Energy-efficient and Intelligent Heavy-duty Vehicle

Transcription

RESEARCH REPORT
VTT-R-02704-11
Energy-efficient and Intelligent Heavy-duty
Vehicle (HDENIQ): Annual report 2009
Authors:
Kimmo Erkkilä, Tuukka Hartikka, Petri Laine, Matti Ahtiainen, Pekka Rahkola, Nils-Olof Nylund,
Kari Mäkelä, Maija Lappi, Kai Noponen (University of Oulu), Heikki Liimatainen (Tampere University of Technology)
Confidentiality:
Public
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Contents
1 Introduction and framework ....................................................................................6
2 Project coordination ...............................................................................................8
3 Research partners and contents of the work ..........................................................9
4 Vehicle technology (VTT, Aalto University)...........................................................11
4.1
4.2
4.3
4.4
General outline..............................................................................................11
Energy consumption and emissions of auxiliaries.........................................11
Aerodynamics ...............................................................................................13
Tyre research................................................................................................14
4.4.1 Plan....................................................................................................14
4.4.2 Results...............................................................................................15
5 Intelligent heavy-duty vehicle (VTT, University of Oulu) .......................................17
5.1
5.2
5.3
5.4
5.5
General information ......................................................................................17
Automatic slip detection ................................................................................17
Automatic load detection...............................................................................17
Background information systems ..................................................................17
The intelligent heavy-duty vehicle of the future.............................................18
5.5.1 Preliminary study on the intelligent bus (University of Oulu) ..............18
5.5.2 Preliminary study on the intelligent truck............................................19
5.5.3 Planning and implementation of the in-vehicle data acquisition system19
6 Actual performance and service-life management of heavy-duty vehicles (VTT,
Turku University of Applied Sciences) ..................................................................20
6.1 General .........................................................................................................20
6.2 Emission and fuel consumption measurements for new vehicles .................20
6.2.1 Trucks ................................................................................................20
6.2.2 City buses ..........................................................................................25
6.3 Vehicle maintenance.....................................................................................38
6.3.1 General ..............................................................................................38
6.3.2 Brake checkups of heavy-duty vehicles at statutory vehicle inspections
(Turku University of Applied Sciences) ..............................................39
7 Reporting methods and evaluation of the effects of actions (Tampere University of
Technology, VTT) .................................................................................................41
7.1 General information ......................................................................................41
7.2 Customer-specific determination and reporting of transportation emissions.41
7.2.1 General description and goals ...........................................................41
7.2.2 Literature survey ................................................................................41
7.2.3 Survey................................................................................................42
7.2.4 Further plans......................................................................................43
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7.3 Evaluation of the effects of energy-efficiency measures ...............................43
7.3.1 General description and goals ...........................................................43
7.3.2 Literature survey ................................................................................43
7.3.3 The ETS databank on public transport...............................................45
7.3.4 Future plans .......................................................................................46
8 Development of research methodology (VTT)......................................................47
8.1.1 Determination of driving resistances ..................................................47
8.1.2 New vehicle types ..............................................................................48
8.1.3 New driving cycles .............................................................................50
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1
Introduction and framework
The Energy-efficient and Intelligent Heavy-duty Vehicle project, also known as the
“HDENIQ”project, aims at for reduced energy consumption and emissions and improved safety of heavy road vehicles. The project, building on the legacy generated
the earlier efforts of HDEnergy (“Fuel savings for heavy-duty vehicles 2003 –
2005”) and RASTU (“Heavy-duty vehicles: Safety, environmental impacts and new
technology 2006 –2008”), is part of the new Trans-Eco research programme coordinated by VTT on energy efficiency and renewable energy in road transport. Reports
from
the
previous
stages
can
be
found
at
http://www.motiva.fi/en/transport/projects_in_the_transport_sector/rastu_20062008/.
Launched by VTT, the five-year (2009 – 2013) TransEco research programme develops, demonstrates and commercialises technology for improved energy efficiency
and reduced emissions in road transport. The programme serves as a platform for integrated evaluation and development of new technology and policies for the road
transport sector. Finland’s competencies include fuel conversion technologies and
bio-fuels for transport, applications of information technology (IT) and aspects of
vehicle technology like light-weight structures, electric cars, hybrid vehicles, tyres,
exhaust emission control devices, to mention a few examples. All possible elements
are needed to reduce the environmental impact of traffic.
To begin with, the programme will focus on research and the generation of basic information for decision-making. This will be followed by the techno-economic
evaluation of alternative pathways and the planning of necessary steering actions and
measures. After this, the programme will focus on facilitating the market introduction of new technologies and rooting of the preferred operational methods.
The goals of the TransEco project are as follows:
TheTransEco programme provides a tool for adapting the Finnish road transport
system in a cost-effective way to national and EU-level climate and energy targets.
The data generated within the programme will be used as input in the process of
drafting and implementing EU directives, for the selection and implementation of the
energy pathways most suitable for Finland and for supporting technology exportation. On the technical level the key targets are energy savings in transport, implementation of carbon neutral energy and increasing self-sufficiency in transport energy supply. Advanced biofuels, technology for hybrid and electric vehicles and ICT
solutions for road transport are among the themes covered. The programme is extensively supported by the public sector (ministries and agencies) as well as by industry
The operating model is based on good collaboration among decision-makers, companies, researchers and other actors in the traffic sector.
Information regarding TransEco can be found at www.transeco.fi.
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Like the previous research projects mentioned above, HDENIQ brings together
transportation companies, fleet operators, customers for transportation services and
decision-makers in the public sector, as well as research institutes and other actors in
the transportation sector to promote energy efficiency, emission reductions and
safety for heavy-duty road vehicles.
The HDENIQ project will cover the years 2009 – 2011, and it is the largest single
project within the TransEco programme. The main source of funding for HDENIQ is
Tekes – the Finnish Funding Agency for Technology and Innovation. Actual work
within HDENIQ commenced in the early fall of 2009.
The general framework and links to other projects, as well as matters related to
communications, are presented in the 2009 annual report of the TransEco programme. Published in April 2010, the report VTT-R-03160-10 is available on the
TransEco website at http://www.transeco.fi/. The project plan for HDENIQ is presented in the document VTT-M-01450-09.
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2
Project coordination
A coordination group has been assigned for the project that consists of representatives of both funding and research parties. Typically, this steering group convenes
twice a year, but it can also make decisions related to the project at other times, if
needed. This is to ensure prompt assessment of new ideas.
The actual research work did not begin until the autumn of 2009. For this reason,
only one meeting related to the HDENIQ project was held during the reporting period. This two-part meeting took place in Otaniemi on 23 September 2009. The event
began with a shared administrative meeting for the vehicle projects included in the
TransEco programme: HDENIQ (heavy-duty vehicles) and EFFICARUSE (lightduty vehicles). The research plan of the HDENIQ was presented and discussed during the second part of the meeting. In addition, a joint seminar was held to end the
RASTU project and to launch the TransEco programme on 4 November 2009 at Innopoli in Otaniemi.
A consortium agreement to confirm the composition of the coordination group was
concluded in 2009. The organisations participating in the programme are listed below (Visbolas, which is mentioned in the original HDENIQ plan, withdrawn of the
project because of a cancelled parallel project).
•
•
•
•
•
•
•
•
•
•
•
•
Finnish Vehicle Administration AKE
Ministry of Transport and Communications
Helsinki Metropolitan Area Council YTV
Helsinki City Transport HKL
Kabus
Transpoint
Nokian Tyres
Gasum
Itella
Veolia Transport Finland
Neste Oil
Proventia Emission Control
Research parties:
• VTT Technical Research Centre of Finland
• Aalto University School of Science and Technology
• Tampere University of Technology
• Turku University of Applied Sciences
• University of Oulu
The composition of the coordination group is confirmed annually.
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3
Research partners and contents of the work
Several research institutes cooperate within TransEco and the HDENIQ project. In
the case of HDENIQ the research partners are:
•
•
•
•
•
VTT Technical Research Centre of Finland, principal research partner and
coordinator
Aalto University (vehicle technology)
Oulu University (ICT technology)
Tampere University of Technology (reporting systems)
Turku Polytechnic (vehicle technology)
The HDENIQ research project consists of six sub-projects. Below is a short list of
these sub-projects and their contents.
Vehicle technology
•
•
•
•
•
•
•
•
Improvement of aerodynamics: potential and practical possibilities; fuel
consumption vs. functionality; usability, safety and legislation
Potentials and opportunities related to hybrid and electric heavy-duty vehicles
Reduction of energy consumption in auxiliaries: profiles for operation and
optimisation of use
Optimisation of heating and cooling systems (HVAC)
Tyre selections related for heavy-duty vehicles, especially in terms of fuel
consumption and safety
Development of a tyre selection tool for the needs of transportation companies
Evaluation of actual tyre performance in Finnish conditions (in connection
with ITC development, e.g. automatic slipperiness detection)
Evaluation of the effect of lubricants on energy consumption in heavyduty vehicles
Intelligent heavy-duty vehicle
•
•
•
•
New and innovative equipment that makes operating heavy-duty vehicles
easier and more efficient
Evaluation of the effects of driver’s aid systems, including background
computing systems and reference databases
Automatic slip and load detection; the effect of environmental conditions
on the reliability of methods
The intelligent heavy-duty vehicle of the future: preliminary study; buses
and trucks
Life-cycle emissions and energy consumption of heavy-duty vehicles
•
•
Emissions and energy consumption of new vehicles
Stability of emissions and energy efficiency over the service life of the vehicle
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•
•
•
•
Truthful emission factors based on actual vehicle operation, evaluation of
vehicle emission performance as part of emission models and inventories
Unregulated emissions
Performance of retrofitted emissions control systems
Improving the inspection systems for heavy-duty vehicles
Public procurement & tendering
•
Development of tendering systems for bus and truck transport services to
better reflect environmental impacts (energy consumption, local emissions, renewable energy)
Reporting methods and evaluation of the effectiveness of energy conserving
measures
•
•
Evaluations of energy-efficiency of total transport chains
Evaluation of the overall effects of energy-saving measures, including the
outcomes of the HDEnergy and RASTU projects
Development of methodology
•
•
•
Measurement methods to assess improved aerodynamics as part of measures to reduce fuel consumption
Defining the accuracy for measurement of air resistance in highway conditions
Assessment methods for new vehicle types, e.g. hybrids
Most of these sub-projects were launched during 2009. The plans and first results
are discussed in more detail in the following section.
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4
Vehicle technology (VTT, Aalto University)
4.1
General outline
In order to minimise total energy consumption, the vehicle’s need for power should
be minimised and the efficiency of power generation should be maximised.
Significant efforts have been put in reducing the fuel consumption of heavy-duty engines. The vehicle itself, however, has received less attention. Therefore, this subproject will focus on the vehicle rather than on the engine. It examines where, how and
how effectively the generated power is used. As for the engine, the research will be
limited to the user’s opportunities to influence energy consumption and emissions by
choosing the engine correctly.
