressive deformable barrier for compatibility assessment in comparison to the ODB
test, which does not produce any assessment information on partner protection issues.
Therefore further investigations on the PDB and MPDB test are recommended also with
regard to the special compatibility requirements in front crash situations involving small
electric vehicles [51].
61
Table 6. Overview of compatibility test configurations discussed within FIMCAR.
Test name
Description
Crash
overlap
Impact
speed
[km/h]
FWRB test
Full width rigid barrier test - vehicle
impacting rigid and flat barrier.
100 %
56.0
Load cell wall measuring
barrier contact force.
[54]
100 %
50.0
Load cell wall behind
deformable layers measuring barrier contact
force.
[55]
FWDB test Full width deformable barrier test vehicle impacting flat two-layer
deformable barrier.
Specific compatibility
evaluation possibility
Source
ODB test
Offset deformable barrier test – vehicle
impacting EEVC barrier under ECE R
94 crash conditions.
40 %
56.0
No specific compatibility
evaluation method.
[56][57]
PDB test
Progressive deformable barrier test vehicle impacting new type of
progressive deformable barrier (PDB).
50 %
60.0
Post-crash analysis of
barrier face deformation.
[50]
MPDB test
Mobile progressive deformable barrier
– vehicle impacting moving trolley
weighting 1,500 kg equipped with
PDB face.
50 %
50.0 vehicle,
50.0 trolley
Post-crash analysis of
barrier face deformation
and resulting deceleration
of barrier trolley.
[58]
Based on results from the FIMCAR project the UN ECE GRSP informal working group on
frontal impacts follows a time schedule for the improvement, revision and new development
of the ECE regulation 94 (chapter 4.1.1). In a first phase till 2014 the introduction of a fullwidth test to ameliorate compatibility assessment will be accomplished. The decision whether
the FWDB test set-up proposed by FIMCAR or the alternative FWRB test set-up will be
accepted is still pending. Also precisions on further test specifications like the impact speed
are still not available. Current discussions treat a possible reduction of the crash impact speed
in case of FWRB test from 56.0 km/h to 50.0 km/h to reduce the test severity [55]. In a
second phase till 2018 a review of the offset front crash test procedure is planned, discussing
the possibility of replacing the current test procedure relying on the EEVC barrier by a new
test using the progressive deformable or the mobile progressive deformable barrier.[59]
The Euro NCAP rating from 2015 on will include an additional full width frontal impact
against rigid barrier with optional use of load cell wall for barrier contact force measuring
[60] (Figure 57).
Figure 57. FWRB test according to Euro NCAP rating from 2015 [60].
62
German automobile club ADAC (Allgemeiner Deutscher Automobil-Club) leads own studies
on front crash compatibility resulting in the ADAC compatibility test protocol. The set-up of
the test is comparable to the MPDB test configuration also investigated in FIMCAR but is
prescribing a barrier trolley with a total weight of only 1,400 kg. Overlap and impact speeds
as well as the used progressive deformable barrier face at the trolley’s front are the same as in
the FIMCAR MPDB test configuration. [61]
US organisation NHTSA (National Highway Traffic Safety Administration) also discusses an
approach to test front crash situations using a mobile barrier trolley. This research issue,
applying the RMDB (research mobile deformable barrier), is meant to reproduce oblique and
small overlap crashes between vehicles. Two test set-ups are currently favoured by NHTSA
(Figure 58 and Table 7) [61].
Figure 58. Test configurations proposed by NHTSA [62].
Table 7. NHTSA crash test configuration parameters [63].
Crash configuration
Small overlap impact (SOI)
Oblique
Vehicle impact velocity [km/h]
0.0
0.0
RMDB impact velocity [km/h]
90.0
90.0
RMDB weight [kg]
2,490
2,490
Impact overlap
20 %
35 %
7°
15°
Impact angle
Future modifications to the proposed front to front compatibility test conditions may result
from the following trends:
 Shift in relevance of crash configurations based on the future modification of the
traffic conditions and the availability of advanced driver assistance systems (ADAS)
for collision mitigation or avoidance. This can justify major changes in test
configurations also with respect to the required crash test severity.
 Full virtual execution of tests can solve problems identified for several hardware based
test configurations including aspects like repeatability or test costs. Therefore, test
conditions showing the highest potential to promote the defined compatibility
priorities for small electric vehicles and their crash partners (Table 5) can gain in
relevance.
63
 To promote vehicle safety according to standards below the existing ones for M class
vehicles but higher than those for vehicles of the L7e class reduced crash requirements
have to be defined. This can be implemented defining test conditions resulting in a
reduced crash severity.
Model estimations on future traffic conditions in urban areas have identified the sinking
relevance of accidents in parallel traffic and resulting injury severities due to the increasing
application of ADAS for collision mitigation or avoidance and infrastructure improvements.
A tendency towards a closing speed reduction by up to 18 km/h for in-line crashes due to the
impact of ADAS results from that as well as a shift in relevance towards accidents in turning
and crossing traffic. [53]
Based on these findings future tests on front to front compatibility should focus on offset test
configurations with reduced closing speeds and oblique impact directions.
The focusing on a full virtual testing of front to front crash compatibility, that in future can
find application as exclusive test method for regulation and consumer protection assessments,
allows a modified evaluation of the compatibility tests currently in discussion. The ideal full
virtual test set-up identified during the FIMCAR project would consist of a series of vehicle to
vehicle crash simulations, where the assessed vehicle is tested against a fleet of generic crash
partners representative for the present vehicle fleet in all relevant front to front crash
constellations. As long as a commonly recognised fleet of generic crash partners is missing,
virtual car to car front crash testing can’t have relevance beyond principal compatibility
analysis in the vehicle design phase. [64]
Besides this ideal full virtual test set-up all vehicle to barrier test constellations presented in
chapter 4.3.2 require an assessment with regard to the defined compatibility priorities for
SEVs and their potential crash partners (Table 5). The results of this assessment, executed
within work package 2 of the SafeEV project, are presented in Table 8 to
Table 14.
Table 8. Assessment of full width test constellations according to defined compatibility
priorities. [(+) good / (o) neutral / (-) weak]
Test set-up
FWRB FWDB
Fulfillment of compatibility priorities for SEVs
(o)
(o)
Deceleration pulse for realistic restraint system performance assessment
(-)
(-)
Good structural interaction (futuristic designs)
(-)
(+)
(o)
(o)
(-)
(+)
Front end force adapted to SEV requirements
(+)
(+)
Fulfillment of compatibility priorities for conventional crash partners
64
Due to a more favourable assessment in comparison to the FWRB test, the crash test against
deformable barrier offers higher use potential as full width test also with regard to the defined
compatibility priorities in the SafeEV project. This selection is in conformity with the
recommendation for a full width test procedure formulated during the FIMCAR project [51].
Table 9. Assessment of offset test constellations according to defined compatibility
priorities. [(+) good / (o) neutral / (-) weak]
Test set-up
ODB PDB M(P)DB
(+)
(+)
(+)
Deceleration pulse for realistic restraint system performance
assessment
(-)
(-)
(+)
Good structural interaction (futuristic designs)
(-)
(+)
(+)
(+)
(+)
(+)
(-)
(+)
(+)
Front end force adapted to SEV requirements
(-)
(+)
(+)
Table 10. Detailed assessment of FWRB test according to defined compatibility priorities.
Test set-up
FWRB (Full Width Rigid Barrier) test
FWRB test is an additional test to offset test, not intended
for compartment strength assessment. [51]
Deceleration pulse for
realistic restraint system
performance assessment
Fixed barrier test results in deceleration pulses that are in
general not reproducing vehicle-to-vehicle crash pulse
situation due to missing partner movement. [65]
(futuristic designs)
Load path detection over load cell wall force response.
Detection of more rear structures not possible. [51]
FWRB test is an additional test to offset test, not intended
Load path detection over load cell wall force response.
Detection of more rear structures not possible. [51]
Front end force adapted to
SEV requirements
Front end force detection over load cell wall force response
[51]. Definition of mass dependent upper force limit in
assessment metric possible.
65
Table 11. Detailed assessment of FWDB test according to defined compatibility priorities.
Test set-up
FWDB (Full Width Deformable Barrier) test
FWDB test is an additional test to offset test, not intended
Load path detection over load cell wall force response. Can
also detect loads of more rear and unconventional
structures. [51]
FWDB test is an additional test to offset test, not intended
Load path detection over load cell wall force response. Can
also detect loads of more rear structures. [51]
SEV requirements
Front end force detection over load cell wall force response
[51]. Definition of mass dependent upper force limit in
assessment metric possible.
Table 12. Detailed assessment of ODB test according to defined compatibility priorities.
Test set-up
ODB (Offset Deformable Barrier) test
Current standard test on compartment strength.
No assessment of structural interaction possible with
applied EEVC barrier. [51]
Current standard test on compartment strength.
No assessment of structural interaction possible with
applied EEVC barrier. [51]
Tendency of heavy vehicles to overcrush deformable layers
66
SEV requirements
of EEVC barrier promotes very stiff front ends not adapted
to SEV requirements. [66]
Table 13. Detailed assessment of PDB test according to defined compatibility priorities.
Test set-up
PDB (Progressive Deformable Barrier) test
PDB designed to address same compartment strength issues
as ODB [66].
Load path detection over barrier face deformation
monitoring at end of crash [50]. Suitability for SEVs to be
checked through further investigations.
PDB designed to address same compartment strength issues
as ODB [66].
monitoring at end of crash [50].
SEV requirements
Front end force detection over barrier face deformation
depth. Definition of mass dependent upper deformation
depth limit in assessment metric in discussion. [50]
With regard to the special compatibility priorities defined for the SafeEV project a PDB or
MPDB tests show a higher use potential as offset test than the commonly known ODB test.
Possible issues on repeatability of PDB and MPDB tests [58] do not have the same
importance in a virtual testing environment than in hardware test set-up as long as the
boundary conditions of virtual testing are well defined.
To promote vehicle safety according to standards below the existing ones for M class vehicles
but higher than those for vehicles of the L7e class, reduced crash requirements resulting in
lower crash severities have to be defined. On the level of test set-up this can be simply
achieved by a meaningful scaling of the crash parameters for example in dependency of the
tested vehicle’s weight.
To limited extent this is already practiced for example within the consumer test protocol for
front crash defined by Euro NCAP. The Euro NCAP test protocol for heavy vehicles fixes the
test speed in the ODB test to reduced 56 km/h for vehicles above 2500 kg weight and with 8
seats and more [67]. This modification resulting in a reduction of the crash severity for this
type of vehicles is applied to address the problem of a bottoming-out of EEVC barrier by
heavy vehicles [66].
67
Table 14. Detailed assessment of M(P)DB test according to defined compatibility
priorities.
Test set-up
M(P)DB (Mobile (Progressive) Deformable Barrier) test
Can address same compartment strength issues as ODB
(proven if PDB is used as barrier face).
Crash partner movement also modeled, therefore realistic
vehicle-to-vehicle crash pulse generation possible under test
load case conditions. [65]
monitoring at end of crash (proven if PDB is used as barrier
face) [58]. Suitability for SEVs to be checked through
further investigations.
Can address same compartment strength issues as ODB
(proven if PDB is used as barrier face).
monitoring at end of crash (proven if PDB is used as barrier
face) [58]
SEV requirements
Front end force detection over barrier face deformation
depth. Definition of mass dependent upper deformation
depth limit in assessment metric possible. [50]
In a contrary sense such a test protocol modification can also be applied to reduce the test
severity for low weight vehicles like SEVs. The scalability potential of the different discussed
compatibility tests is evaluated in Table 15. A reduction of the safety level required for SEVs
can find a justification in the modified traffic conditions that these vehicles will be placed into
resulting in reduced front to front crash severities according to [53].
Table 15. Possible scaling parameters of front compatibility test constellations.
Test constellation
Scalability
Meaningful modification parameters
FWRB
Low
Impact speed
FWDB
Low
Impact speed
ODB
Medium
Impact speed and angle, overlap
PDB
Medium
Impact speed and angle, overlap
M(P)DB
High
Impact speed and angle, overlap, barrier trolley characteristics
68
The test constellation offering the most degrees of freedom for a meaningful test variation is
the M(P)DB test. Here, especially the barrier trolley characteristics can be modified in a sense
to represent different possible crash partners.
Under the special circumstances of full virtual compatibility testing a test constellation using a
MPDB is identified as having the highest use potential as offset test with regard to the
assessment priorities defined for the SafeEV project.
Some aspects of its use, such as the suitability of the PDB face for SEVs or the definition of
required test severity implemented in form of a choice for MPDB test parameters require
further investigations. These tasks will be addressed during the following SafeEV project
phases.
As long as these aspects are not quantified, the offset test configuration proposed by FIMCAR
– the ODB test according to the ECE regulation No. 94 [57] – is proposed as offset test for
front to front compatibility testing. This proposal will be reviewed with regard to future
findings on the usability of the MDPB test in the project report on final test configurations
and evaluation criteria due at the end of the project Work Package 3.
The FWDB test proposed by FIMCAR [55] as future full width compatibility test is identified
as most suitable full width test also with regard to the compatibility priorities followed during
the SafeEV project.
4.4 Rollover
Rollovers happen in a single vehicle accident or within a crash where the vehicle strikes at
least one other object (e.g. vehicle, infrastructure). Rollover can be induced due to railguards,
embankments, pavements, other vehicles and/or with a combination of velocity, friction level
and centre of gravity (CoG). In this section the focus is set on rollover test proposals for small
electric vehicles (SEV). Within the first WP the target year was set to 2025, due to future
mobility changes in the European Union. In Deliverable 1.1 and 1.2 of this project [68][69],
small vehicles were defined in terms of mass and with the input of the questionnaires
(wheelbase, centre of gravity (CoG),…). The average weight as well as the wheelbase is
expected to decrease. The CoG was estimated to be a bit higher and to move slightly
backwards. The longitudinal movement of the CoG depends strongly on the battery concept
and the placement of all electronic components. The vertical movement against the ratings of
the experts is expected to be lower as the high battery mass is normally (state of the art)
positioned below the passengers (e.g. fuel tank area), and therefore a decrease of the zcomponent compared to an internal-combustion-engine vehicle can be assumed. To develop
possible rollover test scenario for these vehicle types following issues will be addressed:



Relevant current regulations and other test methods.
Trends from WP1 of the SafeEV project, regulations and NCAP´s
Deriving future test scenarios supported with numerical simulations of small
generic electric vehicles.
Starting point of this discussion on future test specification is a review of current regulations,
NCAP´s and others shown in From the test review it is clear that rollover has less relevance
for Europe as there are not really tests defined which directly address this accident scenario
for M1 vehicles. In other countries these are more frequent/critical accidents. Research from
Young et al listed the fatalities caused due to rollover, which was one out of three to four for
69
USA and suggested one out of ten in Europe [76]. Specific rollover statistics for Europe were
not found.
Table 16.
From the test review it is clear that rollover has less relevance for Europe as there are not
really tests defined which directly address this accident scenario for M1 vehicles. In other
countries these are more frequent/critical accidents. Research from Young et al listed the
fatalities caused due to rollover, which was one out of three to four for USA and suggested
one out of ten in Europe [76]. Specific rollover statistics for Europe were not found.
Table 16. Current regulations for rollover testing.
Regulation
Test
ECE R21 [70]
Head impact pendulum Test.
ECE R44-04 [71]
Child Safety, Overturning Test (Manikin fall out Y/N, 360°,
Delta-Z <=300mm vertical movement)
FMVSS 226 [72]
Ejection Mitigation, Linear Impactor Test,
18kg, 16km/h@ 6sec & 20 km/h @1.5sec, four target locations.
FMVSS 208 [73]
Rollover, Full Vehicle, 48km/h, 23degree, HIII 50%.
FMVSS 216,216a (upgrade) [73]
Roof crush test, Both sides,
F = 3 x m * g ≤ [Vehicle mass = 2722 kg] < F = 1.5 *m * g
FMVSS 301 (Fuel, System Integrity) [74] Static Rollover, 90° Steps, Fuel Spillage.
CMVSS 216 [75]
Roof crush test, Similar to FMVSS 216
NCAP &Others
Test
US NCAP
SSF (Static Stability Factor), Fishhook Manoeuvre.
Rating with Risk Curve for tipping, or no tipping with SSF
ANCAP
Roof Crush Test
KNCAP
SSF, Fishhook Manoeuvre
IIHS
Roof Crush Test
The EU Rollover Project proposed numerical and experimental test methodologies as well as
some statistical data which should improve occupant safety. The conclusions of this project
were that 5 % to 10 % accidents involve Rollover and there was a fatality rate of 10 % to
20 %, depending on the European country. Due to a lack of data, it was not possible to gain an
EU-wide picture of Rollover accident statistics. With the available data and a Multi-Body
Simulation tool they investigated the critical areas within a vehicle during rollover. For AIS3+
injuries it was found by Gugler et. al that the important vehicle parts are the roof (50 %), the
A-pillar (15 %), ejection of the occupant (10 %), Trim parts and the occupant movement itself
with approximately ~7 %. For AIS 1 and 2 injuries the “occupant movement” itself was
shown to be the most critical with the highest share of nearly 20%. [77][78]
Within the Rollover project test suggestions were developed which included two types.
Proposal 1 was an inverted drop test instead of the roof crush test to proof the vehicle
70
structural protection and a second interior test with adding “stiffener plates” on the vehicle
outside for simulating an external force (e.g. “ground contact”). [79]
In accordance with Gugler et al. [80] three general types of rollover are taken into account.
They are shown in Figure 59.
Figure 59. Rollover type specification.
Within the Visio.M Project (German collaborative research project) rollover risk was shown
from 13838 vehicles involved in accidents to be 5% and for the extracted “small” generic
vehicle (360 vehicles) it was 4 %. The usage profile of these small vehicles was found to be
79% in urban areas, with the highest frequency of parallel traffic accidents, but without
autonomous safety systems which would reduce the frequency. The second important
accident type was turning or crossing. With a decreasing amount of parallel traffic accidents
due to probably higher efficiency and less chance of rollover, the second type is identified to
be more important for rollovers. [69]
A comparison between internal combustion engine passenger vehicles (ICEV) and battery
electric passenger vehicles (BEV) regarding the roll possibility is shown in Figure 60 where
the static stability factor SSF is marked for each type in the diagram. The SSF is calculated
with the track width divided by two times the z-CoG ground height. It was difficult to find the
track width depending on tyre dimension for selected vehicles. Therefore some
approximations had to be done (tyre dimensions). In Table 17 the SSF values for relevant
BEV´s and SEV´s are calculated. There are big differences for the analysed vehicles,
depending mainly on the track width. The z-ground distance for the CoG is for all vehicles
lower than for the ICE Smart, but as the track width is different the SSF´s are varying from
1.17 to 1.95. Walz et al studied the trends for SSF and published the average SSF for
passenger cars in 2003 to be at 1.41 [81].
Table 17. SSF calculated for different vehicle designs.
[73][82][83][84][85][86][87]
Looking at the Diagram, only the iMiEV and the TECOSIM-ICEV model are below the
average passenger car value of 1.41, which means they are worse and have a higher
71
probability for a rollover in a single vehicle crash. In the modified TECOSIM model, fuel
tank – battery replacement decreased the z-CoG and moved the SSF in the area of an average
passenger car. The REVM1 model developed in the project has an even higher SSF, due to
the vehicle track width and very low CoG. In the SmartBatt project the final model had a SSF
of ~1.6. No fishhook test was done, which doesn´t allow selecting one of the combined model
curves but the SSF-only curve is valid. The SmartBatt vehicle and REVM1 have a rollover
probability below 0.1 which means less risk (5 star rating), whereas the others have a higher
risk, but with the trend to decrease the roll probability (CoG shifting) compared with a similar
ICE vehicle. The generic vehicle is based on the data of the stochastic accident simulation
approach in Deliverable 1.1 of the SafeEV and MATISSE project and lies in the area of the
average passenger vehicle SSF and is used for side impact induced rollover prediction
[68][88].
Figure 60. Static Stability Factors of current vehicle designs integrated into the NHTSA
Rollover risk diagram. [88]
There was no investigation in WP1 directly addressing rollover, but in a second loop of the
side impact simulations the roll-angle was evaluated. The simulation basis was developed in
the MATISSE project (partner in SEAM cluster) and forwarded to the SafeEV project for a
final scenario definition. Four accident types, as shown in Figure 61, were considered [88].
The parameter set for these accident types are defined in Table 18. Within the baseline
scenario no “autonomous” system was activated. Within the future scenario an autonomous
system in the priority way car detected the non-priority way car and reacts when the nonpriority way car was 30 cm inside the traffic lane of the priority way car. For all simulations
the roll angle for rollover identification was defined to be greater than 40 degrees. All cases
below this threshold value are classified as no-rollover.
72
Figure 61. Four identified accident Types of the MATISSE project. [88]
Table 18. Parameter definition for the stochastic rollover side collision scenario
investigation
The results of this study are shown in Figure 62. For the baseline scenario 4.3% of all
accidents are identified as rollover relevant. Within the future scenario a trend in rollover
reduction is seen. 1.1 % rollovers resulted due to side collisions, of a reduced overall accident
frequency compared to the baseline scenario, because of mitigated cases. Limitations of this
study are: Only one generic vehicle with a SSF of 1.39 and 500kg was investigated, but from
D1.1 it is known that this would be the design which is expected the most in future urban
traffic. The future market share of vehicles equipped with autonomous systems will be not as
high as defined in this study. Due to the limitations a value between both may be realistic, but
as none of these is relevant in comparison to other accident types it shouldn´t be an issue.
73
Figure 62. Rollover probability within side impact collisions for a small generic electric
vehicle.
There was no further information found on future trends regarding regulations for the
European Union. There are no tests planned within the EuroNCAP roadmap.
Is there a need to introduce a rollover test for vehicle type approval, or not? Looking at the
information collected or developed there was no real relevant evidence compared with the
past why a rollover test scenario should be proposed for future SEV´s. Also there was no step
forward to propose rollover testing, after the Rollover project funded by the European Union
ended. But to ensure there are no critical designs without any protection (worst case) a short
assessment procedure can be defined which should not be a problematic issue for SEV
development.
Possible overall rollover description for the proposal of a test protocol is shown in Figure 62.
To evaluate at least the risk for a single rollover accident the SSF should be calculated and
integrated in a regulation, and included in the technical datasheet. This would be easy for all
OEM´s and as it is expected that most of the SEV´s have a higher SSF it will be no further
steps needed (e.g. roof crush). The second evaluation proposed, but again none-virtual is the
airbag standing time (AST), as suggested in the Rollover-project. After these two values are
defined by the OEM the decision on further steps for type approval should be defined.
One option would be to introduce a minimum required SSF and AST for type approval
without any testing procedures for rollover. Below this value a single or double roof crush test
with the evaluation of force-displacement as well as head and neck protection should be a
requirement. Additionally Ejection mitigation test can be considered for Virtual Assessment.
If the SSF and AST seem to be not enough for type approval the evaluation of a fishhook or
ESC test can be used to study dynamic stability issues in driving manoeuvres and could be
used as an optional evaluation possibility in the decision process for Virtual Assessment.
The right path in Figure 62 proposes a virtual multi-body simulation procedure for rollovers
induced due to collisions and environmental boundaries, but as described there is no relevance
74
seen, for both cases. Therefore no additional steps, in terms of finite element approaches are
defined.
In this chapter the relevance of rollover testing for SEV´s is discussed. A proposal which
should at least cover a SSF was defined. Based on this further issues can be evaluated.
Limitations of this proposal are sparely published data on European rollover real life
accidents. Also on which level of safety a minimum SSF should be defined. A short summary
can be given:



