TUCRRC Presentation Tennessee 2014 9526KB Sep 13 2016

Transcription

Crash Data Presentation
Tennessee Crash Conference
2014
Tennessee 2014
http://tucrrc.utulsa.edu
2
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Order of Presentation

Crash Testing Setup


Review of EDR data from crash vehicles


Jeremy Daily, University of Tulsa
Rotational Mechanics Analysis


Brad Muir, Ontario Provincial Police
Heavy Vehicle EDR and Network Data


Joe Meier, Mechanical Engineering Student
EDR Data Analysis


Amila Perera, Mechanical Engineering Graduate Student
Patrick Tyrving, Mechanical Engineering Student
Closing Remarks

John Daily, ???
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Consortium Website

Research Topics of Interest



Vehicle Networks
Event Data Recorders
YouTube Videos

Channel = TheTUCRRC
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Amila Perera on
DATA ACQUISITION
SYSTEMS AND SETUP
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Racelogic VBox 3i





100Hz GPS system
Serial communication
Compact flash logging
Brake trigger
IMU


Tri-axial accelerometer
Tri-axial gyroscope
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Racelogic Video VBox




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10Hz/20Hz GPS system
4 Cameras
Microphone
Compact flash logging
8
Instruments

eGPS-200Plus
Combines data from 2 GPS antennas an IMU, and RTK
units to provide several measurements at a rate of up
to 200Hz


Measurements





Acceleration (All 3 axis)
Angular velocity (All 3 Axis)
Speed
Heading, altitude, longitude
Slip angle
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Instruments

Accelerometer



Tri-axial measurements
±70gs
10,000 Hz bandwidth
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Gyroscope



Tri-axial measurements
±600 deg/s rates
400 Hz bandwidth
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eDAQ Data Acquisition




Rugged system designed for use in harsh
environments
Enables simultaneous and synchronous
recording of multiple channels with different
types of instruments
Convenient data recording modes
Simple interface
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eDAQ
4 Layers

DIO
 Digital I/O


HLS
 High level analog

ECOM
 Vehicle network
communications
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eDAQlite

4 Layers



ELBRG
 Bridge
HLS
 High level analog
ECOM
 Vehicle network
communications
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eDAQ Data Recording
Modes

Time history


Records continuously
Burst history



Buffer data
Records data in a
predefined interval
Simplifies data
processing
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Interface (Web)



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Limited access
Manage networked
cameras
Quick test startup
15
VC4000DAQ



10Hz GPS
Brake pedal sensor
Tri-axial accelerometer

Used to determine drag coefficient
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Mounting the instruments in
the Envoy
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Power distribution board
eDAQ Lite
12V Power Supply
Vbox 3i
VVBox
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Mounting instruments in the
S10
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eGPS 200
Accelerometer
eDAQ Lite
12V Power Supply
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Power distribution board
VVBox
Vbox 3i
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Mounting instruments in the
trailer
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eDAQ
VC4000
Accelerometer
12V Power Supply
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Scene Mapping

Total Station (Carlson Robotic)


Distance measurements
Angle Measurements
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Crash Test Preparation
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Joe Meier on
PRESENTATION OF ACM
DATA FROM CRASH
VEHICLES
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Introduction

Air Bag Control Module Overview

Data from EDR

Reference accelerometer data

Data Analysis
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Air Bag Control Module
(ACM)


System in vehicles designed to protect
passengers during a car crash
Monitors crash sensors throughout the car in
order to determine deployment of air bags
and pretensioners
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ACM Components

Crash Sensors





Located in front, rear and sides of car
Detects narrow crash zones
Wakes up algorithm enable (AE)
More modern sensors can send acceleration
data to help in AE deployment decision making
Accelerometer in Air Bag Control Module

Generally in CG
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ACM Components

Air Bags and Seatbelt Pretensioners


Deploy based on AE decision making
Event Data Recorder (EDR)


Stores pre-crash data from vehicle
communication network
Stores crash data


Delta v
Time
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How the ACM works

ACM uses accelerometer to detect crash like
conditions


When these conditions are met, AE will activate
When activated, AE has two choices

Deploy air bags and pretensioners



Called deployment event
Data permanently stored to memory
Not deploy air bags and pretensioners