During the first year of the project, experimental research in vehicle technology focused mainly on tests on auxiliaries. In addition, plans and preparations were made
for future measurements related to improved aerodynamics and tyres. Nokian Tyres
carried out research related to tyre grip in slippery conditions. The results will be
presented in this report.
4.2
Energy consumption and emissions of auxiliaries
In the summer of 2009, pre-tests were carried out to study the energy consumption of
auxiliaries in different weather and driving conditions and operating states.
The tests were performed using a Kabus ML city bus (model year 2009), which was
equipped with the necessary sensors and data acquisition equipment. Engine load
was recorded from the CAN bus of the vehicle. The following auxiliaries were
tested:
•
•
•
•
•
engine cooling fans
air compressor
power steering
A/C compressor
alternator
These auxiliaries were decoupled for the tests and forced to run under maximum load
in order to reproduce specific situations.
In this bus model, the engine cooling fan is controlled using a magnetic coupling
with three options: “fan off,” “fan partially engaged” and “fan fully engaged” The
tests were carried out using the “fan fully engaged”and “fan off”settings. When testing the air compressor, it was forced to operate at maximum output, and its pressure
level was measured. For the parallel test, the compressor was demounted.
Power steering was loaded by turning the steering wheel throughout the entire test.
The pressure generated by the power steering pump was measured during this time.
This allowed for measuring the pump loading at a typical pressure level.
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The driver’s air conditioning system was controlled by varying the power demand by
different target temperature settings. The zero level was measured by switching
power off by disengaging the magnetic coupling of the A/C compressor.
When measuring alternator performance, the alternator was loaded using the vehicle’s power-consuming units, as well as an additional load resistor that was connected to the alternator. The power and voltage levels of the alternator were measured over the tests.
Figure 1 shows the energy consumption of different auxiliaries over the engine speed
range. The figure shows that the energy consumption of the cooling fan increases exponentially when the engine speed rises above 2,000 revolutions per minute. The energy consumption of other auxiliaries was relatively steady regardless of engine
speed.
Energy consumption of auxiliaries over engine rpm range
logged from CAN-bus
12.0
10.0
Cooling Fan
Power demand (kW)
8.0
Air Compressor
Powersteering Pump
Driver Air Conditioning
6.0
Alternator 65/120 A
4.0
2.0
0.0
500
1000
1500
2000
2500
3000
Engine s peed (RPM)
Figure 1. Energy consumption of auxiliaries over engine rpm range.
The results of these preliminary tests will be used in a later stage of the project, in
which two city buses, an express coach, a delivery truck and two heavy-duty trucks
will be equipped with information acquisition devices. This information will be used
to collect operating and condition information related to auxiliaries and, consequently, energy consumption information related to auxiliaries in actual driving and
operating conditions. In addition, the results can be used when dimensioning electrically driven auxiliaries.
Related to the research on auxiliaries, a student of Aalto University will complete a
master thesis started in 2009 on HVAC (heating, ventilation and air conditioning)
during the spring of 2010.
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In addition, a literature survey on the power needs of auxiliaries will be completed in
2010.
4.3
Aerodynamics
Designers of heavy-duty vehicles and their superstructures have traditionally paid
less attention to aerodynamics than other properties. Because current legislation restricts the length of vehicle combinations, designers have wanted to use all of the
available cargo space as effectively as possible. This has usually led to designs that
are in contrast with good aerodynamics.
The driving resistance of a heavy-duty vehicle combination consists of rolling resistance and air resistance that is also called drag. For a truck-trailer vehicle combination (enclosed body) with a full payload, air resistance typically represents about
40% of the total resistance at a speed of 80 km/h. With improved aerodynamics resulting in reduced drag coefficient (Cv) this proportion can be reduced considerably.
The drag coefficient of a modern truck-trailer vehicle combination is between 0.6
and 0.8, mainly because of unfavourable design defined by cargo spaces. If the drag
coefficient could be reduced by improvement of aerodynamics for example by 50%,
the total driving resistance would decrease by about 20%. An equivalent reduction in
energy consumption could be achieved by, for example, decreasing speed from 80 to
about 56 km/h (by 30%).
The aerodynamics sub-project is based on harnessing the potential of reducing air
drag for increased energy efficiency. The goal is to make adjustments and modifications to existing vehicles that are as practical as possible, and to enhance vehicle performance significantly through these aerodynamic improvements. Most of these improvements will not affect vehicle usability or load handling. The aerodynamic
modifications consist of different types of covers and panels that will be mounted on
the test vehicle combinations. The feasibility of the aerodynamic aid solutions presented in Figure 2 will be explored during the first phase of the research project.
Air deflector between cabin and cargo space Aerodynamic panels between cargo spaces
Aerodynamic underpanel
Boat tail trailing edge panels
Aerodynamic side farings
Figure 2. Aerodynamic development goal.
In addition to the reduction of air resistance, the aerodynamics sub-project examines
the effect of wind conditions on the stability of vehicle combinations. The combination of truck plus full trailer is of special interest for Finland. The project will assess
the stability of a vehicle combination and the factors that affect this stability. It will
also provide information for the aerodynamic design of vehicle combinations.
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Sensitivity to side-wind will be studied using computer simulations. These simulations for vehicle combinations will be based on the multi-body simulations approach,
in which the air resistance of both units of a vehicle combination is described as
point loads. The evaluations of the power, direction and point of application of air resistance will be based on experimental data from wind tunnel tests carried out using
scale models as part of the former RASTU project.
The aerodynamics sub-project will study the effects of the magnitude and the angle
of incidence of the airstream in terms of the requirements they set for the necessary
friction levels between tyres and the road surface in each axle needed to maintain
stable ride. In addition, the project will study, as special cases, deceleration in slippery conditions with a side-wind, as well as sudden and significant changes in sidewind, for example, when moving from forested areas to open areas.
4.4
Tyre research
4.4.1
Plan
A new study combining on-road measurements, chassis dynamometer measurements
and actual field tests has been set up. The new study complements and adds to the results of earlier projects. The tyre study will examine the effects of tyre size, tyre imbalance, tyre pressure and tyre wear on the energy consumption of a vehicle.
In the on-road measurements, the effects of tyre size on energy consumption will be
examined using two similar trailers (the brand of the trailers is Ekeri) with different
tyre sizes (385/65 22.5 and 445/45 19.5). In addition, the effects of tyre imbalance
will be studied using additional weights that will be attached to tyres.
VTT’s heavy-duty chassis dynamometer will also be used to examine the effects of
different tyre brands, tyre imbalance, tyre pressure and tyre size on energy consumption.
The field tests related to the tyre study will be carried out using vehicles operated by
Transpoint and Veolia transport companies. The research teams will select vehicles
that frequently use the same routes, which make them suitable for collecting data.
The vehicles will be equipped with data acquisition devices and different types of
tyres. The field tests will provide information about tyre behaviour and performance
in Finnish conditions, both based on the automated LIKU slip detection system developed in the previous research phases and observations from the drivers. Tyre wear
will also be observed. It is also expected that the field test will deliver information on
fuel consumption differences.
The following four new sets of tyre series will be examined in the field tests:
o Noktop 41
o Noktop 31
o Noktop 45 (AllSeason)
§ Standard
§ Siped (a fine-grooved tyre with additional incisions at an interval of about
10 millimetres on the surface, covering approximately half of the surface)
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The results of the tyre survey will be used, for example, to develop a tyre calculator.
The calculator is a tool intended to make selecting the right type of tyre easier for the
operators. The tool takes into account purchasing and operating costs, durability and
other parameters, with the objective to make tyre comparisons as practical as possible.
Results
As part of the tyre study, Nokian Tyres carried out comparative research on a slippery-surface test track.
Tests were performed using single-mounted tyres on hard-packed snow, with an axle
load of 8,000 kg and a tyre pressure of 8.0 bars. The following tyre models were
tested:
o Noktop 41
§ Standard (new)
§ Tyre wear of about 33%
o Noktop 45 (AllSeason)
§ Standard
§ Siped
Figure 3 shows the test results from the slippery-surface test track. When the reference tyre (Noktop 41, tyre wear of about 33%) is compared to a new Noktop 41 tyre,
it is evident that tyre wear does not have a significant effect on tyre traction.
Tyre traction on hard packed snow
35
30
25
Traction [kN]
4.4.2
20
15
10
5
0
0
10
20
30
40
50
60
70
80
90
Slip precentage [%]
1. 315/80R22.5 NOKTOP 41, 1/3-w orn
2. 315/80R22.5 NOKTOP 41
3. 315/80R22.5 NOKTOP 45
4. 315/80R22.5 NOKTOP 45 Siped
Figure 3. Tyre traction (kN) as a function of slip percentage on hard-packed snow.
Data from Nokian Tyres.
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Furthermore, the test results for Noktop 45 (AllSeason) Normal are slightly weaker
than those for the other tyres included in the test series. Noktop 45 (AllSeason) Siped
recorded the best test results. Based on these results, siping improves tyre traction on
hard-packed snow.
A master’s thesis on the effects of tyre balancing and tyre pressure on energy consumption and traffic safety is in progress at Aalto University. The work will be completed during the spring of 2010.
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5
Intelligent heavy-duty vehicle (VTT, University of Oulu)
5.1
General information
Current motor vehicles are already equipped with multiple sensors and various ICT
systems that collect and process information related to vehicles and their operation.
Aside its original purpose of use, this information could be used more effectively to
enhance the efficiency of day-to-day operations at transport companies, to aid drivers
actively, and even to restrict vehicle performance if necessary for the purpose of
safeguarding the vehicle in potentially dangerous situations.
ICT technologies offer opportunities to increase energy efficiency and road safety, to
improve service level and to provide automatic reporting options.
5.2
Automatic slip detection
TechnoSmart already supplied slip and load detection devices for the previous
RASTU project. For the HDENIQ project, Technosmart was asked to provide an offer on check-ups and software updates, as well as reinstallation and maintenance, of a
total of nine devices. Negotiations were carried out with Transpoint Oy on device installations and use in full trailer trucks in the same manner as in the RASTU project.
In addition to the functionality of the slip and load detection (LIKU) method, the
equipment supplied by TechnoSmart will now be used to study how the LIKU
method could be used also to evaluate tyre performance in Finnish climate and road
conditions (see section 3.4, Tyre research).
In addition to the equipment acquired for field-tested during the RASTU project, new
and more powerful vehicle computers will be acquired. These can be used to study
how external factors affect the observations made by the slip detection system. These
new computers will also serve as data acquisition devices in tests performed on operation of auxiliaries in Finnish conditions, as well as for automatic slip detection.
Work to commercialise the automatic slip detection system also is underway. The
system will be based on simpler terminals. Also these will be tested in Transpoint
vehicles. This phase has been awarded separate funding and it will be carried out
alongside the HDENIQ project.