The SSF value compared to them for ICEV would be higher.
The SSF for electric vehicles with a smaller track width could be lower (define
threshold).
Both REVM´s are as good as the average Passenger Car model year 2003 SSF, or
even better.
After the Rollover project, no further research projects on testing proposals were started. It
can be concluded that no relevance was seen by reviewing the results. In Europe regulations
cannot be found for passenger cars. All discussed studies showed less relevance for taking
rollover accidents into account. Urban rollover accidents induced to side collision as shown in
the stochastic analysis are less relevant.
75
Figure 63. Rollover testing proposal for future SEV´s.
Considering the deliverable 1.1 of the project this situation will be further improved as new
mobility concepts, city developments, technological developments decrease conflict zones
and speeds. However, a future proposal was developed based on all the relevant research
results and should minimize the rollover probability for small electric vehicles.
Shortly summarized, following recommendations should be taken into account:
 A proposal which should at least cover the identification of a SSF and the AST
Based on these values further issues can be evaluated:
 The evaluation of Fishhook or ESC tests can support the decisions for virtual
assessment
 Decision on Inverted Roof Crush Test.
 Decision on Ejection Mitigation Testing.
76
4.5 Rear End
There are a limited number of rear-end impact tests specified in FMVSS and in ECE
regulations. Some of these are focused on fuel tank leakage and battery integrity, mainly these
are FMVSS 305 and ECE R32, and because these do not address occupant safety these tests
are not presented in this report.
In FMVSS 202 and in ECE R17 seat back and head restraint properties are controlled. ECE
R17 requires that a seat and head-restraint strength test is carried out. In the FMVSS 202 the
rearward angular displacement of the head reference line shall be limited to 45 degrees from
the torso reference line when a forward acceleration of at least 8g on the seat supporting
structure is applied. Alternatively, the head restraints must be at least 700 mm above the
seating reference point in their highest position and not deflect more than 100 mm under a
372 Nm moment. The head restraint must withstand an increasing rearward load until there is
a failure of the seat or seat back, or until a load of 890 N is applied.
Regulatory tests with the purpose to enhance in-vehicle protection against whiplash injuries as
sustained in rear-end impact, commonly referred to as Whiplash Associated Disorders
(WAD), are in power in the US since September 1, 2011. This regulatory test, referred to as
FMVSS 202a, requires that all head restraints in both the front and rear seats should pass a
static head-restraint geometry test. The head restraints must have a backset of no more than 55
mm as measured by an H-point machine (HPM) fitted a Head Restrain Measuring Device
(HRMD). In case a seat does not comply, then dynamic rear-end impact sled tests are to be
carried out using a Hybrid III 50% male dummy installed in the seat. The head to torso
rotation is to be measured and has to be lower than 12 degrees.
In parallel with the development of the FMVSS 202a, a Global Technical Regulation No. 7
(GTR 7) was drafted and was approved in 2008 under the 1998 agreement. In practical terms
this GTR is identical to the FMVSS 202a. Following the development of the GTR 7, the
Working Party 29 agreed that an informal group should continue to work to bring forward further
proposals to enhance in-vehicle protection against whiplash injuries. The activities of this
informal group, GTR 7 Phase 2 [91], will be presented in the section on important trends below.
To date, the rating programs within Euro-NCAP, Japan –NCAP (J-NCAP) and Insurance
Institute of Highway Safety (IIHS) includes a dynamic rear-end impact sled test in which the
seat system performance is assessed. Table 19 summarizes the sled accelerations and velocity
changes used in these programs. The tests procedures for the dynamic sled tests are rather
identical among these three programs; a BioRID II dummy is positioned in the seat according
to a positioning procedure in which an HPM/HRMD is used (Figure 64). The sled is
thereafter exposed to a forward acceleration that simulates a rear-end impact and several
measurements are collected and thereafter recalculate into performance grades.
In Euro NCAP, front seats are tested statically and dynamically according to Euro NCAP
Whiplash Testing Protocol [89]. Rear seats are assessed statically according to the Euro
NCAP Rear Whiplash Protocol [90].
77
Table 19. Test conditions used in NCAP programs
and in the rear-end impact tests performed by IIHS.
No. of dynamic tests
Δv (km/h)
Peak acc. (g)
Criteria
Euro-NCAP*
J-NCAP**
IIHS***
3
16.1
15.6
24.4
5.0
10.0
7.5
Head Cont. Time
T1 x-acceleration
Upper Neck Fx and Fz
Head Rebound Vel.
NIC
Nkm
1
20.0
1
16.0
11.9
9.5
NIC
Upper neck Fx Fz My
Lower neck Fx Fz My
Head Cont. Time
Torso acceleration Upper neck Fx Fz
* [89]
** [95]
*** [96]
Figure 64. BioRID II dummy installed in a seat prior to a Euro-NCAP rear-end impact test.
The GTR 7 Phase 2 draft [91] includes both static measurements and dynamic sled tests. The
static measurements include height, gap size in the head restraint and between restraint and
top of seat back, backset (Figure 65), head restraint and seat back strength and stiffness and
energy absorption.
78
Figure 65. Measurements of the seatback height (left) and gap size in head restraint (middle)
and backset using a HPM/HRMD (right) [91].
In the dynamic test either a Hybrid III 50th percentile male dummy or a BioRID II 50th
percentile male dummy shall be used to determine compliance. When the Hybrid III is used a
body in white or a vehicle mounted to a sled will be used. For the Hybrid III test, the rearward
angular rotation between the head and torso should be below 12 degrees and HIC15 value
should be below 500 in all outboard designated seating positions.
Seat system evaluations using a BioRID II are to be carried out with the seat mounted on a
sled and a generic belt system. The BioRID II should be updated and certified according to
GTR 7 Phase 2 standards [91]. The sled acceleration should be within the corridor specified in
Figure 66 and result in a velocity change of 17.6 km/h.
Figure 66. Sled acceleration corridor suggested for the GTR 7 Phase 2 [91].
EuroNCAP is currently reviewing its test protocols for the near future; a report that presents
future test changes is expected to be made available to the public soon.
A few years ago Whiplash Associated Disorders (WAD) from a rear-end impact accounted
for a very large proportion of all traffic injuries leading to long-term consequences. Seat
79
concepts aimed at lowering the risk of WAD have been found to reduce the risk of WAD
following a rear-end impact (Table 20, [92]). The market penetration of these seat concepts is
still increasing. More recently AEB have been introduced and it is estimated that at least 50%
of the car fleet will be equipped with AEB in year 2020. It has been estimated that this market
penetration will reduce the number of crashes by 50% and the closing speed between two
vehicles will also be reduced by 50% when the impacting car is equipped with AEB. It is
therefore expected that the number of persons suffering from WAD as a consequence of a
rear-end impact will be reduced in the future.
However, the data presented by Kullgren et al. (2013) [92] indicate that there is no or very
slight reduction in risk of WAD between the 2000-2004 and the 2005-2009 groups (Table
20). Possibly, the risk of WAD in the future may therefore be close to those of these two
groups if the test protocols currently used remain unchanged. This would mean that WAD due
to rear-end impacts would continue to be the traffic accident condition that results in the
largest number of occupants with long-term consequences. To tackle this it is important that
additional research is undertaken and these test protocols are updated.
Table 20. Proportions (and 95% confidence limits) of female and male drivers (%) with
symptoms for more than one month and permanent medical impairment (PMI) in relation to
number of reported initial symptoms for rear-end impacts as a function of year of
introduction on the market (adopted from [92].
Rear-end
<1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
2005-2009
symptoms > 1 month
pmi
Male
Male
15.5
15.1
15.4
14.4
12.4
9.4
10.0
Female
±
±
±
±
±
±
±
2.4
1.7
1.5
1.5
1.3
1.9
3.3
20.0
19.4
19.0
18.0
15.8
11.5
14.4
±
±
±
±
±
±
±
2.9
2.0
1.9
1.8
1.4
1.9
3.4
9.2
8.8
9.5
8.4
6.0
4.6
3.3
Female
±
±
±
±
±
±
±
1.9
1.3
1.3
1.2
0.9
1.5
2.5
11.2
12.2
11.3
10.3
8.9
5.7
6.7
±
±
±
±
±
±
±
2.3
1.6
1.6
1.4
1.1
1.6
3.2
Carlsson 2010 [93] analysed accident data base studies that compared males and female
whiplash injury risk and found that the risk was on average almost two times higher for
females (Figure 67). The study by Kullgren et al. (2013) [92] found this to be partly the case
also for more recent car models (Table 20). This calls for the development of test conditions
that are representative of real life accidents in which the female is the occupant. As a
consequence a female 50% dummy, injury criteria and risk functions tailored for females
should be developed.
Currently three sled pulses are included in Euro NCAP test protocol. A possible benefit of this
inclusion is that a seat that obtains a good rating performs well independent of impact
severity. However, only one BioRID posture is specified in current test protocols. Several
studies have shown that the average occupant posture differs from those specified in the test
protocols.
80
Figure 67. Relative whiplash injury risk for females compared to males [93].
A large market penetration of AEB systems is expected in a few years’ time and may result in
an even larger proportion of the occupants that is in non-reference posture when impacted
from the rear. Hence, it is expected that the number of persons that suffer WAD will be
reduced if also seat tests were carried with the BioRID II in non-reference postures
representative of the postures seen in real-life driving.
For additional assessments of seat system robustness, test protocols that use a 5% female
dummy and a 95% male dummy should be drafted and considered. Currently there is no rearend impact dummy available in these sizes; possibly scaled finite element models of the
BioRID II is the way forward. Test data from rear-end impacts with the BioRID II 50% male
and 50% female could serve as seat system and seat interaction validation data. The validated
seat model could then be used to assess the performance of the seat for 5% and 95%
occupants in a virtual environment (FE-environment).
The introduction of AEB systems may call for changes in the tests protocols. A shift in deltaV due to introduction AEB is expected. It may be cost efficient to test seat systems in a rather
low velocity that is representative of the velocity change in the car that is impacted by a car
that is fitted an AEB system. A large AEB market penetration may introduce changes to the
fleet speed and gaps between cars in dense traffic. This would call for a test at a higher delta
V than used today.
It is expected that due to vehicle design and packing, the front and rear-end vehicle stiffness
will increase. This calls for a review of the sled pulses to be used in future rear-end impact
tests.
Davidsson and Kullgren (2013) found poor correlation for some of the criteria and parameters
included in the assessment of whiplash performance in Euro-NCAP [94]. This suggests an
update of the injury criteria to be used to assess the risk of WAD (see chapter 5).
The introduction of AEB and introduction of seat concepts aimed at lowering the risk of
WAD will reduce the number and risk of WAD in rear-end impacts. However WAD will
remain frequent and the consequences will lead to large societal costs and personal suffering.
81
To tackle this additional and improved test tools and test conditions are to be developed and
introduced. Among these are a female dummy and associated limits and a large size dummy.
For reduction of tests finite element models of dummies could be developed and used in
sensitivity studies, e.g. studies of the performance in non-reference test postures. Also there is
potential to use human body models in different sizes. Within SafeEV (WP3) it was decided
however that the focus of the simulation activities will not be on whiplash.
4.6 Other Accident Modes
The “other accident modes” that will be discussed in this section are the so-called Multiple
Impact Crashes (MIC’s) [97]. In a MIC a vehicle is subjected to more than one impact with
other vehicles or with the surroundings (trees etc..). Figure 68 shows a typical example of a
MIC.
Figure 68. Example of a Multiple Impact Crash [98]
In this example the vehicle that experiences a multiple crash (called host vehicle in this
figure) is first impacted from the side/front by another vehicle (bullet vehicle) after which it
undergoes a 2nd crash with a guard rail.
Different accident studies show that about 25% of all passenger vehicle accidents are MIC’s
[98]. An analysis of MIC’s in the GIDAS database from accidents in the period 1999 to 2007
showed a that the risk of severe injuries is 3 times larger than in Single Impact Crashes
(SIC’s) and the risk on fatalities even four times larger [99]. The GIDAS database used here
consisted of 9316 reconstructed accidents, involving 13392 passenger cars with 15639
occupants, sustaining 18169 impacts. 24% of the accidents were MIC’s (see Table 1). 16 % of
them being 2-impact crashes, 5.2% 3-impact crashes, 1.9% 4-impact crashes and 0.7 %
involving 5 or more impact crashes. Rollovers are included in this GIDAS database: 4.4% of
all passenger cars had a rollover of which the majority (90%) occurred within a MIC [3].
82
In the same study [99] also the activation of irreversible restrain systems (pre-tensioners and
airbags) was investigated. In 2/3 of MIC’s with severe injuries the irreversible restraint
systems were not activated if the first impact was a front impact and in about 50% of the cases
if the first impact was a side impact [3]. As a consequence the occupant involved in a MIC in
which an irreversible system is not activated in a first impact has a much larger risk of being
Out-Of-Position (OOP) in the next impact (s).
Table 21. SIC’s and MIC’s in GIDAS database 1999-2007 [99].
Another risk in MIC’s is that if an irreversible restraint system like an airbag is activated in a
first impact that it may not be able to protect the occupant in the next impact(s) anymore for
instance due to deflation of the airbag in the time between the 2 successive impacts.
Up to now regulatory and consumer crash tests focus on single vehicle crashes like front, side
and rear impacts. Currently no specific regulatory crash tests exist concerning MIC’s. So the
protection offered to an occupant relies on the protection offered in the separate impact events
of a MIC. As shown in the preceding section in particular irreversible restraint systems may
cause limited protection capabilities if more than one impact occurs during an accident.
Considering the results from WP1 it can be predicted that the future risk and the severity of a
first impact leading to a MIC will reduce so that the number and severity of MIC’s in general
will reduce in the future. Since MIC’s as such, as shown in the introduction, occur very
frequently and have a significant higher injury risk than single accidents, MIC’s also in the
future will constitute an important part of injury causing accidents. Therefore further steps are
needed.
Two principal strategies can be distinguished to reduce the risk of injuries in case of MIC’s:
1. Use of intelligent manoeuvres of the vehicle after the first impact in order to reduce
the risk of a second impact or to reduce the risk of severe injuries in second (and
following) impacts. In particular automatic braking after the first impact and control of
the lateral motion after the first impact is of high relevance [98]. An example of an
automatic braking system is Audi’s secondary collision brake assist that recently
received a EuroNCAP reward [100]. For control methodologies to influence the lateral
vehicle motion see for instance [98]. See also Chapter 2 concerning evaluation of precrash and active safety systems.
83
2. Use of reversible and irreversible restraint systems that protect also in MIC’s. See for
instance [99] concerning optimization of pretensioners for MIC’s and [101] for a 3+2
point belt system and inboard torso side support in frontal, far-side and rollover
crashes.
The need to protect people in MIC’s is clearly there considering the large frequency of these
crashes and the relative high injury risk. The EuroNCAP initiative to reward a secondary
collision brake system indicates a trend to give more attention to MIC’s in the future in
consumer and regulatory testing. Test methods to improve injury protection of vehicle
occupants in a MIC can be largely based on virtual test methods. See for instance [99] where
THUMS was used to study pretensioning in MIC’s. It is expected that supplier of protection
systems as well as OEM’s will give more attention in the future to safety systems that offer
better protection in MIC’s. For 2025 it can be expected that safety regulations will include
control of vehicle motions during a MIC. Furthermore it can be expected that consumer
testing (like EuroNCAP) will reward protection systems that offer optimal protection in
MIC’s rather than only in single impacts.
Although the frequency and injury severity of Multiple Impact Collisions (MIC’s) will
decrease due to the trends presented in WP1, a strong need to protect people in MIC’s remains
due to the large frequency of these crashes and the relative high injury risk. Recommendations
concerning future work in SaveEV (WP3 etc.) concerning MIC’s are:
1. Inclusion of occupant simulations (virtual testing) with active HBM of extreme
controlled vehicles manoeuvres that are aimed to reduce the risk of or the severity of
second (or more) impacts in a MIC. The aim of such simulations is to study the effect
on human position changes during such manoeuvres and the resulting risk on OOP’s.
2. Inclusion of occupant simulations aiming of optimization of reversible and irreversible
restraint systems during MIC’s.
84
5 Criteria for assessments of SEV safety in crashes
5.1 Injury Criteria
5.1.1 Current Criteria for VRU protection
Head
Over the past forty years, a slant has been put by the biomechanical research on the
understanding of the head injury mechanisms. One of the main difficulties of this research
field is that a functional deficiency is not necessarily directly linked to a damaged tissue.
Nevertheless, an injury is always a consequence of an exceeded tissue tolerance to a specific
loading. Even if local tissue tolerance has very early been investigated, the global acceleration
of the impacted head and the impact duration are usually being used as impact severity
descriptors. In some previous studies, numerous injury predictors based on translational or
rotational head motions were proposed:




Maximum linear acceleration, used for many years and continues to be used in many
helmet standards Amax<N with N a value which depends on the standard used
A-3ms value which refers to the maximum deceleration that lasts for 3ms
Severity Index (SI), proposed by Gadd (1961), was a precursor of the actual HIC
[102]. The SI was designed like:
SI   An dt  TAn  1,000
o
o where A is either effective values of linear acceleration, force, or pressure,
which is a response function producing threshold of injury, T is time duration,
and n is weighting factor equal to 2.5
In an attempt to combine translational and rotational acceleration, Newman (1986)
[103], in contact with Transport Canada, introduces the concept of generalized
GAMBIT (Generalized Acceleration Model for Brain Injury Tolerance). The model
attempts to weight, in an analogous manner to the principal shear stress theory, the
effects of the two forms of motion:
1
 a(t )  m   (t )  n  s
  