5.3
Automatic load detection
The research on automatic load detection will be continued at a later stage of the project, after the multi-purpose data acquisition devices referred to in sections 3.4 and
5.5.3 have been put to use.
5.4
Back-end information systems
The automated slip detection system will need a back-end information support system. The back-end system will collect data from the instrumented vehicles and collate this data into real-time slipperiness information of the road network. For this
purpose, the back-end system must be able to make the information obtained from
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different types of vehicles commensurable. In addition, the information system will
create vehicle-specific files containing warnings of slipperiness for each of the vehicles within the system.
5.5
The intelligent heavy-duty vehicle of the future
5.5.1
Preliminary study on the intelligent bus (University of Oulu)
During the first year of the project, a preliminary study was carried out assessing different intelligent vehicle systems that can be found in scientific literature and patent
documents. The number of ICT applications for vehicle systems has increased rapidly in recent years. Today computing power allows the implementation and design
of intelligent algorithms to improve safety, for example. Intelligent control systems
can also bring other benefits, such as reduced fuel consumption. This would help
transport service companies, as well as others, to save costs.
The preliminary study focused on the applications of intelligent systems in buses.
The study was based on information on Intelligent Transportation Systems (ITS),
with cutting-in on in-vehicle systems and information infrastructure. The main focus
was on intelligent algorithms. The written report of the preliminary study includes 74
references to scientific publications and patent documents.
The study on in-vehicle systems focused on sensors, internal data communications,
driver’s aid information, driver guidance, driver evaluation, diagnostics and service,
safety, optimisation of road operations based on different criteria, as well as navigation and passenger comfort.
In topics related to the driver, the focus was on safety and how to deliver information
to the driver. In the evaluation of driver performance, the focus was on measurable
parameters found in reference literature that could be used in further research to create, for example, indices on safe or economical driving.
Topics like diagnostics, automated maintenance and safety have already been researched a great deal, and a large number of patents have been awarded in these
fields. In terms of safety, the preliminary study focused on products that are already
available and can be used to observe the surroundings and the operation of the vehicle, and possibly to restrict vehicle’s performance, if potentially dangerous situations
are encountered.
Regarding optimisation of driving the vehicle, the study examined how driving
events and operation of vehicles can be controlled automatically. In addition, the
study examined different criteria for such optimisation. Direct control methods include adaptive driving speed controllers that can be used to improve safety, but they
can also be used on the basis of other optimisation criteria. Of these topics, applications related to safety have been studied the most in scientific literature.
Intelligent control requires real-time information on the location of the vehicle.
Therefore, different applications of positioning that serve this function were studied.
The purpose of this study was to define the requirements related to navigation appli-
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cations in buses. In addition, the study covered navigation applications that are already available, as well as the option of creating new ones based on either commercial or free, public-domain maps.
The study on information infrastructure focused on data communications, exploring
different options for in-vehicle and vehicle-to-vehicle communication. Server-based
systems proved to be the most suitable and practical for buses and transportation
companies. Data communications between vehicles and a central server were also
examined, including such options as GPRS and @450 networks. In terms of technology, the @450 network proved to be the best solution, because it enables stable and
fast connections.
Ensuring information safety is critical in information infrastructures. According to
the study, possible and probable threat scenarios need to be developed and proper
safety architecture must be created for the system already in the planning stage. Information safety is particularly important, if the networks are connected to in-vehicle
systems, as malicious attacks can then be propagated to a level that threats safe use
of the vehicle by e.g. voiding the control of ABS brakes. Based on the study, telematics services should be implemented using common web interfaces, because they include embedded information security services already by default.
5.5.2
Preliminary study on the intelligent truck
After the preliminary study on the intelligent bus was completed, a preliminary study
on the intelligent truck was initiated. This study is still in its early stages, with no results available at this point.
5.5.3
Planning and implementation of the in-vehicle data acquisition system
During the autumn of 2009, specifications and a set of requirements were prepared to
determine which data the information acquisition system must be able to measure
and collect. This specification of requirements defines the necessary connections,
sensors and GPS navigation functionalities, as well as properties related to the user
interface, manageability, information storage and forwarding using wireless data
connections. Special attention was paid to ensure the performance of the vehicle
computer and the related software. The study also covered the information management, storage and processing properties required by the remote server. This was
complemented by defining the requirements that the needed software development
sets on hardware, libraries and computing environments.
Based on the specification of requirements, VTT issued a public invitation for tenders on in-vehicle data acquisition systems, and now a supplier has been selected. In
addition, a decision has been made on the in-vehicle sensors.
After the in-vehicle devices have been delivered and installed, the development of
the slip detection system will continue, and the development of the load estimation
method will begin on the basis of the data received from the vehicles.
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6
Actual performance and service-life management of heavyduty vehicles (VTT, Turku University of Applied Sciences)
6.1
General
Heavy-duty vehicles have a long service life, typically over 20 years. This subproject covers matters related to the service life of existing and new vehicles in terms
of energy efficiency, environmental properties and safety.
Because exhaust gas emissions certification for heavy-duty vehicles is based on engine tests, there are no emission or fuel consumption standards or rules for complete
heavy-duty vehicles. However, VTT has developed a method based on chassis dynamometer measurements that enables accurate measurements of fuel consumption
and actual exhaust emissions, and thus vehicle-to-vehicle comparisons. VTT’s methodology has been described in detail in the reports of the previous research stages,
and will not be discussed extensively in this report.
Many transportation companies use VTT’s comprehensive measurement data when
selecting vehicles. Over the years VTT has seen that the competitiveness of various
vehicle brands change with changes in emission regulations. Thus every new set of
emission standards will pose a new competitive situation.
During the first year of the HDENIQ project, the research on new vehicles focused
on 60-ton trucks and city buses. The project also included a special vehicle type: hybrid city bus. The analyses of the test results related to emission measurements of unregulated species are still in progress, and the results will be reported in the next report. The methodology of the measurements, however, will be discussed in this report. In addition, retrofitted emissions control systems for buses were tested on
VTT’s chassis dynamometer.
6.2
Emission and fuel consumption measurements for new vehicles
6.2.1
Trucks
In 2009, measurements were carried out on 60-ton trucks that meet the Euro V emissions standards. The vehicle database was updated with a total of five new trucks:
•
•
•
•
•
Mercedes Benz Actros 2544L (SCR)
Scania R440 (EGR)
Scania G420 (SCR)
DAF 105.46 (SCR)
Volvo FH440 (SCR)
Scania is quite a unique OEM in the sense that it offers engines using either EGR or
SCR technology for the same vehicle class.
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Earlier measurements carried out on 42-ton Euro V vehicles were already reported as
part of the RASTU project (VTT-R-04084-09).
New electronic anti-slip traction control systems make it more difficult to carry out
measurements on trucks, because manufacturer-specific testing and diagnostics devices are often required simply to be able to run the vehicle on a chassis dynamometer. This is the case when only the wheels of the driving axle are rotating, the vehicle’s control system interprets this as an abnormal situation and the vehicle may go
into a limp-home mode. In addition, gear-shifting logic presents problems: anti-slip
systems must be disabled when using a chassis dynamometer, and this may affect the
gear-shifting logic.
Normally VTT tests trucks using three different driving cycles and three load levels:
• distribution
• highway
• freeway (cruise control and constant speed)
• unladen, half load and full load
In this context it was not possible to test all of the vehicles on the distribution cycle,
as this would have required optimal gear-shifting performance. Because of the timeconsuming nature of the problems related to the chassis dyno testing, it was not possible to test all loads on all of the vehicles within the given timeframe.
According to the measured data, there were significant differences in fuel consumption between different makes in both the highway cycle and the freeway cycle. The
differences, however, were ambiguous. The differences between the makes varied by
cycle and by load. In the highway cycle, the biggest difference was recorded with
half load, with the difference between the lowest and highest fuel consumption figure
being about 9%. On average, however, all tested Euro V vehicles consumed less fuel
and slightly more urea than the Euro IV vehicles tested previously.
The following graphs present the aggregated sum of fuel and urea (“adblue”).
Figures 9 and 10 show the average fuel consumption of the Euro V vehicles. According to the data depicted, average fuel consumption of the Euro V vehicles is lower
than that of the Euro IV vehicles with all loads. In fact, the trend goes down from
Euro III to Euro IV to Euro V. On average, the Euro V vehicles consumed 2.5%
(highway cycle) to 3% (freeway cycle) less fuel than the corresponding Euro IV vehicles. The average urea consumption of the Euro V vehicles was 12 - 18% higher
than that of the Euro IV vehicles.
In the case of Scania trucks, the EGR and the SCR versions give roughly the same
aggregate fuel and urea consumption, with the exception of the freeway cycle with
full load, where the EGR variant presented the lowest value of all tested vehicles.
When moving from Euro IV to Euro V emission limits, the limit value for nitrogen
oxide (NOx) emissions goes down from 3.5 to 2 g/kWh. In SCR vehicles, this reduction is achieved simply by increasing urea injection and adjusting the engine.
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Fuel and adblue consumption (l/100km) 60t over highway cycle
Average Euro III
DAF 105.46 Euro V SCR
Scania G 420 Euro V SCR
Average Euro IV
Volvo FH Euro V SCR
Scania R 440 Euro V EGR
Average Euro V
MB Actross 2544 Euro V SCR
60
Consumption (l/100km)
50
40
30
20
10
0
25 640 kg
40 525 kg
60 000 kg
Test weight
Figure 9. Fuel and urea consumption of 60-ton vehicles over the highway cycle.
Fuel and adblue consumption (l/100 km) 60t over freeway cycle
60
Average Euro III
DAF 105.46 Euro V SCR
Scania G 420 Euro V SCR
Average Euro IV
Volvo FH Euro V SCR
Scania R 440 Euro V EGR
Average Euro V
MB Actross 2544 Euro V SCR
Consumption (l/100km)
50
40
30
20
10
0
25 640 kg
40 525 kg
60 000 kg
Test weight
Figure 10. Fuel and urea consumption of 60-ton vehicles over the freeway cycle.
The modifications actually lead to a decrease of NOx emission compared to Euro IV
vehicles Figures 11 and 12 depict the results of NOx and PM (particulate matter)
emissions over the highway and freeway cycles with different loads. In addition, the
diagram includes a line that represents limit values of the ETC exhaust emission test
multiplied with a factor of 1.5. This factor represents the losses caused by the power
transmission line, tyres and auxiliaries of the vehicle. However, this is only a rough
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estimate, because the loss factor depends on, among other things, the load level and
driving cycle. Using this factor, the limit value for NO x emissions in terms of type
approval, 2 g/kWh, is shown as 3 g/kWh, and so on.
PM & NOx emissions 60t over highway cycle
Euro4 ETC limit x 1.5
Average Euro IV
DAF 105.46 Euro V
Volvo FH Euro V
MB Actros 2544L Euro V
Scania G 420 Euro V
Scania R 440 Euro V
6
5
NOx (g/kWh)
4
3
2
1
0
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
PM (g/kWh)
Figure 11. PM and NOx emission results over the highway cycle with different loads.
PM & NOx emissions 60t over freeway cycle
Average Euro IV
DAF 105.46 Euro V
Volvo FH Euro V
Scania G 420 Euro V
Scania R 440 Euro V
6
5
NOx (g/kWh)
4
3
2
1
0
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
PM (g/kWh)
Figure 12. PM and NOx emission results over the freeway cycle with different loads.
Figures 13 and 14 show NOx emissions. Over the highway cycle, the NOx emissions
of the Scania vehicle with SCR-engine were quite high compared to the lowest values measured (Figure 13). No particular explanation was found for this phenomenon,
and the expectation was that the SCR vehicle would perform better with respect to
NOx. Over the freeway cycle the emissions of the Scania SCR vehicle were on a par
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with the other makes, whereas the Scania EGR vehicle recorded the highest NOx
values. A peculiarity of the Volvo vehicle was high NOx with unladen vehicle,
whereas the Mercedes-Benz Actros gave the lowest NOx emissions.
NOx emissions [g/kWh] 60 t truck, Highway cycle
Average Euro III
Average Euro IV
Average Euro V
DAF 105.46 Euro V
Volvo FH Euro V
Scania G 420 Euro V
Scania R 440 Euro V
0
10
9
8
NOx [g/kWh]
7
6
5
4
3
2
1
0
25 640 kg
40 525 kg
60 000 kg
Test weight
Figure 13. NOx emission results over the highway cycle with different loads.
NOx emissions [g/kWh] 60 t truck, Freeway cycle
Average Euro III
Average Euro IV
Average Euro V
DAF 105.46 Euro V
Volvo FH Euro V
Scania G 420 Euro V
Scania R 440 Euro V
0
10
9
8
NOx [g/kWh]
7
6
5
4
3
2
1
0
25 640 kg
40 525 kg
60 000 kg
Test weight
Figure 14. NOx emission results over the freeway cycle with different loads.
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Compared to the Euro IV vehicles, the tested Euro V vehicles in general performed
well in terms of exhaust emissions. In fact, all vehicles were either within or very
close to the Euro V “box”(see Figures 11 and 12).
6.2.2
City buses
6.2.2.1 Full-size buses
The bulk of the emission results in VTT’s data base for buses have been generated
using the Braunschweig bus cycle and simulating half load on VTT’s heavy-duty
chassis dynamometer. Measurements are carried out to establish the performance
level of new bus types as well as to establish the emission stability of vehicle already
in service.
In addition to testing on the chassis dynamometer, VTT will carry out on-road emission measurements. In 2009, plans were made for a measurement campaign that will
take place in 2010. The results will be reported in 2011. The measurements will be
carried out using PEMS (Portable Emission Measurement System) equipment.
As for measurements on the chassis dynamometer, in 2009, measurements were carried out on the following nine city buses:
•
•
•
•
•
•
•
•
•
Volvo Euro II fitted with a pDPF
Volvo Euro V (SCR)
Volvo EEV (SCR)
Scania Euro IV (EGR)
Scania EEV (EGR + pDPF)
Iveco EEV (SCR + DPF)
MAN CNG (2-axle, stoichiometric)
MAN CNG (3-axle, lean-mix)
Solaris Urbino 18 (a hybrid articulated bus)
The Polish Solaris hybrid bus was equipped with a hybrid system from Allison
Transmission Inc., and an engine from Cummins Inc.
Figures 15 and 16 show emissions of NOx and PM over Braunschweig-cycle as a
function of driven distance for EEV certified vehicles participating the follow-up
measurements.
According to Figure 15, the NOx emissions of the SCR buses seem to vary relatively
strongly from test to test. Possible reasons for these variations are malfunctioning
urea systems and the sensitivity of the SCR system operation to exhaust temperatures. Furthermore, for an unknown reason, the NOx emissions of the natural gas bus
using a combination of stoichiometric and lean-mixture combustion were also extremely high at about 100,000 kilometres. On the other hand, fully stoichiometric
natural gas buses deliver extremely low NOx emissions up to about 350,000 kilometres, after which their emissions increase, and gradually reach the levels recorded for
diesel buses. Potential causes for this behaviour include degradation in the three-way
catalytic converter or faults in the closed-loop lambda control system of the engine.
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A survey of the service records of the vehicles will be included in future studies to
give additional information on the possible causes of deterioration of the emission
performance.
NOx emissions in Braunschweig cycle with EEV vehicles
SCR
EGR
10.0
SCR+DPF
9.0
Stoich. (CNG)
Nox emissions g/km
8.0
Lean burn
(CNG)
Lean mix
(CNG)
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
500000
Odome te r reading (km )
Figure 15. NOx emissions over the Braunschweig cycle as a function of accumulated
kilometres. Please note: The diagram includes several individual vehicles.
Figure 16 shows that the PM emissions of the EEV-level EGR bus increase dramatically after about 100,000 kilometres. In practice, the PM emissions of this EEV bus
are on a par with those of Euro III vehicles (0.195 g/km on average). This phenomenon is not explained by the recorded test conditions, nor have the track records and
service histories of the vehicles been examined yet, because of poor availability of
information. Thus, it remains an anomaly to date.
However, the PM emissions of natural gas vehicles were extremely low throughout
the test period. The PM emissions of the bus equipped with an SCR + DPF system
also remained low at least up to 200,000 kilometres, which is the highest odometer
reading tested to date.
The tests also included a Euro II bus equipped with a pDPF particulate filter, a Euro
V SCR bus and a Euro IV EGR bus. Figure 17 shows the NOx emissions of these
vehicles with different amounts of accumulated kilometres. The Euro V SCR bus recorded exceptionally high NOx emissions because of a fault in the SCR system that
was found and fixed after the tests. Nonetheless, the results serve as an overview of
the emission levels of Euro V vehicles, when the SCR system is disabled, or when
urea cannot be injected because of off-limit operating conditions, e.g. too low exhaust temperature. However, NOx emissions of the other vehicles remained stable
throughout the test period. These vehicles will no longer be monitored after 2009. Instead they will be replaced with newer vehicles wherever possible.
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PM emissions in Braunschweig cycle with EEV vehicles
SCR
EGR
0.250
SCR+DPF
Stoich. (CNG)
PM emissions g/km
0.200
Lean burn
(CNG)
Lean mix
(CNG)
0.150
0.100
0.050
0.000
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
500000
Odom eter reading (km)
Figure 16. PM emissions over the Braunschweig cycle as a function of accumulated
kilometres. Please note: The diagram includes several individual vehicles.
NOx emissions in Braunschweig cycle
SCRsystem
fault
16.0
SCRjärjestelmässä
vikaa
14.0
Nox emissions g/km
12.0
10.0
8.0
6.0
SCR Euro 5
4.0
EGR Euro 4
2.0
pDPF Euro 2
0.0
0
100000
200000
300000
400000
500000
600000
700000
Odom eter reading (km )
Figure 17. NOx emissions over the Braunschweig cycle as a function of accumulated
kilometres.
Figure 18 plots the PM emissions from the same buses as before as function of accumulated kilometres. Figure 18 shows that the PM emissions of the Euro V SCR
bus remained quite stable over the accumulated 230,000 km of driving. However, the
PM emissions of Euro IV EGR bus increased by over 50% after 200,000 kilometres
compared to the first measurement at 100,000 km. Nevertheless, at 370,000 kilometres, the PM emissions were again slightly lower than in the previous measurement,
but still considerably higher than the initial level. The measurements at the highest
kilometres (470,000 km) rendered again the highest PM-levels. No solid explanation
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for this kind of behaviour could be reinstated, but certainly this was not due to any
variations in the test conditions.
The PM emissions of the Euro II bus equipped with a pDPF particulate filter have
remained very low since the installation of the filter. Compared to the initial level,
the pDPF particulate filter produced a reduction of about 55% in PM emissions.
PM emissions in Braunschweig cycle
0.18
0.16
PM emissions g/km
0.14
0.12
0.10
0.08
SCR Euro 5
0.06
0.04
EGR Euro 4
0.02
pDPF Euro 2
0.00
0
100000
200000
300000
400000
500000
600000
700000
Odom eter reading (km )
Figure 18. PM emissions over the Braunschweig cycle as a function of accumulated
kilometres.
In late 2009, Veolia and Helsinki Region Transport carried out a field-test of an articulated Solaris hybrid bus in normal revenue service. In addition, its exhaust emissions were measured using VTT’s chassis dynamometer.
Figure 19 is a structural diagram of the Solaris hybrid bus. It is an 18-metre-long articulated vehicle with a total weight of 28 tons. The bus has a Cummins ESB6.7
250B diesel engine with a maximum power output of 181 kW. The engine is
equipped with an SCR exhaust after-treatment system. The hybrid system, manufactured by Allison Transmissions, consists of two electric motors, two synchronous
clutches and three planetary gearings. The system includes nickel-metal hydride
(NiMH) batteries with a total weight of 437 kg. As for the working principle, the
EP50 hybrid system is a parallel hybrid system.
The Solaris hybrid bus was tested in late 2009. Figure 20 shows the fuel consumption
of the hybrid bus with two different payloads (22.5 tons represents a half-load for an
articulated bus, and 19.3 tons represents a half-load for a 3-axle bus). The typical
load of a 3-axle bus was included to make comparisons possible. VTT’s bus database
is mostly built on results for 2-axle buses, as the number of 3-axle buses that have
been measured is limited. However, the results of 2-axle buses can be extrapolated
with good accuracy to represent 3-axle buses, taking into account vehicle weight.
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Figure 20 also includes the average value of all 3-axle buses measured at VTT, and
in addition estimates of “what would be”values for newer 3-axle Euro IV and EEV
vehicles. Over the Braunschweig cycle, the fuel consumption (proportionate to
weight) of the Solaris hybrid bus was 20% lower than that of the EEV city buses and
24% lower than that of the Euro IV city buses on average.
Figure 19. Structural diagram of the Solaris hybrid bus.
Fuel consumption l/100km
60
Fuel consumption on
Braunschweig-cycle of 3-axle busses (estimated from 2-axle bus
results)
Estimated results
50
40
30
20
10
0
Solaris hybrid, Euro5,
22.5 ton
Solaris hybrid, Euro5,
19.3 ton
3-axle average,19.3 ton 3-axle (estimated from 3-axle (estimated from
2-axle results) Euro 4
2-axle results) EEV
average, 19.3 ton
average, 19.3 ton
Figure 20. The fuel consumption of the Solaris hybrid bus with two different loads;
average value for all 3-axle buses measured by VTT (includes older vehicles and
therefore not representative) and esitmated values for newer 3-axle Euro IV and
EEV buses (based on the results recorded for 2-axle buses).