 
G (t )  
 ac    c  




o
o where a(t) and (t) are the instantaneous values of translational and rotational
acceleration respectively. c and ac are limiting critical values and n, m and s
are empirical constants (n=m=s=2.5, ac=250g, c= 25.000 rad/s²). G=1 is set to
correspond to a 50% probability of MAIS 3.
The Head Impact Power (HIP) proposed by Newman et al. (2000) [104], the head is
also seen as a one mass structure. It is computed using both linear and angular
accelerations measured at the centre of gravity of a Hybrid III dummy head as shown
in the following formula:
HIP  C1a x  a x dt  C 2 a y  a y dt  C3 a z  a z dt  C 4 x   x dt  C5 y   y dt  C6 z   z dt


 
Linearcontribution
Angularcontribution
o
The Ci coefficients are set as the mass and appropriate moments of inertia for the
human head: C1=C2=C3=4.5 kg, C4=0.016 Nms², C5=0.024 Nms², C6=0.022 Nms².
ax, ay and az [m/s2] are the linear acceleration components along the three axes of the
inertial reference space attached to the dummy head.
x, y and z [rad/s2] are the angular acceleration components around the three axes of
the inertial reference space attached to the dummy head.
85

o Since the HIP is a time-dependent function, the value taken as an injury
predictor candidate is the maximum value reached by this function. HIP was
designed only for brain injury and not for SDH or skull fracture.
Kleiven (2007) proposed a linear combination of HIC36 and the maximum resultant
angular velocity as a brain injury predictor [105]. The Kleiven’s linear combination
(denotes KLC) is represented as:
KLC  0.004718r  0.000224HIC36
o
o where ωr is the maximum resultant angular velocity.
All criteria used in order to protect the head of a VRU are based on the linear accelerations of
a one mass headform with no distinction about impact orientation and the most used criterion
is the Head Injury Criterion (HIC).
The Head Injury Criterion (HIC) has a historical basis in the work of Gadd (1961) [102] who
used the Wayne State Tolerance Curve (WSTC) to develop what eventually became known as
the Gadd severity index GSI (1966) [106]. The WSTC is based on the average resultant
translational head acceleration. It evolved from the early work of Gurdjian and co-workers
(1955) [107] who used the clinically observed prevalence of concomitant concussions in skull
fracture cases (80% of all concussion cases also had linear skull fractures [108]) to relate
cadaver impacts to brain injury. Gurdjian and co-workers concluded that by measuring the
tolerance of the skull to fracture loads one is effectively inferring the tolerance to brain injury.
Lissner and co-workers (1960) later developed a relationship between the magnitude of the
translational anterior-posterior acceleration and the load duration that became known as the
WSTC [118]. Versace (1971) proposed a version of the current HIC in 1971 as a measure of
average acceleration that correlates with the WSTC [119]. HIC was then proposed by NHTSA
as a replacement for the GSI in FMVSS No. 208 and is computed according to the following
expression:
2.5

 1 t2
 

HIC  max (t2  t1 ) 
 a(t )dt  
( t1 , t 2 )
t

t
2
1

t

1

 
2
Where a [m/s ] is the resultant linear acceleration measured at the center of gravity of the
Hybrid III dummy head. t1 and t2 [ms] are chosen in order to maximize the HIC value.
The maximum time duration (t2–t1) was set as 36 ms at first, however, current standards use
15 ms. Therefore, variable term for HIC is expressed as ‘‘HIC15’’. A HIC15 of 700 was
estimated as a 5% risk of Abbreviated Injury Scale (AIS) 4+ head injury. For adult
pedestrians, a HIC value of 1,000 within a time window of 15 ms has been proposed as an
injury tolerance level for severe head injuries (EEVC, 2002 [109]). Probability of head
injuries of different severities for given HIC values are presented in Figure 69. Figure 70
presents a synthesis of test procedures and head protection criteria for pedestrian protection.
86
Figure 69. Probability of head injuries of different severities for given HIC values.
Figure 70. Head Protection Criteria for Pedestrian Protection.
Lower Leg
In case of pedestrian accident, leg injuries represent 1/3 of body region with AIS2-6. The
bumper is predominantly the cause of these leg injuries. The predominant injuries are on the
lower leg followed by the knee joint, femur and foot. Thus several criteria are used to evaluate
leg injuries. The main injury mechanisms are depicted in Figure 71.
87
Figure 71. Injuries mechanisms in case of pedestrian impacts.
For pedestrian impact, some specific criteria are used:
 Angle in knee lateral flexion [deg]
 Displacement in knee lateral shearing [mm]
 Lateral acceleration of tibia [g]
 Elongation of Medial Collateral Ligament (MCL), Anterior Cruciform Ligament
(ACL) and Posterior Cruciform Ligament (PCL) [mm]
 Bending moment in tibia [Nm]
Figure 72 shows the injury criteria for VRU used in several regulations.
Figure 72. Synthesis of VRU injury criteria used in regulations with limits values.
5.1.2 Current Criteria for Occupant Protection
Frontal impact
Head
Head injury continues to be a leading cause of death and disability although considerable
advancement in the understanding of head injury mechanisms and the introduction of airbag
restraint systems has resulted in the reduction of the number and severity of head injuries. In
spite of these advancements the only injury criteria in wide use is the Head Injury Criterion
(HIC).
88
The Head Injury Criterion (HIC) has a historical basis in the work of Gadd (1961) who used
the Wayne State Tolerance Curve (WSTC) to develop what eventually became known as the
Gadd severity index GSI (1966) [102]. The WSTC is based on the average resultant
translational head acceleration. It evolved from the early work of Gurdjian and co-workers
(1955) [107] who used the clinically observed prevalence of concomitant concussions in skull
fracture cases (80% of all concussion cases also had linear skull fractures [108]) to relate
cadaver impacts to brain injury. Gurdjian and co-workers concluded that by measuring the
tolerance of the skull to fracture loads one is effectively inferring the tolerance to brain injury.
Lissner and co-workers (1960) later developed a relationship between the magnitude of the
translational anterior-posterior acceleration and the load duration that became known as the
WSTC. Versace (1971) proposed a version of the current HIC in 1971 as a measure of
average acceleration that correlates with the WSTC [119]. HIC was then proposed by NHTSA
as a replacement for the GSI in FMVSS No. 208 and is computed according to the following
expression:
2.5

 1 t2
 

HIC  max (t2  t1 ) 
 a(t )dt  
( t1 , t 2 )

 t2  t1 t1
 
where a [m/s2] is the resultant linear acceleration measured at the center of gravity of the
Hybrid III dummy head. t1 and t2 [ms] are chosen in order to maximize the HIC value.
The maximum time duration (t2–t1) was set as 36 ms at first, however, current standards use
15 ms. Therefore, variable term for HIC is expressed as ‘‘HIC15’’. A HIC15 of 700 was
estimated as a 5% risk of Abbreviated Injury Scale (AIS) 4+ head injury. For adult
pedestrians, a HIC value of 1,000 within a time window of 15 ms has been proposed as an
injury tolerance level for severe head injuries (EEVC, 2002 [109]).
Another criterion is A-3ms value which refers to the maximum deceleration that lasts for 3ms
In 2011, Takhounts et al proposed a new metric in order to define a head injury criterion for
Hybrid III dummy head in frontal impact [120].
Frontal impact tests with the Hybrid III dummy (43 NCAP tests – drivers and passengers –
available from NHTSA database) were used to develop the rotational Brain Injury Criterium
(BRIC) for frontal impact. To do that, first, based on criteria established previously with a
finite element head model (SIMon FEM, [110]), Cumulative Strain Damage Measure
(CSDM) values were calculated for each test. Then optimization was carried out to obtain the
best linear fit between CSDM and BRIC (in the form of the following equation) using critical
values of angular velocity and acceleration ωcr and αcr as design variables and subjected to the
constraint that BRIC=1 when CSDM =0.425 (30% probability of DAI/AIS4+).
Where
and
are maximum angular velocities and accelerations for each accident
cases respectively. The linear relationship between CSDM and BRIC was then utilized to
obtain risk curves for hybrid III dummy (Figure 73). The critical values of angular velocity
and acceleration for the Hybrid III dummy were found to be ω cr=46.41 rad/s and
αcr=39,774.87 rad/s2.
89
Figure 73. Risk of brain injuries as a function of BRIC for various AIS levels for Hybrid III
(Frontal impact).
Neck
The neck injury criteria are numerous. For Frontal impacts it exists:





NIC (ECE, EuroNCAP)
Nij: Normalize neck injury criteria
NIC (FMVSS)
MOC: Total moment at occipital condyle
MTO: Total moment at lower neck
which will be explained more in detail in the following section
NIC (ECE, EuroNCAP) [111] and [112]is determined by the axial compression force, the
axial tensile force, and the shearing forces at the transition from head to neck, expressed in
kN, and the duration of these forces in ms. Figure 74 shows tolerance limits in terms of forces
used by standards.
Figure 74. Tolerance limits for ECE and EuroNCAP (upper neck Fx) respectively.
Nij [113]is Normalized Neck Injury Criterion and is composed of four Neck Injury Predictor:


NTE: tension-extension < 1
NTF: tension-flexion < 1
90


NCE: compression-extension < 1
NCF: compression-flexion < 1
The equation to calculate Nij is:
with Fz is the force at the point of transition head to neck, Fzc is the critical force, MOCy is the
total moment and Myc is the critical moment. The critical values depend on the tested dummy.
The different values are reported in Table 22.
Table 22. Critical value of Force and Moment for different dummies.
Fzc [N]
Fzc [N]
Myc [Nm]
Myc [Nm]
Dummy type
Tension
Compression
Flexion
Extension
Hybrid III, male 50%
Hybrid III, female 5%
Hybrid III 6YOD
6806
4287
2800
-6160
-3880
-2800
310
155
93
-135
-67
-37
Mertz et al. (1982) [114] and Prasad and Daniel (1984) [115] performed tests in order to
analyse the impact of the airbag deployment on animals (pigs aged 10 weeks) corresponding
to the size, weight and tissues a 3 year old child. In their study, the tests were conducted in the
same way that those charged with the 3 year old model. This allowed to correlate the different
severities of injury obtained from pigs, with model responses. Neck injuries observed were
initiated by the tearing of small blood vessels in the lining of the capsule of the occipital
condyle. This led to the tearing ligament rupture wing, to spinal cord and cerebellum and
ultimately death when the severity of the impact increased. The blood in the synovial fluid
from the capsule occipital condyle was evaluated as AIS=3.
Based on the location and nature of the neck injuries (tension, extension and combination of
both) the model of three years has been proposed as an indicator of neck injury severity. Both
studies showed that the strength of the neck was the best indicator of the limit AIS≥3, with a
threshold value of 1160 N. However, the severity of the neck injury corresponding to a
tension of 1160 N was fatal. Mertz & Weber (1988) [116] analysed data from Mertz et al.
1982 [114]and proposed a risk curve for AIS≥3 based on the neck tension measured on the 3
year dummy neck. This risk curve is normalized to the size and strength to offer risk curves
for all ages and all sizes of children and adults.
MOC is the total moment about occipital condyle. It calculates the moment along X and Y
axis at the head-neck junction as defined in the following equations:
With MOCi total moment in i direction [Nm], Fi Neck force in i direction [N], Mi Neck
moment in i direction [Nm] and D Distance between the force sensor axis and Condyle axis
[m].
91
100
Nij Risk Curve [%]
80
AIS 2
AIS 3
AIS 4
AIS 5
60
40
20
0
0
2
4
6
8
10
Nij
Figure 75. Representation of neck injury risk curves corresponding to Nij criteria.
Peak forces at neck level – the limit peak values for several dummies are tabulated in Table
23.
Position
In position
Out of position
Table 23. Limit peak Force for different dummies.
Fz[N]
Fz[N]
Dummy Type
Tension peak
Compression peak
4170
-4000
2620
-2520
Hybrid III, 6 year
1490
-1820
Hybrid III, 3 year
1130
-1380
CRABI 12 months
780
-960
2070
-2520
MTO is the total moment and applies for lower neck. This criterion calculates the total
moment in relation to the moment measurement point as follow:
With MTOi Moment in i direction [Nm], Fi Neck force in i direction [N], Mi Neck moment in i
direction [Nm] and Di z<
Distance between the force sensor axis and the condyle axis[m].
92
Thorax
Thorax is composed of a rib cage containing
several vital soft organs. It extends from the base
of the neck to the diaphragm which corresponds to
the lower limit separating the abdomen. The rib
cage is formed of twelve pairs of connected ribs
on the thoracic vertebrae. On anterior area, seven
are fixed to the sternum while the lower ribs are
either indirectly attached to the sternum, or
attached to muscles and the abdominal belt. The
ribs are very flexible for newborns and they stiffen
with age as well as the joints with the sternum and
vertebrae. In addition the rib angle changes with
age; rib angle is steep when newborn and become
flatter with age. The rib cages of young persons
have properties such that rib fractures are
uncommon but the rib cage flexibility is such that
soft tissue injuries without fractures may occur.
On the other hand, this increased rigidity with age
makes more fragile cage, for loads common in
frontal car crashes rib fractures frequently occur,
and reduces the protective potential.
The inner volume can be divided into three parts
Figure 76. Thorax anatomy
as illustrated in Figure 76: right and left region
Sobotta 2010 [117].
containing the lungs and center with the heart
(mediastinum), the trachea and the large blood vessels. The mediastinum is located between
the lungs, the thoracic vertebrae and the sternum. It includes large vessels such as the aorta,
cava veins and pulmonary arteries and veins. Due to the limited space, anterior compression
of the chest can easily cause internal damage.
In case of a brutal deceleration because of a hard impact, three different mechanisms of injury
can be distinguished: compression, viscous loading and inertial loading of the internal organs.
The resulting damage can be classified as either skeletal lesions either soft tissue injuries.
The rib fractures depend of the impactor shape and can cause lungs lacerations. Moreover, an
excessive acceleration can interrupt the electromechanical signal of heart. Rupture of the aorta
is due to a tensile or a shearing force caused by compression of the cage on the spine as
shown in Figure 77. It may also be due to the combination of a hyperextension of the neck
with the chest compression (Figure 77b).
Other organ injuries of thorax can be esophageal rupture and laceration of the diaphragm
which leads to is a hernia, as illustrated in Figure 78.
Several tests were performed to determine the behavior of the human thorax in terms of
acceleration, force, strain and pressure, in particular tests on cadavers led by Kroell et al.
(1971) [122], Stalnaker & Mohan (1974) [123] (Figure 79), in which detailed lesions were
obtained after impact.
93
(a)
(b)
Figure 77. (a) Heart compression and aorte failure, (b) combination of thorax compression
and neck extension leading to aortic laceration [121].
Figure 78. Hernia of diaphragm due to an abdomen impact [121].
(a)
(b)
Figure 79. Impact test on cadavers at sternum level; Force-displacement curve of thorax
[122][123].
94
Current criteria for assessment of THORAX injuries used in legislative frontal impact tests
and in consumer rating programs are limited to:
 Spine Acceleration 3ms
 Maximum Chest Compression
 Viscous Criterion
 Combined Thoracic Index
These were primarily developed for the Hybrid III 50M dummy.
The Spine Acceleration criterion was the first criterion used to evaluate the human thoracic
response to dynamic loads. It was based on experiments by Stapp and the observations
reported by Eiband (1959) [124] that the level of acceleration that humans withstand
decreases with the length of the exposure. The previous version of the Federal Motor Vehicle
Safety Standard (FMVSS) 208 states that peak spinal accelerations measured with Hybrid III
should not exceed 60g for more than 3 ms to avoid severe thoracic injuries. To achieve a good
rating in the IIHS 40% offset deformable barrier (ODB) test maximum spinal acceleration (3
ms) measured with Hybrid III should be below 60g. C-NCAP uses the limits 38g and 60g for
the lower performance and the capping limit, respectively, in both the full frontal and ODB
tests.
However, it has been found that spine acceleration is not a suitable criterion for chest injuries
due to several reasons. The criterion has been found to be load dependant. The criteria fail to
identify local areas with high stresses in the ribcage. In addition, the thorax acceleration
values have been found to be affected by other load paths between an occupant and the
interior, e.g. if the head impacts the car interior or an airbag [125].
Resultant chest acceleration is commonly measured in child dummies and is currently the
only available measurement regularly used to assess chest injury risk for children in frontal
collisions.
The maximum Chest Compression criterion, the Cmax, was first defined by Kroell et al. (1971)
[122]. The criterion is defined as the mid sternal deflection divided by the initial thoracic
depth. It was found to correlate with AIS outcome for chest impactor tests. Kroell et al. (1971,
1974) found that the onset of rib fractures starts at 20% compression [122][126]. Mertz et al
(1991) reconstructed real life accidents in which three-point safety belts were used [127]. The
data was used to develop a thoracic injury risk curve for AIS>3 based on the sternum
deflection of the Hybrid III 50% adult male (Figure 81a).
In the FMVSS 208 two limits are used:
- 52 mm limit for Hybrid III female 5%
- 63 mm limit for Hybrid III male 50%
Thoracic Compression Criterion (ThCC or TCC) is similar to the Cmax criterion; it is the
compression of the thorax in frontal impact between the sternum and the spine. Today a
maximum threshold value of 50 mm is defined in ECE R94 for the Hybrid III male 50%
dummy.
Euro-NCAP (40% ODB tests) and C-NCAP (full frontal and 40% ODB tests) also uses ECE
R94 chest compression values for the lower performance and the capping limit. For the higher
performance limit maximum chest compression as measured in a Hybrid III male 50%
dummy in the front seat is 22mm. In the C-NCAP tests a Hybrid III 5% female is installed in
the rear seat row. For these tests the chest compression limits are 48 mm and 23 mm.
95
Despite that Cmax and TCC are the injury criteria used worldwide it has some serious limits
regarding its applications. Kent et al. (2005) showed that the risk curve in terms of sternal
deflection (or Slider Deflection) is restraint dependent when measured with Hybrid III
dummy. As shown in Figure 80, the risk curve relative to impactor loading is completely
different from that of airbag loading and that of belt loading. This dependence to restrain type
raises a serious interrogation on the relevance of the criterion for its use on the Hybrid III
dummy. It means that it is incorrect to compare injury risk between these loading types. It
means also that the risk curve established using different loading types is no relevant.
The Viscous Criterion (VC) was developed by Lau & Viano (1986) to assess soft tissue
injuries [130]. It is the maximum momentary product of the chest compression (C) and the
rate of the thorax compression (V). Both quantities are determined by measuring the sternum
deflection. It is defined as the maximum of the
following product:
𝑉 𝑚𝑎𝑥 = max 𝑉 𝑡 ∗
𝑡
𝑑𝐷(𝑡) 𝐷(𝑡)
= max⁡
∗
𝑑𝑡
𝑏
where D(t) is the time history of the chest
deflection and b is the initial chest depth.
The authors also proposed thoracic risk curves
for AIS>4 (Figure 81b). ECE R94 requires the
VC in the Hybrid III to be less or equal to 1.0
m/s. Euro-NCAP uses the same value for the
lower performance and the capping limit but
0.5m/sec for the higher performance limit.
Figure 80. Risk curves for AIS3+,
constructed for the Hybrid III dummy in
terms of maximum slider deflection (Kent
[128]).
The VC criterion is mainly applicable when the chest compression rates are in the range of 3
to 30 m/s [130]. This is commonly greater than the chest compression rates expected for a belt
restrained car occupant*; at least for elderly occupants.
(a)
(b)
Figure 81. Thoracic risk curves (a) for AIS>3 in function of Hybrid III sternum deflexion,
(b) for AIS>4 in function of Viscous Criterion.
96
In addition to the thorax criteria used in frontal impact legislative and consumer information
testing the following chest criteria are used and described:
 Chest Deflection Rate – CDR
 Combined model criterion - CM
 Combined Thoracic Index - CTI
 Energies
Chest Deflection Rate (CDR) is the criterion of the compression rate of the chest which is
calculated by differentiation of the sternum relative to spine deformation.
Combined Model Criterion (CM) was based on a statistical analysis of 63 sled tests with
PMHS instrumented with chest bands and accelerometers by Morgan et al. (1994) [131]. The
injury criterion combines chest deflection, deflection rate, acceleration and age. It was found
thta separating the sample of 63 tests in belt and air bag-like restraint modes improved the
injury assessment of the criterion. A further improvement was noticed when different criteria
were used for the belt and air bag-like modes. A process where the type of restraint mode is
assessed first and then the corresponding injury criterion calculated was proposed. The
restrain mode is identified by assessing the symmetry of the deformation pattern of the thorax.
For the latter, the dummies would have to be fitted with mutiple chest deformation
transducres as described in Figure 82.
Figure 82. Location of the five measurement points on the chest.
The coefficients in these criteria were calculated by the use of statistical analysis of PMHS
results. No coefficients have been made available for the Hybrid III or the THOR dummies.
Combined Thoracic Index (CTI) predicts AIS<3 thorax injuries and was developed by
Kleinberger et al. (1998) [132]. It is the 3 ms value from the maximum normalized resultant
thoracic spine acceleration and the mid-sternum chest deflection at any of the five locations
on the thorax. Since dummies available at the time of development of CTI were only able to
measure the mid sternal deflection, that value was used instead of the maximum of five points
on the thorax. The criterion for Hybrid III is calculated according to:
CTI =
Amax Dmax
+
Aint
Dint
with Amax being the 3 ms value (single peak) of the resultant acceleration of the spine, Aint
being the acceleration intercept value, Dmax being the deflection of the chest, and Dint the
intercept deflection values (Table 24).
97
Table 24. Critical/intercept 3 ms Aint values and the
critical/intercept deflection Dint values to be used in
the calculation of CTI for each dummy type.
Dummy type
Hybrid III, 6 year
Hybrid III, 3 year
CRABI 12 months
Aint [g]
Dint [mm]
85
85
85
70
55
102
83
63
57
49
Energy based injury criterion from a one-dimensional model, similar to that proposed by
Lobdell et al. (1973) [133], was proposed by Wang (1989) [134]. This criterion includes four
different energies that define a non-injurious region in a chest deflection rate vs chest
deflection plot. These four energies are:
1) Stored Energy Criterion (SEC)
For this criterion the energy is proportional to the square of the maximum deflection:
max⁡
(𝐸𝑒 ) ∝ max⁡
(𝑦 2 )
where y is the thoracic deflection and Ee is the stored energy.
2) Energy Storing Rate Criterion (ESRC)
The ESRC value is proportional to the VC:
max
dEe
∝ max(yy)
dt
3) Dissipated Energy Criterion (DEC):
t ymax
y 2 dt
max⁡
(Ev ) ∝
0
4) Energy Dissipating Rate Criterion (EDRC)
The EDRC value is equivalent to the power criterion:
max
dEv
∝ max(y 2 )
dt
Wang showed that VC is related to the peak storing energy rate and not to the viscosity of the
thorax. However, Wang did not propose any critical limits for these energies and there is no
experimental data supporting these findings [134].
Lower Leg
During a frontal impact to the knee, the fractures may appear at the leg situated at the femur
and at the head of the femur, as shown in Figure 83. The response to mechanical isolated as
the femur bone loading, the tibia and fibula was measured by different authors such as
Kitagawa et al. 1998 [135], Cappon et al. 1999 [136], and Crandall et al. 1998 [137]. The tests
consisted of tests in tension and bending and are reported in Table 25 by Levine in 2002
[138].
98
Figure 83. Possible fractures due to impact on knee [Crandall 1995] [139].
Table 25. Threshold value for femur, tibia and fibula [Levine, 2002] [138].
Femur
Tibia
Fibula
Male
Female
Male
Female
Male
Female
Torsion [Nm]
175
136
89
56
9
10
Flexion force [kN]
3.92
2.58
3.36
2.24
0.44
0.30
Moment [Nm]
310
180
207
124
27
17
Axial compression [kN]
7.72
7.11
10.36
7.49
0.60
0.48
Femur Force Compression (FFC) (ECE & EuroNCAP) are the femur injury criteria. It
evaluates the axial force [kN] transmitted in each femur of the dummy and the duration of
action of this compressive force [ms]. The tolerance limits curves are represented in Figure
84.
Figure 84. Tolerance limits for femur force.
The Tibia Index (TI) is an injury criterion for the lower leg area and the limit is fixed to 1.3. It
involves the bending moments around the x-axis and y-axes as well as the axial force of
pressure in the z direction at the top or bottom end of the tibia.
with
-
Mx et My Bending moment [Nm] around the x-axis and y-axis
(Mc)R Critical bending moment
99
-
Fz Axial compression [kN] in z-direction
(Fc)z Critical compression force in z-direction
Table 26 reports the force and moment critical values for several dummies.
Table 26. Forces and moments critical values.
Dummy type
MRc [Nm]
Fzc [kN]
Hybrid III, male 95 %
Hybrid III, male 50 %
Hybrdi III, female 5%
307
225
115
44.2
35.9
22.9
The Tibia Compression Force Criterion (TCFC) is the criterion for the tibia strain and is the
force pressure Fz expressed in kN that is transferred axially to each tibia on the test dummy.
For Hybrid III, male 50%, TVFC limit is fixed to 8kN.
Current Frontal ATDs /Dummies & Criteria Under Discussion or in Preparation
Most of the aforementioned criteria applied with the currently widely used crash test dummy
for frontal crash testing and evaluation of safety restraint systems - the (Hybrid-) HIII. So far,
and already mentioned also in Chapter 4, the HIII is available as 50th percentile male, HIII 5th
percentile female which represents the smallest segment of an adult population and for the
largest population segment the HIII 95th percentile male. A detailed description could be
found, for instance, at www.humaneticsatd.com [140].
All HIII family members are also available as virtual / Finite Element version in the most
relevant codes LS-Dyna, PAM-Crash, Radioss and ABAQUS.
Figure 85. Hybrid III ATD (anthropomorphic test device)
Dummy & corresponding virtual FE model [140].
In most of the current regulations and consumer assessment programs, the following (Table
27) criteria are assessed:
100
Table 27. HIII injury criteria - defined and assessed in
most of the current regulations and consumer test.
The criteria are normally derived from acceleration or force / time history of accelerometers
or force transducers mounted at specific locations or measurement platforms of the ATDs.
In general the above mentioned criteria are a measure of the likelihood of an injury. The
injury risk or danger of injury to humans resulting from crash load is usually correlated with
physical measures as referred to in the text above. This also applies to the virtual (FE-) model
of the HIII dummy and other virtual ATDs.
Along with the current harmonization and update of occupant performance criteria and in line
with the general trend to improve safety for elderly and female occupants (see also Chap. 4),
the following criteria were discussed in several initiatives and dedicated working groups in
recent times.
Especially for the thorax additional and new criteria were discussed and proposed to be
implemented to an injury risk evaluation with HIII and finally the new THOR dummy. Most
of the proposed criteria and related physical measurement were motivated by the necessity to
develop more sensitive and distinctive evaluation metrics for chest deflection. So the analysis
of thoracic trauma has been shown that peak chest deflections and correlated injury do not
always occur at the center of the chest. Also the increasing uptake of advanced restraint
technologies and systems like dual stage frontal air bags, (pre-crash -) pre-tensioners and load
limiters require a more effective instrument to measure non-uniform, asymmetric thorax
loading in terms of implementing evaluation tools for an optimized and systematically
development.
Side Impact
Head
31 side impact tests with ES-2re test dummy, and eight side impact tests with WorldSID test
dummy (all were 50th Percentile male sized) were used to develop BRIC for each dummy.
The critical values of angular velocity and acceleration for the ES-2re dummy were found to
be ωcr = 65.68 rad/s and αcr = 23,063.90 rad/s², R² = 0.70.
The critical values of angular velocity and acceleration for the WorldSID dummy were found
to be ωcr = 153.18 rad/s and αcr = 11,527.92 rad/s², R² = 0.94.
Risk of brain injuries as a function of BRIC for side impacts, for various AIS levels and for
two dummies are provided bellow.
101
Figure 86. Risk of brain injuries as a
function of BRIC for various AIS levels
for WorldSID
Figure 87. Risk of brain injuries as a
function of BRIC for various AIS levels
for ES-2re.
Thorax
The Rib Deflection Criterion (RDC) is the criterion for the deflection of the ribs, expressed in
millimeters [mm], in a side impact collision.
Figure 88. Risk curves for EuroSID dummy (USNCAP).
The Thorax Performance Criterion (THPC) is a criterion for chest strain with side impact.
The two elements of the THPC are the rib deflection criterion (RDC) and the viscous criterion
(VC).
Abdomen / Pelvis
The abdomen is the area of the body which is delimited by the diaphragm and pelvis. The
lumbar vertebrae are not considered part of the abdomen. There are differences of mechanical
behavior and tolerance limits between the upper abdomen and the lower abdomen during an
impact (Eppinger et al. 1982 [142]). These are due to the presence of floating ribs. However,
in case of frontal impact, it appears that the organs positioned directly in front of the spine
have a greater risk of being compressed than the side organs.
102
Figure 89. Organs of abdomen [Sobotta 2010] [117].
The abdominal organs are divided into two groups depending on the density. The liver,
spleen, pancreas and kidneys have a higher density than the stomach, small and large intestine
bladder and uterus.
Due to its complex structure, the location of abdominal injuries depends on the severity and
type of impact as well as the location of vital organs. Organs located in front of the spine are
more likely to be compressed than those on the sides.
Several studies have been performed in lateral and frontal impact. Response were recorded
and used to determine the relationship between force and deflection of the abdomen (Nusholtz
et al. (1998) [143], Cavanaugh (1986) [144], Miller 1989 [145]). However, these tests not
taken into account the non-homogeneity of the area.
APF is the abbreviation for Abdominal Peak Force. This is a criterion for the European side
impact regulations. APF is the maximum side abdominal strain criterion. It is the highest
value of the sum of the three forces [kN] that are measured on the impact side.
with Fy is force in y direction [kN].
Figure 90. Injury risk curve for EuroSID dummy (USNCAP).
PSPF is the abbreviation for Pubic Symphysis Peak Force. It is the criterion for pelvic strain
during side impact and is determined by the maximum strain on the pubic symphysis,
expressed in kN.
103
Figure 91. Injury risk curve for EuroSID dummy (USNCAP).
Rear Impact
Neck injury criteria for rear impact are NIC (rear-end) and Nkm criteria. In addition to these
criteria several dummy measurement limits exist that are used in NCAP-rating programs.
These rating program criteria are listed in Table 28 and will be presented in this section. In
addition, limits used in the Euro-NCAP rating program are listed in Table 29.
Table 28. Criteria used in combination with BioRID II
in rear-end impact testing in various rating programs.
Euro-NCAP
Head Cont. Time
T1 x-acceleration
Upper Neck Fx and Fz
Head Rebound Vel.
NIC
Nkm
J-NCAP
NIC
Upper neck Fx Fz My
Lower neck Fx Fz My
IIHS
Head Cont. Time
Torso acceleration
Upper neck Fx Fz
Table 29. Limits used in rear-end impact testing by Euro-NCAP Medium Severity Pulse.
Criterion*
NIC (m2/s2)
Nkm
Rebound velocity (m/s)
Upper Neck Shear Fx (N)
Upper Neck Tension Fz (N)
T1 acceleration* (g)
T-HRC (ms)
Higher
performance
11.0
0.15
3.2
30
360
9.30
57
Lower performance
Capping Limit
24.0
0.55
4.8
190
750
13.10
82
27.0
0.69
5.2
290
900
15.55
92
NIC - Since over ten years many investigation on new neck injury criteria for rear end impact
have been carried out. Boström et al. (1996) proposed the NIC (Neck injury Criterion) as a
value to correlate the head-neck movement with the risk of ganglia injury caused by transient
pressures changes in spinal canal [141]. It addresses the relative acceleration and velocity
between the head and the torso.
104
The NIC value is calculated with the following formula:
With 𝑎 is the acceleration in X direction of the first thorax spine in [m/s²] and 𝑎
is the
Acceleration in x-direction measured at the height of the c.o.g. of the head [m/s²]. Several
studies have suggested that NIC correlates with the risk of symptoms after a rear-end impact.
A selection of those studies is presented below.
Kullgren et al. (2003) compared the symptom duration of 110 occupants, who had been
involved in rear-end impacts, with parameter values obtained in reconstructions of the impacts
by using a mathematical model of the BioRID II and seats [146]. It was found that the NIC
clearly predicted a neck injury with high accuracy; for both initial symptoms and duration of
more than one month. A general concern and weakness of the study was the use of
mathematical models of seats and a prototype of the BioRID II.
Linder et al. (2004) reconstructed 25 rear-end impacts with known one month duration of
neck injury symptoms [147]. In the reconstructions, the BioRID II was placed in the same
type of seat as in the vehicle struck and the vehicle accelerations were reproduced. The results
of the study provided a link between real-world neck injury symptoms and average dummy
readings. It also provided indications of thresholds for a 10% risk of neck injury symptoms
persisting for more than one month. NIC was one of several parameters that appeared to
predict neck symptoms and was suggested for further studies.
Boström & Kullgren (2007) compared the real-life performance of car seats with BioRID II
test results for Saab, Volvo and Toyota seats, before and after the anti-whiplash systems were
introduced [148]. The authors did not suggest criteria to be used in future seat evaluations.
Nevertheless, their results indicate that there possibly exists a correlation between the NIC
and risk of whiplash symptoms.
Risk of long-term symptoms
1.0
0.8
0.6
0.4
0.2
0.00
5
10
15
20 25 30
NICmax [m²/s²]
35
40
45
Figure 92. NICmax Risk curve for symptoms >1 month [155].
105
Ono et al. (2009) used mathematical modelling to reconstruct volunteer, cadaver experiments
and real life rear-end impact accidents with known initial, short and long term risk of neck
injury symptoms, as well as known crash pulse and seat characteristics [152]. In total 20 cases
were reconstructed for which the velocity change during the rear-end impact ranged from 9
km/h to 28 km/h. The results reveal that displacements between the cervical vertebrae may be
responsible for the persistent neck symptoms following rear-end impacts. The study suggested
adopting several criteria, one of these were the NIC.
Davidsson & Kullgren (2013) calculated real-life injury risk for 17 groups of similar seat
designs from data provided by Folksam [153]. Two types of injury risks were used: those