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Table 1 shows the updated emission factors for 2-axle city buses in the Braunschweig cycle. The corresponding factors for the Helsinki 3 cycle (developed by
VTT) are presented in Table 2. The tables show the average regulated emissions and
fuel consumption of the city buses tested by VTT.
Table 1. Emission factors for city buses in the Braunschweig cycle.
Braunschweig
CO
g/km
HC
g/km
CH4*
g/km
NOx
g/km
PM
g/km
CO2
g/km
CO2 eqv
FC
g/km
kg/100km
FC
MJ/km
Diesel Euro I
1.39
0.32
0.00
15.59
0.436
1219
1219
38.6
16.4
Diesel Euro II
1.48
0.19
0.00
12.94
0.202
1270
1270
41.0
17.4
Diesel Euro III
0.79
0.15
0.00
8.57
0.190
1182
1182
38.0
16.2
Diesel Euro IV
2.77
0.11
0.00
8.32
0.116
1197
1197
38.6
16.4
Diesel Euro V**
2.77
0.11
0.00
8.32
0.094
1197
1197
38.6
16.4
Diesel EEV
0.93
0.03
0.00
6.12
0.071
1126
1127
36.9
15.7
CNG Euro II
4.32
7.12
2.33
16.92
0.009
1128
1283
42.1
20.7
CNG Euro III
0.15
2.14
1.70
9.82
0.013
1222
1271
45.1
22.1
0.91
3.34
0.007
1251
1272
45.0
21.9
CNG EEV
2.73
1.08
* For diesel CH4 = 0
** Euro 5 emission factors are estimated by Euro 4 results
Table 2. Emission factors for city buses in the Helsinki 3 cycle.
Helsinki3
CO
g/km
HC
g/km
CH4*
g/km
NOx
g/km
PM
g/km
CO2
g/km
CO2 eqv
FC
g/km
kg/100km
FC
MJ/km
Diesel Euro I
1.12
0.26
0.00
12.63
0.353
988
988
31.1
13.2
Diesel Euro II
1.20
0.16
0.00
10.48
0.163
1029
1029
33.0
14.0
Diesel Euro III
0.64
0.12
0.00
6.94
0.154
957
957
30.6
13.0
Diesel Euro IV
2.24
0.09
0.00
6.74
0.094
970
970
31.2
13.2
Diesel Euro V*
2.24
0.09
0.00
6.74
0.076
970
970
31.2
13.2
Diesel EEV
0.75
0.02
0.00
4.95
0.058
912
913
29.7
12.6
CNG Euro II
3.50
5.76
1.89
13.70
0.007
914
1039
33.9
16.7
CNG Euro III
0.13
1.74
1.38
7.95
0.010
990
1030
36.3
17.8
0.73
2.71
0.006
1013
1030
36.3
17.6
CNG EEV
2.21
0.87
* For diesel CH4 = 0
** Euro 5 emission factors are estimated by Euro 4 results
6.2.2.2 Neighbourhood service traffic vehicles (small buses)
Helsinki Region Transport also provides services with smaller buses based on vans.
The service is called “Jouko”, and it is mainly targeted to serve local neighbourhoods
and it is running on a much relaxed schedule for easy boarding.
The Jouko cycle, which was designed to simulate neighbourhood service traffic in an
urban environment, was used for the first time at the turn of the year 2009/2010. The
design of the cycle is discussed in more detail in section 7 (Development of methodology). Comparative measurements were carried out on two Mercedes Benz Sprinter
vehicles owned by Helsingin Palveluauto. The purpose of this study was to compare
the performance of comparable diesel and CNG vehicles in conditions resembling
service traffic over the Jouko cycle.
The vehicles used in the tests were registered as passenger cars (M1), with the highest
gross vehicle weight (GVW) being 3,500 kg. However, the vehicles used in
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neighbourhood service traffic are typically registered as M2 vehicles, with the highest
GVW being 5,000 kg. For this reason, additional weight was simulated in the tests by
using inertia settings typical of M2 vehicles: empty vehicles were tested at 3,610 kg,
half-load setting was 4,305 kg, and a full load setting was 5,000 kg.
The diesel vehicle tested was the Sprinter CDI 315, and the CNG vehicle was the
Sprinter NGT 316. The latter was equipped with a bi-fuel system capable of using
both CNG and petrol. The engine is started using petrol, which is switched automatically to gas after sufficient running temperature has been reached. Both vehicles
were type-approved according to the regulations for M1/N1 vehicles (passenger cars
and vans), and represented Euro 4 emissions level. Even if their certification was
based on a dynamometer test, the emissions measured in the “Jouko”tests cannot be
directly compared to those recorded in approval measurements. The reason is that the
simulated vehicle weights in the “Jouko”comparison measurements were higher, and
the driving cycle differs considerably from that used in type approval measurements.
Fuel consumption was measured by weighing. The gas consumption of the CNG vehicle over the cycle was measured using a special weighing system provided by Inspecta (provider of inspection and certification services). The system is installed in a
trailer and designed for the inspection of natural gas refuelling stations.
Table 3 illustrates the emission and fuel consumption results for the diesel and the
CNG vehicle with different payloads. The results were as expected: the spark-ignited
CNG vehicle was less energy efficient, but it delivers lower NOx and PM values.
However, despite of the higher energy consumption, the CNG vehicle also delivered
lower CO2 emissions, due to more favourable fuel chemistry (C/H-ratio).
Table 3. Emission factors for diesel and CNG service traffic vehicles.
Load
Jouko cycle
Diesel vehicle w/o load
half load
full load
CNG vehicle w/o load
half load
full load
CO
HC
(g/km) (g/km)
0.023
0.020
0.043
0.017
0.051
0.011
0.035
0.021
0.020
0.022
0.027
0.000
NOx
PM
CO2
CO2 eqv
FC
FC
CH4
(g/km)
(g/km)
(g/km)
(g/km) (kg/100km) (MJ/km)
(g/km)
0.001
2.056
0.008 351.519
351.519
11.379 489.298
0.002
2.251
0.009 382.278
382.278
12.450 535.358
0.002
2.508
0.011 416.642
416.642
13.463 578.927
0.011
0.025
0.005 317.159
317.652
12.240 612.016
0.011
0.034
0.005 342.236
342.732
13.429 671.448
0.012
0.026
0.004 372.813
372.813
14.486 724.311
Figure 21 shows the PM emissions of the diesel and the CNG vehicle over the Jouko
cycle with different payloads. The diesel is equipped with a particulate filter, and
thus both vehicles have very low PM emissions. The PM emissions of the diesel vehicle grew slightly with increased payload. However, the CNG vehicle recorded opposite results in terms of load response. With an empty vehicle, the PM emissions of
the diesel vehicle varied considerably from test to test (several repetitive tests). This
raises the level of the average result. In the first test with an empty vehicle, the PM
emissions were close to those with full load. This observed scatter could be a result
of regeneration of the particulate filter during the cycle. On the other hand, during
the regeneration process, additional fuel is injected late in the combustion cycle in
order to raise exhaust gas temperature. However, no differences in temperatures were
detected between cycles, nor any distinct changes in fuel consumption were observed. Therefore, there was no clear evidence of regeneration.
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PM emissions in Jouko cycle with a service trafic bus
0.012
0.010
g/km
0.008
Diesel
0.006
CNG
0.004
0.002
0.000
W/O Load 3610 kg
Half Load 4305 kg
Fully Loaded 5000 kg
Test weight
Figure 21. PM emissions of diesel and natural gas vehicles over the Jouko
neighbourhood service traffic cycle.
Figure 22 shows the NOx emission results of the diesel and the natural gas vehicle.
Compared to the diesel-powered option, the natural gas vehicle had extremely low
NOx emissions. The difference was quite remarkable: the NOx emissions of the diesel vehicle were approximately 100 times higher. When the NOx emissions were
proportioned to the fuel consumption of full-size city buses, the emissions of the diesel vehicle were close to those of normal city buses. The emissions of the CNG vehicle, however, were significantly low despite similar proportioning. As a matter of
fact they were lower than found for ordinary full-size CNG buses.
Nox emissions in Jouko cycle with a service trafic bus
3.00
2.50
g/km
2.00
Diesel
1.50
CNG
1.00
0.50
0.00
W/O Load 3610 kg
Half Load 4305 kg
Fully Loaded 5000 kg
Test weight
Figure 22. NOx emissions of diesel and natural gas vehicles over the Jouko service
traffic cycle.
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Figure 23 shows the carbon monoxide (CO), hydrocarbon (HC) and methane (CH4)
emissions of the diesel and the CNG vehicle with a half-load. The natural gas vehicle
had higher hydrocarbon and methane emissions, and the diesel vehicle had higher
carbon monoxide emissions. However, one should consider that the emissions shown
in Figure 23 were fairly low. For this reason, they do not constitute a fully justified
basis for comparisons between the two types of vehicles. In the case of CNG, nontoxic methane was the dominating hydrocarbon component.
g/km
CO, HC and CH4 Emissions in Jouko Cycle with Half Load
0.050
0.045
0.040
0.035
0.030
0.025
0.020
0.015
0.010
0.005
0.000
Diesel
CNG
CO (g/km)
HC (g/km)
CH4 (g/km)
Figure 23. CO, HC and CH4 emissions over the Jouko cycle with a half-load.
Table 4 indicates that, based on the fuel consumption measurements (Table 3), the
two vehicles have almost equal fuel costs. The calculation was done using retail
prices in July 2010 (diesel 1.04 €/l and CNG 1.12 €/kg). The CNG vehicle gives
slightly lower fuel costs, the biggest difference was recorded with full load: 0.44
€/100 km. The lower efficiency of the CNG vehicle is compensated by lower fuel
prices.
Table 4. Estimated fuel costs for diesel and CNG vehicles with different loads.
FC (kg/100km)
Jouko cycle
Load
Diesel vehicle w/o load
11.379
half load
12.450
full load
13.463
CNG vehicle
w/o load
12.240
half load
13.429
full load
14.486
Diesel Price 1.04 e/l (www.polttoaine.net, 8.7.2010)
CNG Price 1.12 e/kg (www.gasum.fi, 8.7.2010)
Fuel Price
(e/kg)
1.238
1.238
1.238
1.120
1.120
1.120
Fuel Cost
(e/100 km)
14.088
15.415
16.669
13.709
15.040
16.225
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6.2.2.3 Unregulated emission measurements (full-size buses)
General information
The first set of analysis of the unregulated emissions of the newest Euro IV and EEV
vehicles was carried out in 2007 and reported in 2009 (Report VTT-R-04084-09).
The three city buses included in this analysis were:
•
•
•
Scania (EGR) Euro IV emission-level vehicle (model year 2006)
Iveco (SCRT) EEV emission-level vehicle (model year 2007)
MAN CNG (TWC), stoichiometric EEV emission-level vehicle (model
year 2007)
Unfortunately, this measurement campaign was unsuccessful in many respects. The
measured Scania (EGR) Euro IV vehicle recorded quite high emissions results. This
was particularly true for the PM emissions.
Moreover, the PAH analyses were marked by uncertainty, because the service provider for the analysis was changing during the measurement campaign. Thus the results were eventually deemed unsatisfactory. The mutagenicity tests also produced
surprising results: the Scania bus, which had high PM emissions, recorded a zero response in the Ames test. This result differs considerably from those recorded by earlier vehicles equipped with similar technologies. Thus, it was also rated inconclusive.
For these aforementioned reasons, a decision was made to perform the test series
again on similar vehicles at a later time. This became possible in 2009 as part of the
HDENIQ research project. Also this time three city buses were tested in terms of unregulated emissions. The vehicles – a CNG vehicle and two diesel vehicles – were
two years younger (model years 2008 and 2009) than those used in the previous test.
All of the vehicles had EEV emission certification. In this campaign the following
three city buses were tested:
• Scania (EGR + pDPF) EEV emission-level vehicle (model year 2008)
• Volvo (SCR) EEV emission-level vehicle (model year 2009)
• MAN CNG (TWC), stoichiometric EEV emission-level vehicle (model
year 2009)
These vehicles are described in Table 5. Again, the Scania EEV bus (model year
2008) recorded very high PM emission levels, although the vehicle was equipped
with a particulate catalyst.
Table 5 also includes the selection of unregulated emission analyses. The special
emission measurements were carried out as described in the report VTT-R-04084-09.
Gaseous phase:
• hydrocarbon analysis for C1–C8 compounds (up to toluene, GC analysis)
• aldehydes (DNPH sampling, HPLC analysis)
• ammonia NH3 (on-line FTIR analysis)
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Particulate phase:
• particulate size distribution (ELPI) and total number (CPC)
• PAH (polyaromatic hydrocarbon compounds) analysis of the particulate matter
• Ames mutagenicity test for particulate matter
Table 5. The regulated and unregulated emissions analysed in 2009 from EEV emission-level city buses.
Make
MAN
Volvo
Scania
Make
MAN
Volvo
Scania
Make
MAN
Volvo
Scania
Model
Displ.
Exhaust
Emission
TransMileage
Test
Year
[dm3] Aftertreatment
Level
Fuel
mission
[km]
Duty Cycle
Load
2009
11.9
TWC
EEV
CNG
A
71300 Braunschw. 50 %
2009
7.15
SCR
EEV
diesel
A
2008
8.87
EGR
EEV
diesel
A
Fuel Cons.
CO
HC
CH4
NOx
CO2
PM
NMHC
[kg/100km]
[g/km]
[g/km]
[g/km]
[g/km]
[g/km]
[g/km]
[g/km]
44.1
1.41
0.39
0.26
0.85
1230
16.6
0.13
35.6
3.87
0.02
0.00
5.99
1089
47.3
0.03
37.8
0.53
0.02
0.00
6.83
1171
149.8
0.02
PM (h.c.) Gaseous
CPC
FTIR
PM
PAH
Ames
Aldehydes
[mg/km]
HC
# (>7 nm) multicomp High Capacity
PM filter Mutagenicity
1.25
x
x
x
x
(x)
38.1
x
x
x
x
x
x
x
147.3
x
x
x
x
x
x
x
(x) very low filter loading
It should be noted that the semi-volatile matter (in between the gas phase and particulate phase) is not collected and analysed as part of current procedures. However,
semi-volatile matter is known to contain, for example, high amounts of 2–4-ring
PAH compounds. EPA has a sampling technique (EPA202a) for collecting all of the
matter condensed after the vehicle particulate filter for closer analysis. This is the
only way of estimating the organic ingredients of exhaust gas as a whole, and the effects of exhaust gas on human health and the atmosphere. Provisions how to include
this type of sampling also in VTT’s arrangement are being studied.
Discussion on PM measurements
The CNG bus has very low PM emissions, which are very difficult to measure in accordance with the appropriate standards. Table 6 shows that standard particulate
mass measurements produce results that are 10–15 times higher than the PM emissions calculated from the results obtained using a proprietary in-house particulate
measurement system based on large-capacity collection: that is, 17 mg/km vs. 1.25
mg/km for emissions that have not been corrected for background concentrations.
For this reason, the PM emission results, and especially analyses based on the standard PM measurement method, should be treated with great reservations. The differences in emission levels are systematic and have also appeared earlier. However,
there is no certainty about the reason. The background PM contents collected by the
standard filter, which were achieved by introducing clean dilution air through the
tunnels and simulating a driving situation, varied between 5 and 13 mg/km, and the
uncorrected PM emission results varied between 12 and 21 mg/km. Therefore, the
actual PM emissions of the CNG vehicle can be anything between 0 and 16 mg/km.
The filter types and flow velocities at the filter face are within the tolerances of the
norms in both collection methods.
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Table 6. PM emissions of EEV city buses tested in 2009, including comparison of
standard PM method vs. high-capacity sampling. BR= Braunschweig bus cycle,
ADEME= Paris bus cycle (low-speed).
Make &
Fuel
Exhaust
aftertreatment
MAN 2009
CNG
TWC
gas tunn b.g. - 1
gas tunn b.g. - 2
DIKC 0/-10
Volvo 2009
Emission
level
Test
cycle
EEV
Br
Br
Br
Br
Br
Br
Br
Br
Br
Br
Br
Br
Br
Ademe
Ademe
Br
Br
Br
(no b.g. corrected)
EEV
SCR
diesel tunn b.g.
Scania 2008
DIKC 0/-10
EGR (+ox cat)
Scania 2009
DIKC 0/-10
EGR (+ox cat)
diesel tunn b.g.
1)
2)
1)
PM(mg/km)
standard
EEV
EEV
2)
PM (mg/km)
high capacity
(no b.g. corrected)
12.3
20.8
21.4
20.5
12.2
14.9
9.4
12.9
51.5
43.1
5.1
147.4
152.3
187.3
206.0
37.9
41.3
n.d.
2.0
1.1
0.93
1.7
0.85
0.91
0.65
0.17
38.3
37.8
1.8
150.2
161.4
204.0
232.1
33.9
39.0
2.5
PM high capacity PM standard /
mass on filter
PM high capacity
mg
%
0.233
0.130
1068 %
0.107
0.193
1593 %
0.098
0.105
1540 %
0.089
0.024
3.521
3.473
124 %
0.247
10.383
11.196
96 %
9.090
10.303
90 %
3.055
3.510
109 %
0.369
TX40 teflon coated glass fibre filter, d=70 mm, 80 dm3/min & 47 cm/s
3
Fluoropore fluorocarbon membrane filter, d=130 mm, 300-500 dm /min & 38-63 cm/s
However, according to the literature, the TX40 filter used in the standard collection
method is known to catch some gas-like artefacts from the emissions, unlike the Teflon filter used in the large-capacity collection system. Furthermore, the sample matter collected was small in both the large-capacity and standard collections, between
0.1 and 0.3 mg. In the large-capacity PM collection, the background content was
high, representing 9–70 % of the particulate matter. Based on these findings, background concentrations must always be taken into account. In a parallel test, the background concentration observed using the large-capacity PM collector was 1.8 mg/km
(at a collection speed of 600 l/min) in the diesel tunnel. The background concentration of the standard collector was 5.1 mg/km (using 80 l/min flow). The table also
shows that the difference between the results of a standard and large-capacity collection disappears, as PM emission levels rise. The Scania vehicle recorded similar PM
emissions with both measurement methods.
One of the purposes of this subtask was to evaluate the reliability of particulate
measurements and analyses related to low-emission vehicles; that is, the overall relevancy of specifications. Thus, the results can be rated excellent for this purpose.
For the sake of comparison, Table 6 also includes the emission levels of a new
Scania EEV bus (25,000 kilometres, model year 2009). Based on the results we can
assume that the after-treatment devices of this bus are still fully operational. The PM
emissions of the 2008 EEV vehicle were 150 mg/km, as opposed to the PM emissions of 40 mg/km of the 2009 EEV vehicle, over the Braunschweig test cycle.
More detailed PM and gas analyses are still in progress, and will be reported in 2010.
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6.2.2.4 Retrofitted exhaust after-treatment devices
The first year of the HDENIQ project also included testing of retrofitted exhaust gas
after-treatment systems. The main focus was on Proventia Emission Control’s SCR
catalyst (selective catalytic reduction) system with urea-based reduction agent. The
SCR system was tested as such, and in combination with devices for PM reduction.
A Euro III emission-level Volvo B7RLE city bus was used as test platform. The performance of the equipment in various configurations was verified through chassis
dynamometer measurements (Figure 24). The SCR as such also will undergo fieldtesting in Oulu during 2009 and 2010 at the Koskilinjat transportation company. The
tests will focus on system operation in real-life city traffic.
Figure 24. Testing of the combined SCR + DPF system in a city bus
The Volvo Euro III vehicle was first tested in its original state (baseline), without the
exhaust after-treatment equipment. In terms of the initial performance level, the vehicle was a rather high emitting specimen of its class. Its PM emissions were extremely high: over 0.6 g/km vs. 0.195 g/km, the average value for all tested Euro III
vehicles. After the baseline measurement, the following combinations were installed
and tested on the vehicle:
•
•
•
SCR only
SCR + DPF (actual wall-flow filter)
SCR + DOC (Diesel Oxidising Catalyst).
All tests were carried out over the Braunschweig cycle, because it represents typical
city traffic in the Helsinki metropolitan area. Moreover, VTT’s emission database is
also based on the Braunschweig cycle.
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The “gain”value of an SCR system portrays the relation between the amount of injected urea and engine-out NOx emissions: the higher the “gain”value, the higher the
amount of injected urea in proportion to NOx emissions. Determining the optimal
amount of urea injection is important because the properties of the SCR catalyst and
exhaust temperature have a considerable effect on the reduction efficiency. Figure 25
shows that a “gain” value of 0.8 produced an optimal of NO x emissions and urea
consumption. The SCR + DPF combination, and using gain 0.8 in urea feed, reduced
NOx emissions of the vehicle by about 75% and PM emissions by more than 95%.
Judging by these results, the combined SCR + DPF retrofit system made by Proventia is able to lower the exhaust emissions of a Euro III bus to true EEV level, a level
considerably lower than the average of the EEV diesel buses measured at VTT.
SCR, DPF and DOC combinations with various gain
14.0
12.0
NOx (g/km)
10.0
8.0
6.0
4.0
2.0
0.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
PM (g/km)
Euro2 limit x 1.8
Baseline
Gain:0.8 DPF+SCR
Other Euro 3 Volvos
Euro3 limit x 1.8
Gain:0.8 SCR
Gain:0.9 DPF+SCR
Gain:0.8 DOC+SCR
Gain:1 DPF+SCR
Gain:0.7 DPF+SCR
EEV / Euro 5 average
Figure 25. PM and NOx emissions over the Braunschweig cycle.