leading to documented symptoms of more than one month’s duration and those classified as
leading to permanent medical impairment as a consequence of a rear-end impact. These risks
were compared to parameter values from sled tests performed with a BioRID II at 16 km/h
pulses. Regression coefficients were calculated. The study found that NIC best predicted the
risk of developing permanent medical impairment and symptoms of more than one month,
given the occupant had initial symptoms following a rear-end impact.
The first NIC threshold proposed was 15 m²/s². In 2006, Eriksson & Kullgren (2006) used a
MADYMO model of the BioRID II and simulated 79 real accident cases and proposed a NIC
risk curve for symptoms > 1 month [155]. It estimates that a NIC of 24.5 ±10 m²/s²
corresponds to risk of 50 %, as illustrated in Figure 92.
Based on reconstructions of volunteer tests, PMHS experiments and accidents using a HBM,
Ono et al. (2009) developed WAD2+ risk curves for NIC and upper and lower neck loads
[152] (Figure 93). In these risk functions the risk of WAD2+ was shifted towards lower NIC
values as compared to the risk function presented by Eriksson & Kullgren (2006) [155].
Based on these risk functions Ikari et al (2009) suggested limits for the J-NCAP rear-end
impact rating program [156].
Nkm - Schmitt et al. (2002) proposed the Nkm criterion based on the linear combination of
shear force and bending moment at the occipital condyle [157]. Nkm corresponds to the four
criteria defined by the following equation:
N_km (t)=(F_x (t))/F_int +(M_ocy (t))/M_int
With Fz being the force at the point of transition from head to neck. Fint being the critical
force, MOCy being the total Moment (MOC) at the occipital condyles and Mint being the
critical moment (Table 30).
Since both positive and negative shear force and bending moment may be present in a rearend impact four combinations of Nkm values may be present. These are Nfa flexion anterior,
Nea extension anterior, Nfp flexion posterior and Nep extension posterior.
Some studies have suggested that Nkm predicts WAD when measured using the BioRID II
dummy. Kullgren et al. (2003) reconstructed rear-end impacts using a mathematical model of
the BioRID II and the seats. In total 110 occupants with symptoms following a rear-end
impacts was included in the study [146]. The study showed that Nkm predicted a neck injury
with high accuracy. Based on reconstruction of 25 rear-end impacts, using a physical tests
with the BioRID II, Linder et al. (2004) recommended that Nkm should be studied further
[147].
106
Figure 93. WAD2+ risk functions [152].
Dummy type
Table 30. Critical values used in the calculation of Nkm.
Fint [N]
Fint [N]
Mint [Nm]
Positive
Negative
Flexion
shearing
shearing
Mint [Nm]
Extension
845
-845
88.1
-47.5
BioRID II, male 50%
845
-845
88.1
-47.5
107
As for the NICmax, Eriksson & Kullgren (2006) established a Nkm risk curve for symptoms > 1
month [155]. It estimates that a Nkm of 0.5 ±0.3 corresponding to risk of 50%, as illustrated in
Figure 94.
T1 x-acceleration is the maximum
value of the average T1 acceleration
from time of test start to the time of
head to head-restraint contact. No
injury risk function is available for T1
x-acceleration, however studies have
indicate that T1 x-acceleration may
be correlated to the risk of WAD
following
a
rear-end
impact
[147][153].
Risk of long-term symptoms
Head Cont. Time (HCT) is defined as the time it takes form the start of the impact (seat base
acceleration) to the time of head contact time with the head restraint. No injury risk function
is available for HCT. Davidsson & Kullgren (2013) found rather that HCT as measured in the
BioRID II did not correlate with the
risk of developing WAD after a rear1.0
end impact [153].
0.8
0.6
0.4
0.2
0.0
0.0
0.5
1.0
1.5
Nkm
Upper neck loads are included in the
Euro-NCAP and J-NCAP rating Figure 94. Risk curve of symptoms > 1 month [155].
programs. Included in both programs
are the maximum shear force and the maximum tension force in the upper neck from time of
test start to the time of head to head-restraint contact. Positive shear should be indicative of a
head-rearwards motion and positive tension should be associated with pulling the head
upwards. In J-NCAP also the neck moment in extension and in flexion are included. In JNCAP scores are calculated using a sliding scale; the higher and lower performance limits for
both extension and flexion neck motions are 12 and 40 Nm, respectively.
Risk curves for upper neck loads were presented by Ono et al. (2009) [152]; these are
presented in Figure 93. Note that these are based on simulations.
Several studies have matched BioRID II tests data with real life data and found the upper neck
loads to possibly predict symptoms following a rear-end impact [147][148][152] (additional
information on these studies can be found in the section on the NIC).
Lower neck loads are the maximum shear force, the maximum tension force and the
maximum rearward bending moment in the lower neck load transducer in the BioRID II from
time of test start to the time of head to head-restraint contact. Lower neck load limits are
included in the J-NCAP. Risk curves for lower neck loads have been provided by Ono et al.
(2009) [159], see Figure 93. By studying the response of PMHS neck specimens, Stemper et
al. (2007) found that lower neck shear forces correlate with cervical facet joint motions [158].
In a follow up study Stemper et al. (2009) found that lower neck shear forces also correlated
with facet joint ligament strains [159]. Ono et al (2009) found that displacements between the
cervical vertebrae can cause neck injuries/persistent symptoms and defined an inter-vertebral
strain injury [152]. In addition it was found that.
Seatback dynamic deflection is defined as the maximum change in angle achieved at any time
during the test between the sled acceleration starts and the end of head-to-head restraint
contact. For the high severity pulse used in the Euro NCAP rear-end impact test, the seatback
108
deflection should be below a rotation of 32.0° to avoid penalty. No study have shown that seat
back angle change have a negative effect on the risk of WAD, but is considered important to
avoid ejection during sever rear-end impacts and to avoid injuries to second row occupants.
5.1.3 Trends and Future Injury Criteria
Head & Neck
At present the most widely accepted method of assessing head injury risk in road safety
research is the Head Injury Criterion (HIC). This is the tool currently used in safety standards
for head protection systems using headforms (for example for helmet homologation with the
ECER022 standard or for bonnet evaluation with the EuroNCAP Pedestrian Testing
Protocol). However, HIC only considers the injury risk to the head resulting from linear head
accelerations. As such, HIC cannot be used to predict the possibility of head injuries resulting
from head rotation, or distinguish between the different types of head injuries that can occur,
such as skull fractures, subdural haematomas or diffuse axonal injuries. In addition HIC does
not distinguish between the impacts directions when it is well known that lateral impacts are
more aggressive then frontal or occipital ones. It is anticipated that a head injury assessment
method, more advanced than HIC, will lead to the development of improved head protective
systems capable of reducing the incidence of head injury fatalities. A proposed alternative
method for assessing head injury risk is to use a human head Finite Element Model (FEM),
which enable the investigation of the intra-cranial response under real world head impact
conditions. It exists around the world some Head Finite Element Models which have some
tolerance limits to specific injury criteria (SIMon models developed by NHTSA and
Takhounts et al. [110], KTH model developed by Kleiven et al. [149] WSU model developed
by Zhang et al. [150], SUFEHM model developed by Kang et al. [151]). Only SUFEHM
model has criteria for three different injury mechanisms ie skull failure, Diffuse Axonal Injury
DAI and Subdural hematoma. SUFEHM model (Figure 95) has been validated against all
existing data available through the literature and used to reconstruct real world accident cases
in order to define tolerance limits under three codes (Radioss, LS-DYNA and PAM-CRASH).
SKULL
FALX
BRAIN
TENTORIUM
SCALP
CSF
FACIAL
BONE
Figure 95. Strasbourg University Finite Element Head Model (SUFEHM).
After some statistical analysis it appeared that DAI are well correlated with intra-cerebral Von
Mises stress. The threshold for this parameter (for Ls-Dyna code) is of the order of 28 and 53
kPa respectively for moderate and severe neurological injuries as it appears in the injury risk
curves reported in Figure 96.
109
1,0
0,9
0,9
0,8
0,8
Probability (Severe DAI)
Probability (Mild DAI)
1,0
0,7
0,6
0,5
0,4
0,3
0,2
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0,1
0,0
0,0
0
10
20
30
40
50
60
70
0
80
10
Brain Von Mises stress [kPa]
20
30
40
50
60
70
80
Brain Von Mises stress [kPa]
Regression: log(p/(1-p)) = -5.718 + 0.108X where X
is the maximum brain Von Mises Stress
Regression: log(p/(1-p)) = -5.438 + 0.193X
where X is the maximum brain Von Mises Stress
Figure 96. Head injury tolerance curve calculated with SUFEHM model
under LS-Dyna code for DAI injuries.
Concerning Subdural hematoma (SDH) injuries the best correlation was the maximum strain
energy within the CSF, with a R² value of 0.465 and a threshold value of about 4950 mJ. The
injury risk curve is proposed in Figure 97.
1,0
0,9
Probability (SDH)
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0,0
0
2000
4000
6000
8000
10000
CSF Strain Energy [mJ]
Regression: log(p/(1-p)) = -4.931 + 0.001X where X is the CSF strain energy
under LS-Dyna code for SDH injuries.
Finally skull fracture injuries are correlated with the maximum strain energy within the skull
and a threshold value for a 50% risk of injuries of about 544mJ. The injury risk curve is
proposed in Figure 98.
110
PROBABILITY OF SKULL FRACTURE [%]
100
90
80
70
60
50
40
30
20
10
0
0
200 400 600 800 1000 1200 1400 1600 1800 2000
SKULL INTERNAL ENERGY [mJ]
Regression: log(p/(1-p)) = -4.931 + 0.001X where X is the CSF strain energy
under LS-Dyna code for skull fracture injuries.
In order to transfer the proposed head injury prediction tool to potential end users the
methodology illustrated in the following figure which shows a coupled experimental versus
numerical approach is proposed. It is a matter of recording the linear and rotational 3D
acceleration of the headform under impact and to consider these experimental data as the
input for the driving of the head FE model, which in turn will derive the injury risk for DAI,
SDH and skull fracture. Such an approach is possible with Hybrid III head, with the
pedestrian headform or with the helmet standard test headform.
Figure 99. Head Injury prediction Tool.
111
Neck
In this section neck injury criteria that most likely will be included in rating programs and in
legislative testing in the near future are presented. First, injury criteria intended for the use
with dummies in the near future in frontal and rear-end impacts are presented. Thereafter
follows a presentation of the injury criteria candidates to be used with state of the art HBMs in
simulations of impacts.
For sever neck injuries few new criteria for ATDs are expected. However, for prediction of
WAD discussions are still on-going. One reason for this is the lack of suitable models to be
used to study the governing injury mechanism; PMHS have deteriorated properties and
detection of soft tissue injuries is difficult. Volunteers lend them self to study sub injury level;
extrapolating data to higher severities are challenging. Reconstruction of accidents are
hampered by the lack of information on initial occupant posture, e.g. head to head restraint
distances, and the effort it takes to reproduce a sufficient number of accidents.
Numerous studies have focused on WAD and the mechanisms that produce these
injuries/symptoms. A review of all these studies will not fit into this report. Though, Ikari et al
(2009) [156] combined a literature review and results obtained in a reconstruction study by
Ono et al. (2009) [152] . Based on this they recommended injury criteria to be used in the near
future with the BioRID II. They concluded that some injury criteria candidates, e.g. Nkm, LNL
and occipital condyles relative T1 rotation and retraction, could be substituted by neck load
limits (Table 31). Other criteria, such as the rebound velocity, did not correlate to tissue
strains in the neck (Table 31). This reasoning suggested that in the future NIC, upper and
lower neck loads should be assessed.
Table 31. Reasons to include or exclude an injury criteria/parameter [156].
Index of
injury
Correlation with
strain/strain
rate
Forward
Backward
Tension
Compression
Extension
Flexion
Forward
Backward
Tension
Compression
Extension
Flexion
Max
Comments
Overall decision
Marginal
Good
Good
Marginal
Marginal
Good
Marginal
Good
Good
Marginal
Marginal
Good
Good
Min
T1G
Poor
Good
Nkm
LNL
Rebound V
OC-T1
Head-chest rotation angle
Marginal
Good
Good
Good
Good
Correlation coefficient is low, dispersion is large
Correlation of discomfort in volunteer test
Correlation to strain of vertebra, strain rate are high
Simulation output is too small to judge the correlation
Purpose to evaluate control effect of neck upper motion
Correlations with strain of vertebra and strain rate are high
Correlation coefficient is low, dispersion is large
Simulation output is too small to judge the correlation
Purpose to evaluate control effect of neck lower motion
before the contact with head restraint
No correlation
Substituted by NIC (NIC included acceleration of T1, NIC
can evaluate both head G and T1G)
Substituted by upper Fx, My
Substituted by lower Fx, Fz, My
Phase is different of max. strain and strain rate
This is displacement, substituted by lower Fx
This is rotational angle, substituted by lower My
Upper Fx
Upper Fz
Upper My
Lower Fx
Lower Fz
Lower My
NIC
More recently IV-NIC have been studied and found to be predictive of WAD; Ivancic & Sha
(2010) identified that IV-NIC was the only whiplash criterion capable of predicting the
112
intervertebral level, mode, severity, and time of soft tissue neck injuries [160]. Since IV-NIC
is not easily monitored in the existing BioRID they also studied correlations between IV-NIC
and exciting criterions. They observed a correlation between IV-NIC and NIC, Nkm, Nij, and
NDC. Additional studies were reported in the Global Technical Regulation No. 7: Head
Restraints (GTR-HR2) meeting on September 15th 2013 [161] and the results confirm those of
Ivancic & Sha (2010) [160]. Also, these studies concluded that IV-NIC correlate with NIC
and components of NDC and should be measured in future rear-end impact tests.
Moorhouse & Kang (2013a) [162] also suggested that IV-NIC correlated with the risk of neck
injuries, as observed in a rear-end impact with PMHSs [163]. Additional PMHS experiments
that were carried out by the same research group, using standard car seats, confirmed these
observations and injury risk functions were produced. This more recent work was presented in
the GTR-HR2 meeting on September 15th 2013 [164]. The findings supported that IV-NIC
correlated with the risk of dislocation injuries. On-going work is focused on suggestions for
criteria to be measured in rear-end impact tests with the BioRID II. The group also studies the
correlate between the neck loads as measured in the PMHS and the observed injuries.
Table 32 includes a summary of the criteria candidates, intended to be used in future
legislative rear-end impact testing, that were presented in the September 15th 2013 GTR-HR2
meeting [165].
Table 32. Draft injury criterion as discussed by the informal group in the meetings on GTRHR2; proposal from JAPAN - JMLIT/JASIC/JARI with a green background, proposal from
NHTSA with a red background.
1) [166] 2) [167], [159]
The studies by Ono et al. (2009) [152], Ivancic & Sha (2010) [160] and Kang et al. (2012)
[163] were to some degree hampered because they did not correlate BioRID II measurements
directly with real life data or with the injuries that were observed in the PMHSs. Davidsson &
Kullgren (2013) aimed at a direct comparison between BioRID II data and the risk of
symptoms in real life accidents [153]. They matched dummy data with calculated real-life
injury risk for 17 groups of similar seat designs from data provided by Folksam. Two types of
injury risks were used: those leading to documented symptoms of more than one month’s
113
duration and those classified as leading to permanent medical impairment as a consequence of
a rear-end impact. These risks were compared to parameter values from sled tests performed
with a BioRID II at 16 km/h pulses. Regression coefficients were calculated. The study found
that NIC, the maximum rearward Occipital Condyle relative T1 x-displacements and L1 xacceleration best predicted the risk of developing permanent medical impairment and
symptoms of more than one month, given the occupant had initial symptoms following a rearend impact. In conclusion, their study confirmed some of the results obtained in the studies
that were presented in the September 15th 2013 GTR-HR2 meeting.
Criteria for Human Body Models
Concerning the neck aspect, in the last decades a number of neck multi-body and finite
element models were develop with different levels of details in terms of geometry, validation
and mechanical properties. Ono et al. (2009) [152] proposed based on a FE model a new
injury criteria based on the strain and the strain rate of the facet joint. The relationships
between strains and WAD are shown in Figure 100.
Figure 100. Relationships between strains and WAD [152].
In 2004, Meyer et al. [154] proposed a finite element neck model and its original validation
(multidirectional time and frequency domain validation as well as a validation against
vertebrae relative motion) and coupled it in 2012 with the existing Strasbourg University
Finite Element Head Model (SUFEHM).
Based on an existing whiplash accident database including crash pulse recording, the authors
proposed an in-depth investigation of the neck response at tissue level with the objective to
extract pertinent ‘intra-cervical’ parameters presenting high correlation with the occurrence of
114
whiplash injury. The crash pulse acceleration of 86 real life rear-end impact from Folksam
database have been reconstructed [168]. A number of intra cervical local and global
parameters were considered as candidate parameters for neck injury criteria by investigating
the correlation of the different metrics with the occurrence of injury.
Figure 101. Cross section of the Strasbourg University human head–neck system FE model.
Main conclusion of this extensive real-world rear impact accident simulation and statistical
analysis is that none of the existing criteria or more local parameters (such as facet distorsion)
presents an acceptable correlation level. However, when a more global (or cumulative)
parameter is considered, such as the summation of the shearing displacement at each level, an
acceptable regression parameter was observed and it was possible to derive a tentative injury
risk curve for whiplash injury based on this metric (figures below).
1,0
Probability of WAD1
0,9
(a)
0,8
0,7
0,6
0,5
0,4
0,3
Nagelkerke score value
R²=0,223
0,2
0,1
0,0
0
1
2
3
4
5
6
7
8
ABS(C1-C7) [mm]
Figure 102. Risk curves of the injury criteria proposed for the WAD 1 derived from
accident reconstructions with FE head/neck model.
115
1,0
Probability of WAD2
0,9
0,8
R²=0,545
0,7
0,6
(b)
0,5
0,4
0,3
0,2
0,1
0,0
0
1
2
3
4
5
6
7
8
ABS(C1-C7) [mm]
Figure 103. Risk curves of the injury criteria proposed for the WAD 2 derived from accident
reconstructions with FE head/neck model.
1,0
Probability of WAD3
0,9
0,8
0,7
R²=0,842
0,6
(c)
0,5
0,4
0,3
0,2
0,1
0,0
0
1
2
3
4
5
6
7
8
ABS(C1-C7) [mm]
Figure 104. Risk curves of the injury criteria proposed for the WAD 2 derived from accident
reconstructions with FE head/neck model.
Thorax
Rib fractures constitute the most common AIS3+ thorax injury. Commonly soft tissue injuries
occur in the rib fracture zone. These injuries are common among elderly as results of
increased ribcage brittleness and flatter rib angles as compared to young persons. For several
of the developing countries life expectancy is increasing dramatically and the average age of
car occupants will increase. Hence traffic related thorax injuries are expected to grow in
proportions to other traffic related injuries. This change will lead to additional focus on thorax
injuries in the near future and call for the development of new test methods and advanced
thorax injury criteria for the use with Human Body Models (HBM) and dummies. These
introductions are motivated by the necessity to develop a more sensitive and distinctive
116
evaluation metrics for chest deflection. It has been shown that peak chest deflections as
measured in the center of the chest does not always correlate with injury risk. Also the
introduction of advanced restraint technologies, e.g. dual stage frontal air bags, pre-crash pretensioners and load limiters, require a more humanlike crash test dummy and effective
instrument to measure asymmetric thorax loading. Examples of such a dummy and instrument
systems are given below. Thereafter follows a presentation of proposed injury criteria and
related physical measurements for the frontal impact dummies the Hybrid III and the THOR
and the side impact dummy the WorldSID, and HBMs.
The new THOR dummy version, the SAE mod kit and the EU7 THORAX, is now considered
for use in legislative and NCAP testing. Currently its performance and injury assessment
capabilities are evaluated by NHTSA and others. Especially will this dummy allow for the
aforementioned multi-point and asymmetric chest deflection metrics.
Figure 105 shows the current status of the THOR (Test Device for Human Occupant
Restraint) dummy and also its virtual (FE-) version. The table included in the figure provide
an overview of the improved design features in terms of additional measurement compared
with the Hybrid III. Several improvements of the dummy and suggestions for criteria are also
based on the outcome of the EU project THORAX [www.thorax-project.eu - THORAX, FP7
SST.2007.4.1.2, GA No. 218516], SAE work groups and NHTSA. Some of these criteria will
be presented below.
Figure 105. The THOR (Test Device for Human Occupant Restraint) dummy – additional
measurement compared to HIII & new criteria under discussion [169].
117
Thorax Multi-Point and high Rate measurement (THMPR) takes both mutipå point chest
deformations and rate into account and was defined for the use with the Hybrid III but could
also by applied to virtual Human Body Models [170].
Figure 106. Multi chest deflection points (THMPR) for HIII and virtual HBM (THUMS) –
here evaluation of various seat belt and airbag loading condition [170].
Whereas THMPR could be used as a universal measure, the so-called RibEye system was
developed to provide chest deflection at 12 locations just for the use with a Hybrid III
dummy. The RibEye system is based on the insertion of an optically-based measurement
device. In principle the illumination from 12 LED positioned on the inside rib surface or
sternum is captured by two sensors placed on either side of the spine box in the dummy. The
evaluation of the system and its performance is discussed in detail in the NHTSA report
“Evaluation of the Ribeye Deflection Measurement System in the 50th Percentile Hybrid III”
[172].
Figure 107. RibEye - Multi-point differential thorax deflection measurement to evaluate
peak chest deflection / non-symmetric chest deflection - optically-based measurement system
to be used with the HIII 50th dummy [172].
This section that follows includes a presentation of thorax injury criteria candidates for
dummies and for HBMs. First, global criteria for dummies are presented and thereafter
criteria on structural and material level intended for HBMs.
118
Global criteria for frontal impact dummies
Equivalent deflection criterion (DEQ) was developed by Petitjean et al. (2003) [173] and
further improved by Trosseille et al. (2013) [174] and allow for separate risk assessment of
loads from airbags and belt restraint systems. The criterion is based on the principle that the
injury risks associated to a belt and to an airbag are different in terms of chest deflection. The
localized deflection, caused by the belt and evaluated from the shoulder belt force, and a
distributed deflections, evaluated from maximal deflection caused by an airbag, are combined.
This will facilitate that the different risks associated to each restraint are taken into account.
Figure 108. Schematic figure of the Deq [175].
The deflections caused by the belt and air bag are then combined to obtain the equivalent
deflection criterion as follows:
DEQ t =
d2l t + fn d2d (t)
where DEQ is the equivalent deflection criterion; dl is the deflection due to belt loads; dd is
the deflection due to air bag loads; and fn is a normalization factor
For the Hybrid III the reported value for fn was 0.57, the ratio of the chest compression at
50% risk of AIS3+ for belt (41 mm) and air bag (72 mm).
In order to suggest values for fn a number of assumptions hade to be made; these assumptions
and the calculation of fn are arguable. Currently DEQ is not considered for thorax injury
evaluation by any NCAP program or informal working groups.
Differential Deflection Criteria (DC) and DcTHOR. The DC was developed by Song et al.
(2011) for the THOR dummy as part of the THORAX project [176]. It is based on simulations
of 26 PMHS tests in sled, impactor and static air bag test conditions. This criterion combines
the mid sternal chest deflection and the difference between the compression at the 7 th rib level
and in that way account for the asymmetry in chest compression (Figure 109). Such
asymmetric chest compression has been identified as a contributor to skeletal injuries in the
thorax. For the Human Body Model used in the simulations the DC is defined as follows:
DC = Ds + Cf ∗ dD
Lc + dD
Lc
where Ds is the x component of the mid sternum displacement relative to T8; dD is the
differential deflection. Difference between the left and right costochondral joints at the 7th rib
measured as the x component of the displacement relative to L1; Lc is the characteristic
length and was fixed at 24 mm; and Cf is the contribution factor and was fixed at 0.15
As presented previously, the coefficients Lc and Cf were defined for HUMOS2LAB and may
not be the values to be used with other HBMs or ATDs.
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Figure 109. Deformation of the chest in simulated frontal collisions
using a HUMOS2LAB HBM [176].
A criterion tailored for the THORAX demonstrator dummy was developed within the
THORAX project; this new DC criterion was named DcTHOR. he adapted Dc criterion for
the THOR dummy, denoted DcTHOR, is defined as below:
DcTHOR = Dm + dDup + dDlw
Where Dm is the mean deflection of the ribcage, calculated based on the four maximum
deflections measured by the IRTRACCs in the X-axis (Formula 1):
Dm = ( ULX max + ULX max + LLX max + LRX max⁡
)/4
dDup reflects the upper thoracic twisting level (Formula 2). The twisting effect is null if the
upper left-right differential deflection is less than 20 mm, or if the maximum X-deflection on
the one side of the upper thorax does not exceeds 5 mm:
dDup = ULX
URX max
20
dDlw reflects the lower thoracic twisting level (Formula 3). The twisting effect is null if the
lower left-right differential deflection is less than 20 mm, or if the maximum X-deflection on
the one side of the lower thorax does not exceeds 5 mm.
dDlw = LLX
LRX max
20
ULX, URX, LLX and LRX are the IRTRACC X-component time histories with respect to the
local coordinate system.
Davidsson et al. (2013) showed that the Dc THOR, an average of DC for upper and lower
measurement points in the dummy, predict injury in sled, out-of-position and impactor tests
[177]. An example of a DcTHOR risk function that was developed to assesses the risk of five
fractured ribs or more are included in Figure 110.
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Figure 110. Injury risk functions for the THORAX demonstrator;
Dmax to the left and DcTHOR to the right [177].
Maximum deflection of five locations (Dmax) is based on the combined thoracic index; using
the normalized maximum deflection among the five locations on the thorax (Figure 110)
instead of the maximum mid sternum deflection, improved the injury predictions of CTI.
Davidsson et al (2013) developed injury risk curves for Dmax for four locations by combining
PMHS injury data and THORAX demonstrator test data from reproductions of these PMHS
tests [177]. Their injury risk quality assessment suggested that Dmax can be an effective
measure of rib fracture risk. An example of a Dmax risk function that was developed to
assesses the risk of five fractured ribs or more are included in Figure 110.
Number of Fractured Ribs (NFR) for THOR was developed with the THORAX project. For
this six pairs of ribs in the THORAX demonstrator was fitted strain gauges on the exterior
side and an onboard measurement system to record strains in these ribs. Figure 111 illustrates
the method used in the development of the NFR criterion; the method to transfer the recorded
strain values to NFR and determine the strain threshold to be used. NFR risk curves were
developed using matched PMHS and dummy test data. Risk curves were developed (Figure
111) and the assessment of the risk curve quality indicated that additional work remain before
rib strain measurements in the THOR dummy can be used for rib fracture prediction [177].
NFR (PMHS)
Determining εthreshold to obtain the best regression
NFR(ε)=f(ε ≥ εthreshold)
NFR (dummy)
Figure 111. Method used in the THORAX project to transfer rib strain
to NFR and sample injury risk curve based on NFR.
Principle Component Analysis (PCA) is currently being developed by University of Virginia
and has the similar structure as DcTHOR. While DcTHOR takes the average of DC for upper
and lower measurement points in the THORAX demonstrator dummy, the PCA takes scaled
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deflections of the upper and lower chest and the differential deflections of the upper and lower
chest according to the following principal equation:
PCA = C1 ∗ Uppertot + C2 ∗ UppeDriffMax + C3 ∗ Lowertot + C4 ∗ LowerDiffMax + C5
The PCA is based on sled test data only whereas DcTHOR was developed using sled, out-ofposition and chest impactor tests data. The PCA criterion also takes costo-cartilage fractures
whereas these had to be omitted in the development of the DcTHOR. The PCA injury risk
function assesses the risk of three fractured ribs or more.
Structural criteria and material level criteria for Human Body Models:
When crash test dummies are used to represent humans in impact tests, or when virtual crash
models of test dummies are used in mathematical simulations of impacts, global injury criteria
are used. In HBMs, that are becoming more frequently used in the development of advanced
restraints, the local effect on an organ and the effect on tissue level can be studied in
simulated impacts. Special injury criteria that assess the risk of injury at organ level and tissue
level have been developed and are commonly referred to as structural injury criteria and tissue
criteria. In general it is considered that a structural criterion is in less model dependent than
tissue criteria. A review of these criteria, first the structural criteria and thereafter the tissue
criteria, are presented below.
End-to-end displacement (Df) was proposed by Kindig (2009) for experiments with single
ribs in anteroposterior bending [178]. It was shown that the criterion performed better than the
criteria force, work to failure and bending moment. The end to end displacement is defined as:
Df =
D(t)
D0
where D(t) is the distance between the anterior and the posterior end of the rib and D0 is the
initial distance between the anterior and the posterior end of the rib.
The Df criterion performed best in antero-posterior bending tests on ribs performed by Kindig
[178]. There is no information about its performance in full body tests, where the rib may also
show shear and torsion.
Energy criteria, e.g. Rupture energy (W) defined by Charpail et al. (2005) [179] and Work to
fracture (W) defined by Kindig (2009) [178], defines methods to calculate energy transfer do
individual ribs and the energy it takes to rupture or fracture a rib. The W-criterions calculates
the elastic energy that a rib has absorbed; it does not take into account the distribution of
energy along the rib length. A rib where the deformation energy is localized is more likely to
fracture than a rib where the energy is more evenly distributed along the rib. In addition, the
stiffness calculation requires a force-rib deflection plot; to compute this force-rib deflection in
a full body test is not trivial, since in a full body test the forces could be applied at any point
and likely onto a substantial length of the rib. Further, these criteria only include the anteroposterior forces and several other forces may contribute to the local strain that causes the rib
fracture. Internal energy of each rib is possibly more power for assessment of a rib fracture
than other energy based criteria. This energy accounts for all loads that have deformed the rib.
Force (Ff) that contributes to the anteroposterior bending of the rib has been suggested
suitable as a rib fracture criteria by Charpail et al. (2005) [179] and by Kindig (2009) [178].
However, several other forces may deform the ribs of an occupant in a car crash; hence this
force may not be enough in a full body test where other loads exist.
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Moment (Mf) was studied by Kindig (2009) [178] and was calculated as the sum of moments
measured at the rib end support and the moment generated by the resultant force with respect
to the point of fracture. This criterion requires additional updates as this criterion the moment
is calculated at the location of the fracture; which is unknown in HBM simulations.
Rotation of ends of the ribs was suggested by Charpail et al. (2005) [179]. It was found in
tests with rib specimens that this value was similar for all experiments at the time of fracture.
Change in curvature has been considered [176] as an alternative criteria candidate to the
strain along the rib axis. This curvature could be calculated in HBMs on the rib plane or in
space.
Several initiatives and publications discussed the capability of finite element HBMs to predict
rib fractures, using material level criteria that occur under different loading conditions over
the past years. Most of the authors propose a strain-based method to predict a (local) rib
fracture risk (see below). Needless to say, that in a first step the mechanical properties and
behaviour of the ribs and chest have to be modeled and validated in detail. Several studies are
currently addressing other measures of stress and strain to improve the rib fracture
predictability of finite element HBMs.
Plastic strain in the rib cortical bone was introduced in THUMS to erode rib cortical bone
elements [180]. It could be argued that plastic strain is not always present prior to a fracture;
plastic strain is present to some degree in cortical bone tissue samples from younger subjects
prior to fracture but commonly not in samples from older subjects.
A plastic strain criteria was also implemented in the HUMOS2 which was developed in the
Aprosys project. Damage was associated with ultimate strain. It was found that distribution of
high stresses and damaged elements in the ribcage correlated well with fractures seen from
PMHS tests.
Figure 112. (left) Plastic strain damage model – A > yield strain, B > damage initiation, C
>complete damage; (right) Fracture distribution in ribcage model [181].
Number of Fractured Ribs (NFR) was reported by Song et al. (2011) [176]. A rib is
considered fractured when the plastic strain as predicted in a HBM (in this case the
HUMOS2LAB model) was considered fractured when a pair of shell elements on the inside
and outside of a rib reached a certain value (this value was set to 1.8 and 2.4% to represent a
fragile and a strong person).
Max principal stress, Rankine is commonly used to predict failure of brittle materials. Failure
occurs when the maximum principal stress in the cortical bone of ribs reaches the uniaxial
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tension or compression strengths. No value has been suggested for HBMs and is expected to
be model dependent.
Von Mises stress in the ribs was adopted for the prediction of rib fractures in the HUMOS2
HBM, step 1, which was developed in the APROSYS subproject 5 (Deliverable 5.3.3 &
5.3.4). Figure 113 shows the result of a HUMOS2 simulation compared to a PMHS sled test
(3-point safety belt).
Figure 113. (left) Von Misses stress at 60 ms /40 km/h sled test and (mid) rib fracture
predicted by the model – (right) rib fractures seen in PMHS test [181].
Maximum principal strain criterion is applied to the failure of brittle [182]. Failure occurs
when the maximum principal strain in the cortical bone of a rib reaches the yield strain value.
No value has been suggested for HBMs and is expected to be model dependent.
Strain parallel to the rib. In several experiments with PMHSs the strain parallel to the rib axis
has been measured and used as an indicator of fracture since these strain measurements drop
at the moment of fracture [179][183][185][178]. In some cases, the strain parallel to the rib
axis was similar to the principal strain but in some others it was not [184][183]. An attempt to
use strain parallel to the rib in a dummy, the THORAX demonstrator, to predict rib fractures
was presented in Davidsson et al. (2013) [177].
Abdomen / Pelvis
One of the main mechanisms which cause abdominal injuries was identified with
submarining. Due the fact, that “submarining” loading arising typically when lap belt rides
above the iliac crest, meanwhile several countermeasures like (active) seat ramps, belt
pretensioners and adapted belt geometry are established in the vehicle fleet to avoid this
mechanism. Current dummies (e.g. THOR) also offer the possibility to measure relevant loads
in this area (Figure 114).
Nevertheless, a metrics and injury risk in correlation with lap belt forces or pelvis kinematics
is still under discussion. Beck et al. [186] reported on investigations to define an objective
measures for determining submarining and abdominal Injury in HIII dummies. The authors
finally suggested further research to get better understanding of the submarining mechanism.
Further also the steering wheel and/or an airbag could cause abdominal injuries. Current
literature and latest research in this field suggest to distinguish also between the abdominal
regions when discussing and defining injury criteria and load limits due to the fact, that
different abdominal structures respectively organs with different mechanical properties and
injury mechanisms are loaded.
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Figure 114. Sensor device in current THOR dummy to measure lap belt force – dummy an
related FE-model [169].
Latest research and relevant studies were compiled and can be found in APROSYS SP5
“Final report for the work on “Biomechanics [187].
Exemplarily for the THOR dummy biomechanical response requirements for the abdominal
region are defined and published in the GESAC report GESAC-05-03 [188]. The related
validation tests are illustrated in the figure (Figure 115) below.
Figure 115. Biofidelity evaluation of current THOR dummy – abdominal [189].
Although this dummy will allow additional measurement still the discussion concerning
new/additional criteria is ongoing. Several initiative and publications suggest that abdominal
injury depend on maximal compression and maximum impact velocity (compare also VCViscous Criteria, Chapt. 5.1.2.1 - thorax). The authors of APROSYS SP5 Final Report also
summarizing that good correlation to the injury severity was obtained when calculating the
product of the maximum impact velocity and the maximum abdominal compression. For very
low loading velocities (seat belt loading), the maximum compression was a better predictor of
abdominal injury.
Finally this discussion could be as well summarized with the intention to define more global
or integral criteria to be used with a (specific) dummy /ATD.
Similar to the above-mentioned method to evaluate local thorax injury risk, meanwhile
numerical HBM also have the capability to predict injuries of internal abdominal organs. It
has to be stated that, of course, the characterization of material properties with the
development of constitutive laws and related numerical modeling is also still ongoing in this
area. Nevertheless, for some of the organs in the lower abdomen (liver, kidney, spleen) local
or damage criteria can be defined. This is mainly related with tissue failure and the same
approach as formulated above for injury prediction in the thorax region can be applied.
The next figures (Figure 116) give an overview of the current status of the GHBMC model
and its reported capability to predict local injury risk or damage for several internal organs.
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Figure 116. Capability in predicting crash induced injury with current GHBMC 50% model
– abdomen region [190].
Three papers concerning material characterization and estimation of strain threshold for liver
and/or kidney were recently published at IRCOBI 2013.
Umale et al (2013) [191] reported on the development of a robust finite element model of the
liver and kidney and the capability of the models to reproduce injuries of the organs to a great
extent in terms of acceleration and peak force of the impactor as well as lacerations sustained
by the organ during the experiments. Finally the authors state, that the models can be
integrated with HBM to predict corresponding injuries.
Sato et al. (2013) [192] also presented similar work with a FE- liver model with hyperviscoelastic material properties. Ultimate strains for hepatic parenchyma and membrane were
estimated by comparing strain patterns of the FE model with damaged conditions of tested
livers.
Untaroiu et al. (2013) [193] shown results of 18 tension test on fresh human samples of liver
parenchyma at four loading rates to optimize these FE–models of the organs to be
implemented in complete HBM to better understand liver injury mechanism during vehicle
collision.
Figure 117 illustrates, as an example, findings and simulation results of the work done by
Sato et al. (2013).
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Figure 117. (top) Liver damage obtained from the experiments – (bottom) True strain
distribution of liver membrane at maximum compression ratio [192].
Lower extremities / Tibia / Knee
As already described under 5.1.1.2 and 5.1.2.1 two main injury mechanisms and affected
tissues are relevant for the lower extremities. On the one hand fracture of long bones (Tibia
& Femur) results from bending, relevant for pedestrian and occupant load cases, and
compression loading, mainly relevant occupant load cases, in a crash event. On the other
hand, knee ligament rupture is mainly linked with the pedestrian load case.
For long bone compression and bending criteria and thresholds are already defined for the use
with ATDs. It could be stated, that due to the “technical” nature (in terms of load bearing
structure) of the lower extremities the correlation of these physical parameters defined for
ATDs and observed injury risk on humans /human specimen are quite robust – in contrast, for
instance, to the injury mechanism of ribs.
Nevertheless, the loading of the lower extremities is highly influenced by the total kinematics
of the entire body and contact of these body parts to e.g. instrument panel (occ.) or the car
front (ped.). Updates of related components in latest ATD development (e.g. THOR) enhance
biofidelic behavior in this specific area.
To improve validity and biofidelity was also the motivation to develop the Flex PLI, which
will now be used in most of the protocols to assess the injury risk for the lower extremities in
pedestrian accident. The technical representation of the ligaments and criteria are close to the
anatomic structures and injury mechanisms. The Flex PLI and especially its numerical FE
model and related validation are described in the IMVITER Deliverable 6.1 [194].
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Figure 118. Illustration of current Flex PLI impactor and FE model (Flex PLI GTR V2.0) 1
[194].
Numerical HBM will, of course, also allow the prediction of these injuries in a similar way as
already discussed for the other body regions above.
For the long bones respectively skeletal structures strain-based method to predict a fracture
risk are proposed be several authors. Also the implementation of a damage model is feasible
as it was discussed for rib failure under 5.1.3.2. It should be mentioned, that the kinematics of
a complete impact simulation of a pedestrian accident could be influenced by the use of
damage respectively realistic representation of a fracture. This aspect will be further discussed
in the course of this project.
Next figure shows an example of bending and failure of long bones with damage modeling /
deletion of elements.
Figure 119. Left – Example for three point bending simulation of humerus – Right –
Example for simulation of injury mechanism and fracture of femur due to knee bolster impact
[195].
A direct comparison and correlation of injury predictors for lower limb injury assessment was
reported by Takahasi et al. (2012) [196]. The authors investigated and compared injury
prediction capability and validity of two impactor legforms and a numerical human body
model. Correlation analysis between the peak von Mises stress and the tibia fracture measures
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at the time of peak von Mises stress using the human FE model showed that the bending
moment of the tibia best correlates with the stress.
Figure 120. Comparison of injury prediction of numerical HBM and impactor (here
FlexPLI) [196].
Main knee ligaments are also modelled in most of the published and used numerical HBM.
Figure 121. Left - Knee area HBM Honda [Takahashi Y et al.; IRCOBI 2012 – Right – Knee
area HBM H-LE model [195].
In contrast to bone material most of the publications in this field report, of course, on different
material models and constitutive laws for ligaments. In general ligaments are fibrous materials
with pronounced non-linear force-displacement response. Especially the sensitivity of
ligament tissue failure to strain rate motivates a more complex failure predictor or damage
model.
Similar to the ongoing research to describe injury risk and damage for inner organs and other
soft tissue, it could be stated that also modelling of ligament failure and related injury risk
prediction is still under discussion. Finally it should be stated, that “injury” could be defined
also for a ligament, which only suffered partial tear - so still the traumatic mechanism and
injury patterns has to be understood in detail.
Two IRCOBI papers should be exemplarily mentioned, which reported on ligament failure
investigation and the use of strain and strain rate as injury predictor. Meyer et al. (2012)
reported on the determination of ligament strain during high ankle sprains due to excessive
external foot rotation in sports [171]. The objective of the study was to integrate in vitro and
in vivo experiments along with computational models based on rigid bone surfaces and
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deformable ligaments of the ankle to investigate the external foot rotation injury mechanism
with different shoe constraints and ankle positioning. Bonner et al. (2013) [197] investigated
the sensitivity of material properties of the lateral collateral ligament of the porcine stifle joint
to strain rate and confirmed the aforementioned strain rate dependency of ligament tissue
respectively its material properties.
Use of strain-based methods or damage modelling to predict ligament injuries with the use of
numerical HBM should also be further discussed in the dedicated pedestrian accident subtasks
of this project – based on latest research results on the one hand and effect of these (failure)
modelling technics on total respectively full body kinematics and/or other assessment criteria
on the other hand.
5.1.4 Discussion and Conclusion
As already mentioned in Chapter 4 a general trend towards improved protection of female
and/or elderly population can be identified in dedicated research and discussions concerning
assessment protocols, legislation etc.
This is reflected in the (technical) upgrades of currently used ATDs and new dummy
developments. Especially a more sensitive thorax and abdominal region is now realised with
new structures and new measurement. Following the discussion and related research
concerning a definition of new injury predictors it could be stated, that criteria sensitive to
restraint system loading in terms of capability to distinguish between airbag and belt caused
injury risk are in focus. The Combined Deflection (Dc) and Number of Fractured Ribs (NFR)
are candidates here.
Nevertheless, also these criteria are in principle injury risk predictors which are used with
ATDs and which can be defined as “global” respectively where normally an injury pattern of
a body region is correlated with measurable dummy values.
This also applies for the numerical (FE) version of ATDs and/or impactors.
Here numerical Human Body Models, which are represent bone, flesh, soft tissue and finally
anatomically correct structures like organs instead of “rubber and steel surrogates” as ATDs
stand for, might offer injury prediction in the sense of direct evaluation of biological damage
to human structures and tissues in the future.
Of course, and this is discussed and further developed in several initiatives and research
activities for over 20 years now (if just numerical HBM related activities might be reviewed),
such an injury prediction capability is intrinsically linked with the modelling quality and valid
representation of respective material properties and characteristics. Some examples and latest
result on this subject is given above with the characterization and modelling of failure and/or
damage of inner organs.
In contrast to the application of ATDs and related criteria, accordant definitions in terms of
“criteria”, or better local injury predictors and finally thresholds are currently not broadly
agreed and accepted for HBM. For skeletal structures (e.g. ribs, long bones) it could be stated,
that a strain-based analysis to predict such an injury risk or mechanism (fracture) are proposed
as method of choice by most of the authors. Modelling of damage has to be taken into
account, if further injury mechanisms, which might be related with a continued occupant or
pedestrian motion sequence in an impact, are also in focus.
Also for the head respectively the evaluation of a complex head injury risk it could be stated
that the discussions concerning appropriate and valid criteria are at an advanced stage with the
use of HBM/FE head models.
130
Research to define respective methods and investigate structural response in other body
regions and human tissue like e.g. inner organs or ligaments is still ongoing.
Within the course of this project it will be, of course, not possible to continue this
biomechanical research or further improve the validity of the numerical HBM which will be
applied now in the following work packages.
Nevertheless and in contrary, the current research results and the, so far, proposed methods
and post processing to predict injury risk will be further discussed in the related subtask to
propose and recommend finally their appropriate use within the projected development of a
new assessment framework for SEVs.
5.2 Compatibility
As described in chapter 4.3.1 front crash compatibility assessment has to focus on different
issues of self and partner protection in vehicle to vehicle crash situations. Therefore also
performance evaluation criteria can be divided into assessment criteria for self-protection and
assessment criteria for partner protection. While self-protection assessment mainly focuses on
occupant injury prediction and evaluation, partner protection assessment deals with structural
performance aspects of the vehicle itself.
Chapter 5.2.1 presents current criteria that are applicable for compatibility assessment while
most important assessment trends from recent research programs are the subject of chapter
5.2.2. Compatibility criteria that are suitable for future vehicle to vehicle front crash situations
involving small electric vehicles are presented in chapter 5.2.3 and finally discussed within
chapter 5.2.4.
5.2.1 Current criteria
Current front crash performance assessment only focuses on issues of self-protection. These
assessments include the evaluations of expected occupant injuries resulting from the
interaction of the occupant with the vehicle structure and the restraint systems. A broad
presentation of the different injury evaluation criteria currently in use is given in chapter 5.1.
A partner protection criterion based on the evaluation of the structural design of vehicle front
ends is introduced by the US voluntary commitment for the improvement of the geometric
frontal impact compatibility of light trucks and vans (LTV). The design based criterion
defined by the voluntary commitment prescribes standards for the vertical alignment of
LTVs’ front end structures to reduce the occurrence of override situations in LTV to
passenger car front crashes. According to the voluntary commitment the primary and
secondary energy absorbing structures in LTVs front ends have to show a defined overlap
with the given “part 581 zone” vertically covering the space from 406 to 508 mm (16 to
20 inch) measured from the ground (Figure 122) [198].
Figure 122. Scheme illustrating the part 581 zone overlap requirements [54].
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5.2.2 Most important trends