Fuel consumption increased by about 2.5% because of the SCR + DPF combination,
with urea consumption being about 3% of fuel consumption. The results are available
as a separate report (VTT-R-01293-10).
6.3
Vehicle maintenance
6.3.1
General
Maintenance is closely related to the life cycles of vehicles. Old vehicles can be upgraded for example to reduce exhaust emissions. However, it is even more important
to ensure that vehicles continue to function as planned. In addition to increased fuel
consumption and emissions, vehicles that have not been serviced can pose safety
threats because of poorly maintained brakes, as an example. Therefore, an examination of the opportunities to improve the brake testing of heavy-duty vehicles at statutory technical inspections began in 2009.
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6.3.2
Brake checkups of heavy-duty vehicles at statutory vehicle inspections
(Turku University of Applied Sciences)
The brake testing methods used for statutory heavy-duty vehicle inspections in
Finland have been studied by collecting research results from different sources and
identifying development needs based on this information. Originally commissioned
by the Finnish Vehicle Administration Agency AKE, the most significant of these research projects were related to the specification of inspection requirements for trucks
and trailers equipped with electronically-controlled air brake systems (Rahkola &
Leppälä, 2005). The project included on-road deceleration measurements, which
were compared to traditional brake dynamometer measurements.
Based on the results, on-road deceleration measurements and dynamometer measurements are not comparable. The significance of the difference in terms of the reliability of results is a crucial issue that needs to be examined. The introduction of onroad deceleration measurements as an inspection method is a viable option, if the related practical problems can be resolved. On-road deceleration measurements, however, cannot completely replace dynamometer measurements, because axle-specific
brake forces still need to be checked using a dynamometer.
Research projects related to the reliability of the current brake measurements systems
have also been examined. These include tests carried out on brake dynamometers and
roadside inspection programmes using a test trailer, as well as a literature study as
part of a thesis completed at Turku University of Applied Sciences on the reliability
of two brake inspection programmes. The purpose of this section is to determine the
reliability of the current methods and compare them to possible alternative methods.
Development needs related to current methods are also considered in order to minimise uncertainty factors related to users and conditions.
Comparisons with inspection methods in other countries
Based on information received from authorities, vehicle inspection methods in the
other Nordic countries and in Europe are examined as part of a Belgian exchange
student’s thesis work. The intention is to include any applicable elements in the new
test method.
Processing of inspection and roadside inspection information
The results of roadside inspections have been examined in terms of detected brake
system faults. The recorded results only seem to contain generic information about
inspections, such as: “a fault was detected in the brake system.”The records do not
list specific types of faults. An organisation carrying out roadside inspections in
Southwest Finland has provided information on types of faults. This organisation is
not aware of any faults related to electric brake systems that would have been detected by indicator lights.
Statistics related to statutory vehicle inspections have been examined in collaboration
with the newly formed Finnish Transport Safety Agency (TraFi) in order to determine the component-specific distribution of detected faults. This work is still in its
early stages. The fault statistics to be received from the vehicle inspection company
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K1 Katsastajat will enable component-specific fault analyses. For electronically controlled brake systems faults recorded in the system are in practise indicator light malfunctions or faults indicated by the light. They can also be faults related to the EBS
modulator valve.
Statistical and system information received from repair shops
Matters related to electronically controlled brake systems and their inspection have
been and will be examined by interviewing repair shop staff. The transport company
Schenker Cargo will submit service history of its vehicles in Southern Finland, including information on all repairs made during 2009. Reliable brake inspection
methods have been examined in collaboration with repair shops in order to determine
the most relevant ones. One option is to include certificates issued by repair shops in
statutory inspection requirements.
Experiences collected from transportation companies
Experiences have been collected from transportation companies, especially from
drivers, mainly orally. The purpose is to receive information on how brake systems
work in practice. A written survey is currently being carried out at Schenker. Depending on the results, this research may be expanded to include other companies. In
addition, an engineering thesis related to this field is in progress.
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7
Reporting methods and evaluation of the effects of actions
(Tampere University of Technology, VTT)
7.1
General information
This sub-project consists of two sub-tasks. The first one explores the opportunities
for customer-specific determination and reporting of total emissions. The second one
develops methods for evaluating the effects of energy-saving measures.
7.2
Customer-specific determination and reporting of transportation
emissions
7.2.1
General description and goals
The project goals were defined in the application as follows: “The goal of the research project is to develop operating processes and technical systems that enable
accurate measurements of fuel consumption for Transpoint. The system is intended to
provide fuel consumption information related to specific transportation services. The
company can use this information to monitor fuel efficiency on many levels, both internally and externally. Above all, the system is intended to enable fuel consumption
monitoring specific to consignment notes, which will allow for the reporting of customer-specific carbon dioxide emissions, as well as other emissions, related to transport chains. This requires identifying the current and future needs of transportation
customers and the public sector in terms of reporting said emissions.”
7.2.2
Literature survey
The research began with a literature survey to find information on measurement
methods related to energy consumption data specific to transportation actions and
consignment notes. Judging by this literature survey, monitoring and reducing environmental effects has become an important part of corporate social responsibility.
This development is connected to political goals to control climate change. In
Finland, energy-efficiency agreements in different sectors serve as tools for improving energy efficiency and the related reporting. In addition, environmental awareness
is increasing among customers, and this development makes demands on reporting
related to the environmental effects of companies. In response to these demands,
some companies have set goals for labelling their products with carbon footprint information, and some of their products have been carbon audited. The public sector
has integrated the development of climate labels into climate policies.
None of the guidelines for the calculation of carbon footprints – such as PAS2050,
GHG Protocol and ISO 14064 – have become international standards. In addition,
these guidelines are fairly general in nature, leaving many important issues to be
solved by the companies performing the calculations. Environmental reporting also
poses challenges for the determination and reporting of the environmental effects related to logistics. Scope, focus, adjustments, costs and information availability pre-
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sent problems in the carbon auditing of supply chains. The division of emissions between customers, especially when running deliveries for multiple clients simultaneously, is a major problem in customer-specific environmental reporting. There are no
general guidelines, and different methods can produce very different customerspecific results in terms of emission calculation. Because of these problems, carbon
footprint information related to specific products is often treated with great scepticism. In some cases, this information is even seen as an obstacle to emission reductions that can be detected through carbon audits on the product chain level. Nonetheless, environmental labels specific to performance in transportation would increase
transparency and make it easier for customers to compare companies and different
forms of transportation. Customers would not, however, change transportation forms
because of environmental labels, and they are not willing to pay extra for having
such labels at their disposal.
7.2.3
Survey
A survey was carried out to study the needs of Finnish transportation customers in
terms of environmental reporting. The survey was intended for large and mediumsize (over 20 employees) Finnish companies in industry and trade. The contact information was submitted by the company MicroMedia. The survey was performed in
January and February 2010 using the Webropol application on the Internet. The invitation to participate in the survey was e-mailed to 2,273 managers or equivalents,
who were also offered the opportunity to forward the invitation. A total of 2,009 invitations were delivered successfully, and 115 companies submitted a response. Despite the relatively low response rate of 5.7%, the responses came from a diversity of
fields and companies. The results can be regarded as representative, although responding to surveys of this type may reflect attitudes that are more positive toward
the environment than those among the selected companies on average.
Based on the survey results, the majority of Finnish companies in industry and trade
have not yet encountered external demands related to environmental reporting. Large
companies, however, have internal demands related to such reporting. Moreover, the
companies do not require extensive environmental reporting from their subcontractors. The companies have been proactive, developing environmental reporting practices that exceed statutory requirements. Most of the companies project they will be
publishing an annual environmental report by 2016.
A total of 15 companies had calculated carbon footprints for specific products, encountering the same problems that have been presented in earlier studies. The companies felt a need for the standardisation of carbon footprint calculation methods.
Despite the problems, companies that already had carried out carbon audits believed
–clearly more strongly than others –that carbon footprint labels would become more
common. Responses to the question about the future of carbon footprint labels reflected a distinct uncertainty: one-third of the respondents did not regard such labels
as either probable or improbable. Responses to other questions about the future were
marked by the same uncertainty. Based on the responses, however, companies are
very willing to reduce their environmental effects, but they need more information
about the means to achieve this goal.
Companies felt a distinct need to further develop environmental reporting related to
transportation. They would like to receive more information, especially about carbon
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dioxide emissions, performance-specific fuel consumption and vehicle utilisation
rate. Based on the survey, very simple reporting methods, such as a quarterly spreadsheet with location-specific key figures, would be sufficient for many companies for
reporting the environmental effects related to transportation. In addition, the responses clearly showed that companies are not willing to pay extra for reporting, although they value and sometimes make demands on environmental reporting. Standardisation was regarded as important for ensuring comparability in terms of environmental reporting related to transportations.
Based on the results of the survey, the attitudes of Finnish companies in industry and
trade can be summed up as follows: companies want to further develop their environmental practices, but they are not willing to pay extra and need more information
on the means to achieve this goal.
7.2.4
Further plans
The analysis of the survey results will continue. The need for customer-specific environmental reporting will be evaluated on the basis of the survey results and the literature survey. Requirements will be specified for a new system that may be implemented. The requirement specifications can be used to devise the processes needed
for producing information and to develop the required information systems. Special
attention will be paid to the different options for calculating customer-specific emissions.
7.3
Evaluation of the effects of energy-efficiency measures
7.3.1
General description and goals
The project goals were defined in the application as follows: “The purpose of the
project is to create specifications for an evaluation model to determine the effects of
measures to improve energy efficiency. The energy service directive, as well as the
Finnish energy-efficiency agreements based on the directive, sets requirements for
improving the energy efficiency of public transport and goods traffic and for verifying the effects of energy-efficiency measures. The calculation principles used for
verification are unclear both on the national and company level. The project aims to
clarify these principles and determine requirement specifications for a calculation
application that can be used to evaluate the effects of energy-efficiency measures on
different levels. The specifications are intended to define the content of information,
user interface and to the applicability of the model.”
7.3.2
Literature survey
The project began with a literature survey that examined the requirements set for the
public sector and companies in terms of calculating and reporting the effects of energy-efficiency measures. The European Union’s energy service directive is the most
significant factor affecting the improvement of energy efficiency. In the national implementation of the directive, the most important tools are the energy-efficiency
agreements for public transport, goods traffic and logistics. The energy service directive describes energy efficiency as “a ratio between an output of performance, ser-
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vice, goods or energy, and an input of energy.”In public transport and goods traffic,
energy efficiency refers to the ratio between a transport action and energy consumption (person-km/kWh or tonne-km/kWh, respectively). These indicators are based on
a number of interacting factors, and they can be affected through many types of energy-efficiency actions (Figure 26).