Development trends for the evaluation of occupant injury in front crash cases as part of the
self-protection issues in compatibility assessment are the same for all front crash test
situations. These are on the one hand based on occupant dummy response to crash loading, on
the other hand focussing on an analysis of the deformation and deceleration behaviour of the
vehicle structure. A detailed description of the different trends is given in chapter 5.1.
EU project FIMCAR (frontal impact and compatibility assessment research) proposes
evaluation metrics to all investigated compatibility test configurations (Chapter 4.3.2)
focussing on an assessment of self-protection and form compatibility [51].
For the test configurations with full width impact FIMCAR recommends an assessment based
on the load cell wall (LCW) contact force response registered for each LCW cell (Figure
123). [54]
Figure 123. Load cell wall dimensions [54]).
For the full width deformable barrier (FWDB) test, where the LCW is placed behind the
deformable barrier layers, minimum total force levels Fi per LCW row i are defined (Table
33). This definition delivers a form compatibility metric for vertical load spreading according
to a ‘pass/fail’ evaluation logic.
Table 33. Vertical load spreading assessment metric for FWDB test [54].
FWDB assessment metric
For t < 40 ms:
MAX [(F3 + F4)(t)] ≥ [MIN (200 kN, 0.4 * FT40)]
MAX [F4(t)] ≥ [MIN (100 kN, 0.2 * FT40)]
MAX [F3(t)] ≥ [MIN ((100 kN – LR), (0.2 * FT40 – LR))]
with limit reducer LR = MAX [F2(t)] – 70 kN and 0 kN ≤ LR ≤ 50 kN
FT40 = MAX [Total LCW force FTot(t)]
and Fi(t) as force sum over LCW row i.
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For the full width rigid barrier (FWRB) test, where the assessed vehicle directly contacts the
LCW, different metrics on vertical load spreading are discussed in FIMCAR. None of them is
fully validated due to remaining issues concerning the possible influence of stiff front package
components contacting the LCW at an early stage of the crash, therefore falsifying a structural
response evaluation. [54]
For the offset front crash constellation FIMCAR examines the possibility of assessing the
barrier face deformation shape of a progressive deformable barrier (PDB) at the end of the
crash test (Figure 124). Different metrics based on the homogeneity of the barrier face
deformation in horizontal direction within the part 581 zone are discussed. The most
promising metric is based on the vehicle mass independent DDY (Digital Derivative in Y
direction) criterion which is calculated from the barrier face’s slope in lateral direction
promoting flat slopes resulting from good horizontal load spreading and penalising high
slopes such as those occurring at the edges of holes in the barrier face. FIMCAR does not
recommend the PDB test procedure as offset compatibility front crash test set-up, as the
analysed metric still shows issues on practicability and reliability. [56]
As in the FIMCAR project the progressive deformable barrier is also used for the mobile
progressive deformable barrier (MPDB) test set-up, the same PDB evaluation metric based on
barrier face deformation analysis can be applied [58].
Figure 124. Digitalisation and evaluation example for barrier face deformation [58].
German automobile club ADAC (Allgemeiner Deutscher Automobil-Club) proposes a
different assessment method for the barrier face deformation of the MPDB in the ADAC
compatibility test. This assessment does not distinguish between deformation homogeneity in
vertical and horizontal direction but evaluates the global barrier face displacement in crash
direction (X). The resulting homogeneity criterion measures the area where the Xdisplacement reaches at least 75 % of the maximum displacement detected. The larger the
resulting area is the better the form compatibility rating. In addition ADAC proposes to access
the velocity change of the mobile barrier trolley (Δv), with low Δv resulting in a good
compatibility rating. [61]
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5.2.3 Criteria for future test conditions
The compatibility criteria related to the compatibility tests proposed by the FIMCAR project –
ODB and FWDB test - are identified as generally suitable also for SEV examples [199].
Nevertheless criteria quantifying compatibility priorities defined for SEVs and their
conventional crash partners for the SafeEV project ( Table 5) are not addressed by these tests,
as the FIMCAR project was only focusing on compatibility issues for conventional M1
vehicles [54].
Although discussed, FIMCAR didn’t integrate a force compatibility assessment criterion into
the final metric proposal [54]. In the same way, the homogeneity criterion defined by ADAC
for the PDB face does not include upper deformation limits. The adaptation of conventional
vehicle’s front end deformation force to SEV requirements is defined as compatibility priority
for the SafeEV project (Table 5), therefore criteria for future test conditions have to
incorporate this aspect.
Relying on existing evaluation criteria on load spreading using the LCW force response for
full width tests or analysing the barrier face deformation for offset tests using the PDB, the
requirement of front end force adaptation can be integrated. Upper limits for LCW force or
PDB face deformation (Figure 125) have to be defined, that suite the front end force
requirements of SEVs.
Figure 125. Metric for load path detection on PDB face assessing longitudinal deformation
[50].
5.2.4 Discussion and conclusions
The only currently applied compatibility evaluation criteria defined within the US voluntary
commitment for the improvement of the geometric frontal impact compatibility of light trucks
and vans is a design based assessment criterion. This sort of compatibility assessment
approach is identified as insufficient for the evaluation of future SEVs as their front end
structural design often has to follow imperatives resulting from package restrictions or similar
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making the fulfilment of such criteria impossible. Studies on vehicles belonging to the
Japanese vehicle class of K-cars –which according to their low weight and unconventional
shape can be compared to future SEVs- show that sufficient structural interaction with a crash
partner can even be achieved without direct loading of the front structure, leading the load
path through the front package [200]. Therefore future compatibility criteria have to be
performance and not design based to assure a freedom of design so that the structural design
of SEVs can be realised with respect to boundary conditions of higher priority.
With the compatibility evaluation criteria defined within the FIMCAR project for the FWDB
and the ODB test the SafeEV project disposes of validated criteria generally identified as
suitable for the assessment of SEVs with regard to their specific low weight.
Further investigations on possible additions to the proposed and discussed criteria also for the
PDB will be finalised for the project report on final test configurations and evaluation criteria
due at the end of the project Work Package 3.
5.3 Fire, Electric Safety etc. incl. Criteria
With the electrification of the propulsion system, additional hazards might occur in case of a
crash, e.g. due to the integration of high voltages or the usage of hazardous materials. In order
to analyse the associated risks and the possibility to include these in a virtual evaluation
procedure, possible additional hazards are addressed in the following chapter. These hazards
are described and classified as well as virtual tools for their evaluation are summarized.
Subsequently, current valid legislative regulations relevant for the evaluation of the crash
safety of Electric Vehicles are assessed in chapter 5.3.1. Important trends of the accident
analysis conducted in WP1 and relevant research projects are summarized in chapter 5.3.2. In
chapter 5.3.3 a hybrid test procedure for the evaluation of these hazards is described and in
chapter 5.3.4 the results of this subchapter are discussed.
In case of a crash of an Electric Vehicle (EV), several critical components of the electric
propulsion system might be damaged, including e.g. the battery cell, the battery pack, the
cooling system or the pressure release valve. A damage of these components can lead to a
hazardous reaction as shown in Figure 126. All of these hazards mainly show an injury risk
for the vehicle occupants or rescue teams. Additional risks for pedestrians, if hit by an EV,
could not be found.
Possible Damage
Resulting Hazard
Mechanical Cell Deformation
Electrolyte Leakage, Internal Cell
Short Circuits Resulting in Ignition
Mechanical Damage to Battery
Pack or Wiring
Short Circuits; Chemical Reactions
Resulting in Overheating and Fire
Damage to Cooling System
Cooling Leakage, Short Circuits
Resulting in Temperature Rise
Damage to Pressure Release Valve
Valve Failure Resulting in
Uncontrolled Explosion
Electric Arcs from Short Circuits of
Electric Conductors or Boards
Ignition, Fire (spontaneously)
Relevant For
Occupant
Safety
Rescue
Safety
Figure 126. Possible hazards of traction batteries in Battery Electric Vehicles [204][206].
135
The hazards described in Figure 126 can be classified according to Figure 127 in chemical
hazards, electrical hazards and thermal hazards. This classification and the resulting injuries
are well explained in MATISSE deliverable D1.2 [201]. Besides these, a mechanical hazard
might also occur. If in a crash the body attachment of the battery fails and the battery intrudes
in the passenger compartment, the high inertia forces of the heavy battery can result in
contusion or bone fracture. With the injury criteria being included in current Human Body
Models, as described in chapter 5.1, it is not possible to evaluate the injuries resulting from
chemical, electrical or thermal hazards, while mechanical hazards might be evaluated.
Hazard
Resulting Injuries
Classification
Source
Chemical
Hazards
E.g. Chemical Burns (see pictures),
Respiratory Tract Irritations, Destruction
of Mucuos Membranes, Unconsciousness
[207]
[208]
[201]
Electrical
Hazards
E.g. Electric Currents Passing Through Body
Resulting in Damage to Internal Organs or
Soft Tissue; Burns and Interactions of
Electric Arcs or Secondary Accidents
[209]
[201]
Thermal
Hazards
E.g. Thermal Runaway of Battery Pack Resulting
in Burns of Soft Tissue or Thermal Injuries
such as Erythema
[201]
Mechanical
Hazards
Contusion or Fracture based on high inertia
forces of the heavy battery pack
[201]
Figure 127. Possible injuries resulting from batteries or High-Voltage Systems in EV.
If these chemical, electrical or thermal hazards should be included in a virtual testing
procedure, not only the used Human Body Models must be able to evaluate them, also the
simulation model of the electric components itself must be able to reproduce these hazards. In
Figure 128 some exemplary simulation approaches showing the current research status for
modelling traction batteries are described. While the first three approaches shown in Figure
128 might already be included in a Finite-Element-Model of a full vehicle used for analysing
crash load cases, the last two approaches are more abstract models, which are not intended to
be included in a vehicle crash model at the moment.
Explicit Finite Element simulations, which are primarily used for a virtual analysis of a full
vehicle crash, intend to calculate occurring deformation and stresses in the vehicle structure
for evaluating structural deformations and decelerations. Short circuits, exothermal chemical
reactions or the leakage of cooling liquid cannot be modelled with this simulation method.
Thus, the microscopic model of the pouch cell or the FE model of the cylindrical cell,
described in Figure 128 primarily evaluate the appearing loads of the battery. By comparing
these loads with experimental data, short circuits or leakage could be predicted. In the
Physical Cell Simulation Model of [202], the level of modelled details is highly increased.
With this Finite Volume approach even the charging and discharging event including the
136
movement of the Lithium-Ions in the battery cell could be modelled. Due to the high detail
level and the small element lengths, this approach could currently not be included in full
vehicle crash models with a reasonable calculation effort. Also the integration of the
Continuous Fluid Dynamics (CFD) Model of [203] in a full vehicle crash model does not
make sense, since this model primarily aims to predict and analyse the thermal effects during
an oven test. A reasonable deformation characteristic is not included in this model.
Simulation Model
Basic Explanation
Microscopic Model of
Pouch Cell (AVL/TU
Graz/Audi )
Prediction of short circuit
and leakage based on
mechanical loading
FE Model of Cylindrical Investigation of jelly roll
deformation mechanisms
Cell and Module
(Virtual Vehicle)
and relevant failure models
Vent Gas Generation
Model (Virtual Vehicle)
CFD-FE-Coupling for modeling gas
generation in case of cell failure
Physical Cell
Simulation Model
(Fraunhofer ITWM)
Prediction of cell behaviour on
micro- and cell-level based on
physical material parameters
CFD Model of Pouch
and Cylindrical Cells
Prediction of thermal short
circuits and thermal runaways
during oven test
Cathode
Status
Source
Research
[210]
Research
[206]
Research
[206]
Research
[202]
Research
[203]
Anode
Figure 128. Simulation models of traction batteries.
5.3.1 Relevant current regulation(s)
An overview of current valid regulations for crash safety of Battery Electric Vehicles (BEV)
is shown in Figure 129. All of these requirements only consist of an experimental evaluation
procedure, focusing on frontal, side and rear impacts. More detailed information can either be
found in the corresponding regulations or in deliverable D1.2 of MATISSE [201]. A virtual
assessment is not considered. Possible reasons might be the limited knowledge of or the
experience with the crash safety of BEV and the lack of suitable simulation models as shown
in chapter 5.3.1.
5.3.2 Most important trends from WP1, regulations, EuroNCAP etc..
From WP1 no specific results showing an increase in the injury risk due to the described
additional safety hazards could be derived. Of course the changes in impact speed in the
different impact conditions are also relevant for the assessment of possible damages to
components of the electric propulsion system. But since these changes were already discussed
in chapter 4, it is not necessary to mention them here again.
Within current research projects, several validation tests with different battery cell types and
charging states were conducted. If cell failure is considered, these validation tests show a high
variation based on test set-up (e.g. test facility or test procedure) and test object conditions
(e.g. functionality or state-of-charge) [204].
137
Regulation Basic Requirements
Focus
ECE-R12
Steering wheel should not injure driver during crash;
Electric requirements: protection against electric
shock, electrolyte spillage and battery retention
ECE-R94
Frontal impact; Electric requirements: protection
against electric shock, electrolyte spillage and
battery retention
ECE-R95
Side impact; Electric requirements: protection
against electric shock, electrolyte spillage and
battery retention
ECE-R100
Requirements for the construction and functional
safety of EV in normal driving
Valid for
Status
Vehicle Class
M1/L7e
Post Crash
Safety
Adopted
M1
Operational
Safety
ECE-R100
R2
Updated test procedure for Battery Crash Evaluation
including a verification test, a component approval
and a vehicle approval
FMVSS 305
Frontal impact, rear impact, side impact and static
rollover test; Electric requirements: electrolyte
spillage and electrical shock protection
Post Crash
Safety
SAE J2464
Safety and Abuse Testing of RESS
RESS
Hazards
Discussed
Adopted
Vehicles with
RESS voltage Adopted
above 60V
Figure 129. Experimental Legislative Crash Requirements for Battery Electric Vehicles
161[204][205].
5.3.3 Future test conditions
For the definition of future test conditions w.r.t. the virtual evaluation of additional safety
hazards due to the electrification of the propulsion system, the following issues need to be
considered:
 Definition of relevant criteria and thresholds:
Currently only few test results for the characterization of the crash load behaviour of
battery cells are published. In the SmartBatt-project (see [205]) some first values for
non-hazardous loads for pouch cells (peak acceleration of 54g in a vehicle pulse of
duration of 100 ms for single cells with a reasonable module assembly) are given.
[210] published non-hazardous values for a certain battery pack housing (deformation
of 0 to 10 mm and an acceleration of a 35g half sinus for 45 ms in z-direction). A
definition using physical basis values, like deformation or acceleration is in principle
preferred. But since the crash characteristics are strongly influenced by the cell type,
the cell manufacturer and the charging state [204], the given values are not sufficient
for a holistic definition of relevant criteria and thresholds.
 Analysis of relevant injury risks:
Within the present study, none statistical in-depth investigation or long term study of
the injury risks resulting due to the additional hazards described in chapter 5.3.1
especially in case of a crash of an Electric Vehicle are available. Without these,
reliable and effective evaluation criteria could not be derived.
138
As long as scientifically reliable results for these issues are missing, a relevant definition of an
evaluation procedure is not reasonable.
5.3.4 Discussion and conclusions
Additional safety hazards, which can occur in case of a crash due to the electrification of the
propulsion system of vehicles, are currently not comprehensively addressed in relevant
publications, or could at least not be found within the present study. Possible reasons might be
the limited number of vehicles available in the European vehicle market and consequently the
limited number of relevant consumer protection tests (e.g. in Euro NCAP). Furthermore, only
a limited amount of relevant publications about the crash safety of BEV (e.g. [204][201])
could be found. As long as the knowledge about the crash safety of electric components is not
expanded, a scientifically based definition of future test conditions is not reasonable.
139
6 Discussion and Conclusions
The objective of this study is the specification of test configurations for vulnerable road user
and occupant protection assessment (incl. compatibility) in future (i.e. 2025) accidents
involving small EV’s in urban areas. Small EV’s in SafeEV in particular concern vehicles in
the mass category of so-called L7e vehicles, where currently hardly any safety requirements
exist. So the focus in the work was on this category, but if relevant also predictions for M1
vehicles where provided in particular if the accident conditions in 2025 are predicted to
deviate significantly from the current conditions..
The test conditions are based on the results of WP1 of SafeEV (see deliverables D1.1 and
D1.2), recent regulatory trends and new developments in the field of consumer testing
(NCAP). The assessment of pre-crash based injury reduction systems is also taken into
account. The work includes specification of the (virtual) tools to be used like impactors,
virtual models, crash dummies, integrated experimental/virtual methods etc…
Concerning evaluation of pre-crash and active safety systems it was concluded that the future
focus in SafeEV will be on passive safety pedestrian and crash sensors and the according
requirements for sensor evaluation tests. For pedestrian safety sensors it was shown that
through their geometry SEVs pose a challenge on the setup of the sensor layout as well as on
the sensor and trigger time of in-crash safety systems for pedestrians. Further it was
concluded that only simulation/virtual tools will allow a continuous observation and
evaluation of integrated safety systems in terms of a benefit based assessment.
For VRU (i.e. pedestrian and cyclist) safety evaluation in SafeEV, presented in Chapter 3,
simulations are proposed using human body models (HBM) in the following 4 sizes: 6 year
old child, 5% Female, 50% Male and 95% Male. Simulations concern impacts of a pedestrian
against the vehicle front at 2 speed ranges: 25 km/h to 30 km/h (lower boundary) and 45 km/h
to 50 km/h (upper boundary). Also simulations for cyclist protection are proposed. Note that
these conditions are similar for L7e vehicles as for M1 vehicles.
Concerning occupant protection the following accident situations have been reviewed: frontal,
side, rollover, rear, compatibility and Multiple Impact Crashes (MIC’s).
For frontal occupant protection for L7e class vehicles a test (simulation with HBM) with an
oblique impact configuration (30 degrees) is proposed. One option here is that also accounts
for compatibility aspects, is a test with at a test speed of 30-40 km/h against a movable barrier
that represents the average opponent vehicle mass (1125 kg in GIDAS analysis). Such a
configuration also adapts automatically the effect of variations in SEV mass. The option for a
full virtual test method here has high potential due to the fact that for crash barriers already
validated models are existing. Verification and validation issues concerning the vehicle model
are in general addressed by the IMVITER project and should be taken into account.
Concerning future frontal compatibility protection of M1 vehicles the ODB offset test
configuration proposed by the FIMCAR project as well the FWDB test, are identified as most
suitable tests to be used within the SafeEV project. The quantification of the use potential of a
test configuration using a movable barrier for compatibility tests addressing SEV-to-SEV and
SEV-to-M1 vehicle front crash behaviour will be an aspect addressed within the project work
package 3.
For side impact occupant protection in L7e vehicles a test (simulation with HBM) using the
latest MDB with a mass of 1100kg reflecting typical future car masses, is proposed. The
barrier will hit the vehicle with a speed of 40 km/h at an angle of 90º. The impact location is
moved backwards reflecting a short bonnet in a car body.
140
Rollover protection is not an important accident scenario in Europe (compared to the USA).
Within SafeEV it is proposed that the SSF (Static Stability factor) and AST (Airbag standing
Time) are calculated. For this no simulations or tests are needed. Eventually if these values
exceed certain critical values it could be considered to perform so-called Fishhook and ESC
tests which can be done by simulations. An Inverted Roof Crush test could be considered as
well but will not be addressed within SafeEV.
For rear impacts the introduction of AEB and introduction of seat concepts aimed at lowering
the risk of WAD (Whiplash Associated Disorders) will reduce the number and risk of WAD
in future rear-end impacts. It is expected that due to vehicle design and packing, the front and
rear-end vehicle stiffness will increase. This calls for a review of the sled pulses to be used in
future rear-end impact tests. WAD will remain frequent and the consequences will continue to
lead to large societal costs and personal suffering. Additional and improved test tools and sled
test conditions are under development and are expected to be introduced. Among these are a
female dummy and associated limits and an adult 95th percentile dummy. Also there is
potential for simulations with HBM’s. Initial positioning of the occupant is a parameter with
large influence.
A final accident condition that was considered are the Multiple Impact Crashes (MIC’s), in
which a vehicle experiences at least 2 impacts after each other. Although the frequency and
injury severity of MIC’s will decrease due to the trends presented in WP1, a strong need to
protect people in MIC’s remains due to the large frequency of these crashes and the relative
high injury risk. Recommendations concerning future work in SaveEV (WP3 etc..)
concerning MIC’s are: (1) Inclusion of occupant simulations (virtual testing) with active
HBM of extreme controlled vehicles manoeuvres that are aimed to reduce the risk of or the
severity of second (or more) impacts in a MIC. The aim of such simulations is to study the
effect on human position changes during such manoeuvres and the resulting risk on OOP’s
and (2) Inclusion of occupant simulations aiming of optimization of reversible and
irreversible restraint systems during MIC’s.
Next to a description of test (simulation) methods in a separate Chapter 5 criteria to be used
in the various test (simulation) conditions have been presented. A distinction is made between
injury criteria, compatibility criteria and fire and electric safety criteria.
The overview of injury criteria is rather extensive. Most important body parts and future
trends are addressed (including the need to have better criteria for children and elderly). Both
global criteria (criteria that also can be determined at physical crash dummies) and criteria on
tissue level to be determined on human body models are described. Also a distinction is made
between criteria for vulnerable road users (pedestrians and cyclists) and car occupants.
Specifically concerning numerical Human Body Models (HBM), which represents bone,
flesh, soft tissue and other anatomically correct structures like organs, might offer injury
prediction in the sense of direct evaluation of biological damage to human structures and
tissues in the future. Of course such an injury prediction capability is intrinsically linked with
the modelling quality and valid representation of material properties. In contrast to the
application of ATDs and related criteria, HBM “criteria”, or better local injury predictors and
corresponding thresholds are currently not broadly agreed and accepted. For skeletal
structures (e.g. ribs, long bones) it could be stated, that a strain-based analysis to predict such
an injury risk or mechanism (fracture) are proposed as method of choice by most of the
authors. Modelling of damage has to be taken into account, if further injury mechanisms,
which might be related with a continued occupant or pedestrian motion sequence in an
impact, are also in focus. Specifically for the head, respectively the evaluation of a complex
141
head injury risk, it could be concluded that the discussions concerning appropriate and valid
criteria are at an advanced stage with the use of HBM / FE head models.
The only currently applied compatibility evaluation criteria concern geometric requirements
(US voluntary commitment), so this is a design based assessment criterion. This sort of
compatibility assessment approach is identified as insufficient for the evaluation of future
SEVs. Studies on vehicles belonging to the Japanese vehicle class of K-cars , which according
to their low weight and unconventional shape can be compared to future L7e SEVs, show
that sufficient structural interaction with a crash partner can even be achieved without direct
loading of the front structure, leading the load path through the front package. Therefore
future compatibility criteria have to be performance and not design based to assure a freedom
of design. The compatibility evaluation criteria defined within the FIMCAR project for the
FWDB and the ODB test are initially identified as also suitable for the assessment of small
electric vehicles. But it should be realized that FIMCAR didn’t integrate a force compatibility
assessment criterion into the final metric proposal, so this may need some additional attention
within SafeEV.
Concerning fire and electric safety criteria an overview of current regulations for crash safety
of Battery Electric Vehicles (BEV) is given. All requirements are for an experimental
evaluation procedure, focusing on frontal, side and rear impacts. A virtual assessment of these
criteria is not considered yet. Possible reasons might be the limited knowledge of or the
experience with the crash safety of BEV and the lack of suitable simulation models. A review
of trends in this field did not predict big changes in the current requirements for 2025.
142
List of Figures
Figure 1. APROSYS – Generic assessment methodology for advanced systems [2]. .............. 11
Figure 2. Overview of current / recently finished research initiatives & collaborative
projects concerning development of active / integrated vehicle safety assessment
methodology. ............................................................................................................................ 12
Figure 3. Harmonisation Platform and involved stakeholders for the implementation of
Active / Integrated Safety assessment procedures – Vehicle/Occupant & Pedestrian
Safety. ....................................................................................................................................... 13
Figure 4. Test procedure for AEB within EuroNCAP protocol 2014 / 2016. [3] .................... 13
Figure 5. Test scenarios for AEB-Pedestrian within EuroNCAP rating 2016. [3] ................. 14
Figure 6. Proposal for Test scenarios and test parameters [4]............................................... 14
Figure 7. Draft Euro NCAP protocol 2012–2017 [3]. ............................................................ 15
Figure 8. Example for test equipment for AEB-Pedestrian assessment – propulsion
systems and pedestrian targets evaluated within ASPECSS, AEB & vFSS. [5] ....................... 15
Figure 9. Integrated Pedestrian Safety Assessment: Assessment methodology for adults
(left), simulation models of generic vehicle class representatives (upper right), safety
assessment overview for adults (lower right). [6] .................................................................... 16
Figure 10. Analysed impact positions from WP1. ................................................................... 17
Figure 11. Test results of 2016 AEB-Pedestrian scenarios (left) and obstructed scenario
with running child (right). [4] .................................................................................................. 17
Figure 12. Assessment of vehicles with active bonnets: Methodology of testing (left),
definition of test setup (right) [7] ............................................................................................. 18
Figure 13. Impactor test procedure according to Euro NCAP test protocol [8] .................... 19
Figure 14. Pedestrian impactors: FlexPLI (left), PDI-1 (middle), PDI-2 (right) [7] ............. 19
Figure 15. General logic of pedestrian safety system (left) and schematic of in-crash
triggering of active bonnet (dummy only used for visualization) (right [212]......................... 20
Figure 16. Pedestrian safety actuators: Reversible hood lift-up Mercedes C-Class (left),
irreversible hood lift-up by window airbag in Volvo V40 (2012) (right). ................................ 20
Figure 17. Pressure-hose based pedestrian safety system: Schematic consideration
(left) and integration in front bumper (right). [9] .................................................................... 21
Figure 18. Time between first body contact and head impact on windscreen for flat and
inclined car geometries - Relevant case 11.1m/s ~ 40 km/h, WP1. For examples of flat
and inclined car geometries see Table 6, Safe EV D1.1 [68] .................................................. 21
Figure 19. Extracted from SafeEV Deliverable D1.2, Fig. 21 [53] ........................................ 22
Figure 20. E/E architecture including occupant safety related sensor layout (in red
[211] ......................................................................................................................................... 23
Figure 21. General logic of occupant safety system (left) and typical in-crash triggered
restraint systems (right [212] ................................................................................................... 24
Figure 22. Oblique Moving Deformable Barrier (MDB) test according to FMVSS 208
[10] ........................................................................................................................................... 24
143
Figure 23. Exemplary depiction of a complete virtual tool chain for integrated system
evaluation – Simulation of active safety systems in real world scenario and derived
effective physical parameters for “avoidance“ & “mitigation” (velocity, time to
collision etc. - here displayed with “shark´s fin curve” from AsPeCSS project) >
Transfer of initial “mitigation” parameters to crash simulation and evaluation of injury
risk). .......................................................................................................................................... 26
Figure 24. Co-simulation including generic surround sensor models from SafeEV WP1.
[Peter Luttenberger, Ernst Tomasch, TU Graz] ...................................................................... 27
Figure 25. Overview on current research initiatives and development concerning
implementation of human behaviour / active muscle reaction to human body models
(OM4Is [12], SAFER [13] and TNO [14]. .............................................................................. 27
Figure 26. Co-simulation of passive and active simulation tools during pre-crash
phase. [15] ................................................................................................................................ 28
Figure 27. Methodology for the definition of the vulnerable road user test proposal. ........... 29
Figure 28. Current impactors which are used or planned for pedestrian testing [16]. .......... 30
Figure 29. Stochastic pedestrian impact analysis showing the location of first contact of
the pedestrian on the vehicle front for nearside collisions and two vehicle speed ranges....... 31
Figure 30. Distribution of vehicle and bicycle velocity before impact. ................................... 32
Figure 31. Description of the parametric study. ...................................................................... 33
Figure 32. Representation of procedure test of bonnet and windscreen severity using
the combination of experimental test and FE simulation. ........................................................ 34
Figure 33. Lateral and frontal view of the pedestrian impact situation. ................................. 35
Figure 34. Overall testing proposal for vulnerable road users showing different paths
which are discussed and reduced for a final variant (green arrows). ..................................... 36
Figure 35. Final proposal for pedestrian impact locations and the simulation effort. ........... 37
Figure 36. Final cyclist impact location on the vehicle front end. .......................................... 38
Figure 37. Final cyclist testing proposal and the simulation effort......................................... 38
Figure 38. Current configuration of ECE R 94 ....................................................................... 40
Figure 39. Revision of ECE R94 - Current status of discussion within informal working
group – Relevant parts for occupant performance criteria are highlighted [36]. ................... 41
Figure 40. (cont.) Revision of ECE R94 - Current status of discussion within informal
working group - Relevant parts for occupant performance criteria / ATD are
highlighted [36]. ....................................................................................................................... 41
Figure 41. Example of Full Width test, EuroNCAP as of 2015[43] ....................................... 42
Figure 42. Overview of Full Width test configurations – NCAP worldwide [37]. .................. 43
Figure 43. Overview of Full Width test configurations – performance criteria 5th female
[37]. .......................................................................................................................................... 43
Figure 44. Example of ODB test- EuroNCAP current protocol [43] ...................................... 44
Figure 45. Q-Dummy series [38]. ............................................................................................ 44
Figure 46. Small Overlap test configuration – ........................................................................ 45
Figure 47. IIHS Small Overlap - Assessment of structural behaviour [37]. ........................... 45
Figure 48. IIHS Small Overlap – Flowchart calculating head & neck injury rating [38]. ..... 46
144
Figure 49. Example for dummy-airbag interaction assessment within IIHS Small
Overlap testing – ranking was “partial” in this test. [38] ....................................................... 47
Figure 50. Additional measuring system for dummy excursion (IIHS Small Overlap
testing). [38] ............................................................................................................................. 47
Figure 51. CCIS – Passenger car accidents by impact type [42]............................................ 52
Figure 52. FVMSS dynamic test setup [46]. ............................................................................ 54
Figure 53. Smart ED electric drive train. ................................................................................ 58
Figure 54. Side Impact. ........................................................................................................... 58
Figure 55. Compatibility characteristics ([50]) ...................................................................... 60
Figure 56. Horizontal (left) and vertical (right) disalignment of front structures [49] .......... 60
Figure 57. FWRB test according to Euro NCAP rating from 2015 [60]................................. 62
Figure 58. Test configurations proposed by NHTSA [62]. ...................................................... 63
Figure 59. Rollover type specification. .................................................................................... 70
Figure 60. Static Stability Factors of current vehicle designs integrated into the NHTSA
Rollover risk diagram. [88] ...................................................................................................... 72
Figure 61. Four identified accident Types of the MATISSE project. [88] ............................... 72
Figure 62. Rollover probability within side impact collisions for a small generic
electric vehicle. ......................................................................................................................... 73
Figure 63. Rollover testing proposal for future SEV´s. ........................................................... 75
Figure 64. BioRID II dummy installed in a seat prior to a Euro-NCAP rear-end impact
test............................................................................................................................................. 77
Figure 65. Measurements of the seatback height (left) and gap size in head restraint
(middle) and backset using a HPM/HRMD (right) [91]. ......................................................... 78
Figure 66. Sled acceleration corridor suggested for the GTR 7 Phase 2 [91]........................ 78
Figure 67. Relative whiplash injury risk for females compared to males [93]. ...................... 80
Figure 68. Example of a Multiple Impact Crash [98] ............................................................. 81
Figure 69. Probability of head injuries of different severities for given HIC values. ............. 86
Figure 70. Head Protection Criteria for Pedestrian Protection.............................................. 86
Figure 71. Injuries mechanisms in case of pedestrian impacts. .............................................. 87
Figure 72. Synthesis of VRU injury criteria used in regulations with limits values. ............... 87
Figure 73. Risk of brain injuries as a function of BRIC for various AIS levels for Hybrid
III (Frontal impact). ................................................................................................................. 89
Figure 74. Tolerance limits for ECE and EuroNCAP (upper neck Fx) respectively. .............. 89
Figure 75. Representation of neck injury risk curves corresponding to Nij criteria................ 91
Figure 76. Thorax anatomy Sobotta 2010 [117]. ................................................................... 92
Figure 77. (a) Heart compression and aorte failure, (b) combination of thorax
compression and neck extension leading to aortic laceration [121]. ...................................... 93
Figure 78. Hernia of diaphragm due to an abdomen impact [121]. ....................................... 93
Figure 79. Impact test on cadavers at sternum level; Force-displacement curve of
thorax [122][123]. ................................................................................................................... 93
Figure 80. Risk curves for AIS3+, constructed for the Hybrid III dummy in terms of
maximum slider deflection (Kent [128]). ................................................................................. 95
145
Figure 81. Thoracic risk curves (a) for AIS>3 in function of Hybrid III sternum
deflexion, (b) for AIS>4 in function of Viscous Criterion. ...................................................... 95
Figure 82. Location of the five measurement points on the chest. ........................................... 96
Figure 83. Possible fractures due to impact on knee [Crandall 1995] [139]. ........................ 98
Figure 84. Tolerance limits for femur force. ........................................................................... 98
Figure 85. Hybrid III ATD (anthropomorphic test device) Dummy & corresponding
virtual FE model [140]. ............................................................................................................ 99
Figure 86. Risk of brain injuries as a function of BRIC for various AIS levels for
WorldSID ................................................................................................................................ 101
Figure 87. Risk of brain injuries as a function of BRIC for various AIS levels for ES2re. .......................................................................................................................................... 101
Figure 88. Risk curves for EuroSID dummy (USNCAP). ...................................................... 101
Figure 89. Organs of abdomen [Sobotta 2010] [117]........................................................... 102
Figure 90. Injury risk curve for EuroSID dummy (USNCAP). .............................................. 102
Figure 91. Injury risk curve for EuroSID dummy (USNCAP). .............................................. 103
Figure 92. NICmax Risk curve for symptoms >1 month [155]. ............................................... 104
Figure 93. WAD2+ risk functions [152]................................................................................ 106
Figure 94. Risk curve of symptoms > 1 month [155]. ........................................................... 107
Figure 95. Strasbourg University Finite Element Head Model (SUFEHM). ........................ 108
Figure 96. Head injury tolerance curve calculated with SUFEHM model under LSDyna code for DAI injuries. ................................................................................................... 109
Figure 97. Head injury tolerance curve calculated with SUFEHM model under LSDyna code for SDH injuries. .................................................................................................. 109
Figure 98. Head injury tolerance curve calculated with SUFEHM model under LSDyna code for skull fracture injuries...................................................................................... 110
Figure 99. Head Injury prediction Tool................................................................................. 110
Figure 100. Relationships between strains and WAD [152]. ................................................ 113
Figure 101. Cross section of the Strasbourg University human head–neck system FE
model. ..................................................................................................................................... 114
accident reconstructions with FE head/neck model. .............................................................. 114
Figure 105. The THOR (Test Device for Human Occupant Restraint) dummy –
additional measurement compared to HIII & new criteria under discussion [172]. ............. 116
Figure 106. Multi chest deflection points (THMPR) for HIII and virtual HBM (THUMS)
– here evaluation of various seat belt and airbag loading condition [173]. ......................... 117
Figure 107. RibEye - Multi-point differential thorax deflection measurement to evaluate
peak chest deflection / non-symmetric chest deflection - optically-based measurement
system to be used with the HIII 50th dummy [175]. ................................................................ 117
Figure 108. Schematic figure of the Deq [178]. .................................................................... 118
146
Figure 109. Deformation of the chest in simulated frontal collisions using a
HUMOS2LAB HBM [179]. .................................................................................................... 119
Figure 110. Injury risk functions for the THORAX demonstrator; Dmax to the left and
DcTHOR to the right [180]. ................................................................................................... 120
Figure 111. Method used in the THORAX project to transfer rib strain to NFR and
sample injury risk curve based on NFR.................................................................................. 120
Figure 112. (left) Plastic strain damage model – A > yield strain, B > damage
initiation, C >complete damage; (right) Fracture distribution in ribcage model [184]. ...... 122
Figure 113. (left) Von Misses stress at 60 ms /40 km/h sled test and (mid) rib fracture
predicted by the model – (right) rib fractures seen in PMHS test [184]. .............................. 123
Figure 114. Sensor device in current THOR dummy to measure lap belt force – dummy
an related FE-model [172]. .................................................................................................... 124
Figure 115. Biofidelity evaluation of current THOR dummy – abdominal [192]. ................ 124
Figure 116. Capability in predicting crash induced injury with current GHBMC 50%
model – abdomen region [193]. ............................................................................................. 125
Figure 117. (top) Liver damage obtained from the experiments – (bottom) True strain
distribution of liver membrane at maximum compression ratio [195]. ................................. 126
Figure 118. Illustration of current Flex PLI impactor and FE model (Flex PLI GTR
V2.0) 1 [197]. ......................................................................................................................... 127
Figure 119. Left – Example for three point bending simulation of humerus – Right –
Example for simulation of injury mechanism and fracture of femur due to knee bolster
impact [198]. .......................................................................................................................... 127
Figure 120. Comparison of injury prediction of numerical HBM and impactor (here
FlexPLI) [199]........................................................................................................................ 128
Figure 121. Left - Knee area HBM Honda [Takahashi Y et al.; IRCOBI 2012 – Right –
Knee area HBM H-LE model [198]. ...................................................................................... 128
Figure 122. Scheme illustrating the part 581 zone overlap requirements [54]. ................... 130
Figure 123. Load cell wall dimensions [54]). ...................................................................... 131
Figure 124. Digitalisation and evaluation example for barrier face deformation [58]. ....... 132
Figure 125. Metric for load path detection on PDB face assessing longitudinal
deformation [50]. ................................................................................................................... 133
Figure 126. Possible hazards of traction batteries in Battery Electric Vehicles
[207][209]. ............................................................................................................................. 134
Figure 127. Possible injuries resulting from batteries or High-Voltage Systems in EV. ...... 135
Figure 128. Simulation models of traction batteries. ............................................................ 136
Figure 129. Experimental Legislative Crash Requirements for Battery Electric Vehicles
164[207][208]. ....................................................................................................................... 137
147
List of Tables
Table 1. Current Regulation and Standards for pedestrian testing. ....................................... 30
Table 2. General results of the bicyclist collision parametric study. ....................................... 33
Table 3. EuroNCAP, U.S. NCAP, IIHS side impact comparison. ............................................ 54
Table 4. JNCAP, C-NCAP, KNCAP, ANCAP side impact comparison. .................................. 56
Table 5. Compatibility priorities for SEVs and their (conventional) crash partners............... 61
Table 6. Overview of compatibility test configurations discussed within FIMCAR. ............... 62
Table 7. NHTSA crash test configuration parameters [63]. .................................................... 63
Table 8. Assessment of full width test constellations according to defined compatibility
priorities. [(+) good / (o) neutral / (-) weak] ........................................................................... 64
Table 9. Assessment of offset test constellations according to defined compatibility
priorities. [(+) good / (o) neutral / (-) weak] ........................................................................... 65
Table 10. Detailed assessment of FWRB test according to defined compatibility
priorities. .................................................................................................................................. 65
Table 11. Detailed assessment of FWDB test according to defined compatibility
priorities. .................................................................................................................................. 66
Table 12. Detailed assessment of ODB test according to defined compatibility
priorities. .................................................................................................................................. 66
Table 13. Detailed assessment of PDB test according to defined compatibility priorities. ..... 67
Table 14. Detailed assessment of M(P)DB test according to defined compatibility
priorities. .................................................................................................................................. 68
Table 15. Possible scaling parameters of front compatibility test constellations. ................... 68
Table 16. Current regulations for rollover testing. .................................................................. 70
Table 17. SSF calculated for different vehicle designs. [73][82][83][84][85][86][87] ....... 71
Table 18. Parameter definition for the stochastic rollover side collision scenario
investigation ............................................................................................................................. 73
Table 19. Test conditions used in NCAP programs and in the rear-end impact tests
performed by IIHS. ................................................................................................................... 77
Table 20. Proportions (and 95% confidence limits) of female and male drivers (%) with
symptoms for more than one month and permanent medical impairment (PMI) in
relation to number of reported initial symptoms for rear-end impacts as a function of
year of introduction on the market (adopted from [92]. .......................................................... 79
Table 21. SIC’s and MIC’s in GIDAS database 1999-2007 [99]. ........................................... 82
Table 22. Critical value of Force and Moment for different dummies..................................... 90
Table 23. Limit peak Force for different dummies. .................................................................. 91
Table 24. Critical/intercept 3 ms Aint values and the critical/intercept deflection Dint
values to be used in the calculation of CTI for each dummy type. ........................................... 97
Table 25. Threshold value for femur, tibia and fibula [Levine, 2002] [138]. ......................... 98
Table 26. Forces and moments critical values. ........................................................................ 99
Table 27. HIII injury criteria - defined and assessed in most of the current regulations
and consumer test. .................................................................................................................. 100
Table 28. Criteria used in combination with BioRID II in rear-end impact testing in
various rating programs. ........................................................................................................ 103
148
Table 29. Limits used in rear-end impact testing by Euro-NCAP Medium Severity Pulse. ... 103
Table 30. Critical values used in the calculation of Nkm. ....................................................... 106
Table 31. Reasons to include or exclude an injury criteria/parameter [156]. ...................... 111
Table 32. Draft injury criterion as discussed by the informal group in the meetings on
GTR-HR2; proposal from JAPAN - JMLIT/JASIC/JARI with a green background,
proposal from NHTSA with a red background. ...................................................................... 112
Table 33. Vertical load spreading assessment metric for FWDB test [54]. .......................... 131
149
Acknowledgements
This study was co-funded by the European Commission (7th Framework-Programme) as part
of the SafeEV project.
150
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