Population
Need for mobility
[km/person/day]
Urban structure
Urban planning
Modes of travel [%]
Choice of travel mode,
attitudes
Mobility management
Routing
Route planning
Route optimization
Transport demand [pkm]
Energy efficiency [kWh/pkm]
Demand for public
transport [pkm]
Route performance
[pkm]
Route mileage [km]
Avg. load [persons]
Empty vehicle tranfers [%
route mileage]
Total mileage [km]
Energy use [kWh/km]
Total energy use [kWh]
Vehicle capacity
Vehicle occupancy
Vehicles according to
demand
Ages and sizes of vehicles
Traffic circumstances (other
traffic, road conditions)
Bus lanes and signal
priorities
Driving behaviour
Ecodriving training
Carbon content of fuel
[kg/kWh]
Type of fuel
New vehicle technology
Key ratios
Determinants
Efficiency measures
Total carbon dioxide
emissions [t]
Aggregates
Figure 26. Framework for evaluating the energy efficiency of public transport.
In conjunction with the implementation of the energy service directive, studies have
been carried out at the EU level to enhance the evaluation of the effects of energyefficiency measures. These studies have not been related to the energy efficiency of
heavy-duty vehicles. For this reason, there are no official listings of the effects of energy-efficiency measures. In Finland, the implementation of the energy-efficiency
agreement included the production of information on the effects of such measures,
but this objective was not met. Scientific literature includes countless studies on specific energy-efficiency measures and their effects, but the combined effects of these
measures have not been examined comprehensively.
Public-sector needs for the evaluation of the effects of energy-efficiency measures
are related to assessing the implementation of the energy service directive and the
energy-efficiency agreements in terms of achieved goals. Companies seek to expand
the knowledge base on which their investment decisions are based. Internal monitoring of energy consumption is a basic requirement for developing energy efficiency in
companies, and benchmarking with other companies can bring many types of mutual
benefits. These needs can be combined through an advanced national monitoring system that enables automatic data input from company systems and versatile reporting
based on comprehensive data provided by a single company or several companies.
The existing Finnish national systems, EMISTRA in goods traffic and ESS in public
transport, are insufficient for this purpose.
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7.3.3
The ETS databank on public transport
A national tool is currently being developed for monitoring the public transport energy-efficiency agreement in collaboration with several actors in the field. This tool,
the ETS databank, allows for recording vehicle performance and energy consumption
information, as well energy-efficiency measures, in a national system. This means
that the databank can be used to evaluate the effects of energy-efficiency measures,
which may motivate companies to adopt the system.
Issues related to the ETS databank and the energy efficiency of public transport will
be examined in the spring 2010 with interviews with client organisations and an
Internet survey for suppliers. The interviews that have already been completed indicate that client organisations feel a need to monitor the energy efficiency of public
transport in their areas. The ETS databank could be suitable for this purpose. In conjunction with the interviews, clients were also presented an idea related to marketing
energy-efficiency measures and evaluating their effects as part of the ETS databank
(Figure 27).
Figure 27. Evaluation of the effects of energy-efficiency actions.
Providers of measures for enhanced energy efficiency could have their products or
services evaluated by a third party through the ETS databank. Based on the evaluation, they could be given the right to promote their products or services within the
databank. Companies that decide to use these products or services could provide
valuable information on their actual effects. In goods transport, the EMISTRA system could be developed in this direction or replaced with the ETS databank.
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7.3.4
Future plans
A survey for public transport operators about energy-efficiency measures and the
ETS databank will be carried out during the spring 2010. Based on the responses,
suggestions will be made to enhance the evaluation of the effects of energyefficiency measures by using the ETS databank. In addition, resources allowing, research results related to the effects of energy-efficiency measures will be collected
from different sources to create a database.
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8
Development of research methodology (VTT)
There is no normative basis, and there are no standards or other mutually-accepted
guidelines for chassis dynamometer measurements performed for complete heavyduty vehicles. For this reason, VTT has developed its own measurement methods,
which were accredited by the Finnish accreditation body FINAS in 2003. Despite the
accreditation, these methods need to be further developed to improve their precision
and expand their application to a wider variety of vehicles.
Determination of driving resistances
VTT determines driving resistances for vehicles carrying out coast-down tests on a
specific straight highway stretch with a known elevation profile. The aerodynamic
performance (drag coefficient) and rolling resistance of a vehicle can be measured
relatively accurately in such highway coast-down tests.
Measurements to verify the elevation profile of the test road were carried out in
2009. Accurate measurements of this straight stretch in Nurmijärvi north of Helsinki
(Highway No 3) were needed for high-precision driving resistance determinations
aiming at, e.g., differentiating between air drag and rolling resistance. The earlier
specifications of the profile of the specific stretch were based on road profile information provided by the Finnish Road Administration. The data was based on the
original plan of the road, and not accounted any sagging or other deformation of the
structures over time.
A Trimble precision-GPS device was used for this test. The device consisted of a
central processing unit and a receiver (Trimble R8). In addition to satellites, the device uses land-based stations to determine locations. This enables a precision of 2
centimetres.
Coast-down
M itta s u otrack,
r a e te Southbound
lä ä n
79
78
78
k o rk e u s
Track elevation
[m]
77
77
76
76
T ie ha lli nto
T rim b le
75
75
74
74
3000
2800
2600
2400
2200
2000
1800
m a tk a
1600
1400
1200
1000
800
600
400
200
0
-200
73
73
-400
8.1.1
Track lenght [m]
Figure 28. Test road profiles based on data from the Road Administration and on
precision GPS data.
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The measurements performed on the test road proved that the profile received from
the Finnish Road Administration (Tiehallinto) was still accurate. Figure 28 shows the
congruence of the given profile and the one based on precision GPS measurements
on the southward lane of the road.
Determination of driving resistance was also improved through the acquisition of an
ultrasonic wind sensor. The wind sensor is used to determine wind speed (wind
speed in relation to the vehicle speed in coast-down tests) and direction angle. This
Vaisala WMT52 sensor is discussed in more detail in the following section.
8.1.2
New vehicle types
VTT’s vehicle database has not included drive resistance figures and driving cycles
for small buses typically used in neighbourhood service traffic. For this reason drive
resistance specifications for small buses were created in 2009, as well as a test cycle
that better represents their operating conditions. Furthermore, exhaust emission
measurements were carried out on actual buses by using this cycle on a chassis dynamometer. The results were discussed in Chapter 5.2.2.2 of this report.
On-highway coast-down tests on the neighbourhood service bus
The coast-down tests were performed using a small Mercedes-Benz bus based on the
Sprinter platform. The test vehicle is shown in Figure 29, with the Vaisala WMT52
wind speed sensor and the Trimble R8 GPS receiver installed on the roof. The wind
sensor was mounted on a support with the shape of a swan’s neck to prevent airstreams caused by the vehicle from disturbing the sensor.
Figure 29. The measurements were carried out using a Mercedes Benz Sprinter bus.
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The coast-down tests were carried out with two payloads: empty vehicle (3,610 kg)
and a payload that produced a total mass of 4,640 kg, which is close to the highest allowed mass of the vehicle (5,000 kg).
Figure 30 illustrates the total resistance for both loads, based on the coast-down tests.
The formulas for the curves depicted in the diagram are used to calculate the total resistance factors F0, F1 and F2 (constant, proportional to speed, proportional to square
of speed) that reflect those three main components if the resistance: resistances that
are constant, resistances that are proportional to the speed, and resistances that are
proportional to the square of the speed. The effect of the wind on air resistance was
calculated using information produced by the wind sensor. The effect of the force
generated by the wind component, in the direction of the vehicle, on the total resistance was considered when making the calculations.
Driving resistances of a Jouko service trafic bus
1600
Resistance force (N)
1400
1200
2
y = 0.0301x + 8.2322x + 438
1000
Poly. (Loaded)
Poly. (W/o load)
800
2
y = 0.0114x + 7.8745x + 364
600
400
200
0
0
20
40
60
80
100
Velocity (km/h)
Figure 30. Total resistances of unloaded and loaded Mercedes-Benz Sprinter bus in
the coast-down tests.
Figure 31 shows the curves describing the total resistances, as well as the related
formulas, excluding the effects of the light wind when the measurements were performed. Over the “Jouko”neighbourhood service cycle, which will be described in
more detail below, at a maximum speed of 45 km/h, the difference between the resistance forces is extremely low, less than 1 N, when comparing resistance values including and excluding the effects of the wind. At a speed of 80 km/h, the difference
between the resistance forces with an unladen vehicle is about 4 N. The relative difference, however, is insignificant.
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Driving resistance of a Jouko service line bus without wind effect
1600
Resistance force (N)
1400
2
y = 0.0311x + 8.1697x + 439.4
1200
1000
Poly. (W/o load)
800
y = 0.0138x2 + 7.6855x + 367.7
Poly. (Loaded)
600
400
200
0
0
20
40
60
80
100
Velocity (km/h)
Figure 31. Total resistances of the unloaded and loaded Mercedes-Benz Sprinter bus
in the coast-down tests, excluding the effects of the wind.
8.1.3
New driving cycles
Helsinki, Espoo and Vantaa have in total 44 different neighbourhood service traffic
lines. These service lines have been designed primarily for the needs of senior citizens, people with reduced mobility and people using mobility aids. For this reason,
service-line traffic differs considerably from typical city-bus traffic in the Helsinki
metropolitan area in terms of vehicles and driving patterns. The amount of
neighbourhood service traffic has increased in the Helsinki metropolitan area, which
calls for the identification of its environmental effects. To serve this purpose, VTT’s
selection of bus driving cycles was complemented in 2009 with the “Jouko”cycle,
which represents this service-line traffic.
The cycle is based on actual driving on the J32 city bus line in Helsinki. This information was recorded using the CAN bus of the vehicle and separate GPS positioning
data. Both terminals of the J32 line are located in Haaga sub-urban neighbourhood.
Figure 32 illustrates the route.
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GPS data of the Jouko driving cycle
60.238
Latitude
60.233
60.228
60.223
24.918
24.913
24.908
24.903
24.898
24.893
24.888
24.883
24.878
24.873
24.868
60.218
Longitude
Figure 32. “Jouko”route in Haaga.
Figure 33 shows the speed profile of the “Jouko” cycle as a function of time. The
“Jouko”cycle was designed on the basis of actual recorded data.
Jouko service trafic driving cycle
50
Driving speed (km/h)
40
30
20
10
0
0
200
400
600
800
1000
1200
Time (s)
Figure 33. Driving cycle illustrating service-line traffic (“Jouko”cycle).
Table 9 shows basic information for the new “Jouko”cycle. Compared to the Braunschweig cycle, which represents full-size city-bus line traffic in mid-size cities, the
“Jouko”cycle has a lower average speed (18.3 vs. 22.5 km/h in the Braunschweig
cycle) and a lower maximum speed (45 vs. 58 km/h in the Braunschweig cycle).
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Table 9. Key figures related to the “Jouko” cycle.
Average speed (km/h)
Maximum speed (km/h)
Distance (km)
Idle time (s)
18.3
45.0
6.12
145

Energy-efficient and Intelligent Heavy-duty Vehicle

Transcription

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