Called non-deployment event
Data not permanently stored to memory
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ACM Flow Process
Diagram
Crash sensors
measure acceleration
Crash-like
acceleration?
No
Yes
Activate AE
Deployment
Event?
Yes
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EDR records pre-crash data
from vehicle communication
network and crash data
No
No deployment
of airbag and
pretensioners
Deploy airbag and
pretensioners
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GMC Envoy Crash Video
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No Air Bag Deployment
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Photo of Non-deployment
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Photo of Non-deployment
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GMC Envoy Pre-Crash
Data
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GMC Envoy ABS and Δv
Crash Data
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GMC Envoy EDR Δv
GMC Envoy Δv vs. Time
CDR
0
-5
Δv (mph)
-10
-15
-20
-25
-30
-35
-40
-45
0
100
200
300
400
Time (ms)
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Chevy S10 Crash Video
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Chevy S10 Pre-Crash
Data
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Chevy S10 ABS and Δv
Crash Data
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Chevy S10 EDR Δv
Chevy S10 Δv vs. Time
CDR
0
-5
Δv (mph)
-10
-15
-20
-25
-30
-35
-40
-45
0
20
40
60
80
100
120
Time (ms)
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Combined EDR Δv
Chevy S10 and GMC Envoy Δv vs. Time
GMC Envoy
0
Chevy S10
-5
-10
Δv (mph)
-15
-20
-25
-30
-35
-40
-45
0
50
100
150
200
250
300
350
400
Time (ms)
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Accuracy of EDR Data

To test accuracy of EDR Data a reference
accelerometer was mounted behind the
passenger seat of the crash vehicle
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Reference Accelerometer


Each crash vehicle equipped with a triaxial
accelerometer
Measurements taken at 5000Hz
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GMC Envoy Crash
Acceleration Impulse
Chevy S10 Crash Impulse Acceleration
Accelerometer
80
60
Acceleration (g)
40
20
0
-20
0
50
100
150
200
250
-40
-60
-80
-100
Time (ms)
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Analyzing Accelerometer
Data

Solving for ΔV:
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Constant Acceleration
Example
Acceleration vs. Time
Acceleration (ft/s^2)
Acceleration
10
8
6
4
2
0
0
1
2
3
4
5
Time (s)
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Example
Acceleration
10
8
6
4
2
0
0
1
2
3
4
5
Time (s)
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Example
Acceleration
10
8
6
4
2
0
0
1
2
3
4
5
Time (s)
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Example
Acceleration
10
8
6
4
2
0
0
1
2
3
4
5
Time (s)
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GMC Envoy Crash
Accelerometer
80
60
Acceleration (g)
40
20
0
-20
0
50
100
150
200
250
-40
-60
-80
-100
Time (ms)
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GMC Envoy Crash
Accelerometer
80
60
1ms
Acceleration (g)
40
20
0
-20
0
50
100
150
200
250
-40
-60
-80
-100
Time (ms)
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Crash Impulse
Acceleration
Acceleration vs. Time (1ms)
Accelerometer
Acceleration (g)
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
0.2
0.4
0.6
0.8
1
Time (ms)
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Trapezoidal Rule
Acceleration vs. Time (1ms)
Accelerometer
Acceleration (g)
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
0.2
0.4
0.6
0.8
1
Time (ms)
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GMC Envoy Δv from
reference accelerometer
Accelerometer
0
-5
Δv (mph)
-10
-15
-20
-25
-30
-35
-40
-45
0
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100
200
Time (ms)
300
400
57
GMC Envoy Δv
comparison
Accelerometer
CDR
0
-5
Δv (mph)
-10
-15
-20
Maximum
recorded
velocity
change
-25
-30
-35
-40
-45
0
50
100
150
200
250
300
350
400
Time (ms)
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Chevy S10 Δv
comparison
Chevy S10 Δv vs. Time
Accelerometer
CDR
0
-5
Δv (mph)
-10
-15
-20
-25
-30
-35
-40
-45
0
50
100
150
200
250
Time (ms)
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Accuracy of EDR Data

Based on the data provided by the reference
accelerometer, the EDR Δv is accurate


Similar shape in Δv vs. time graphs validate EDR
data
Trend line can be used to extrapolate data
past the 150ms memory threshold
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GMC Envoy EDR Δv
CDR
0
-5
Δv (mph)
-10
-15
-20
-25
-30
-35
-40
-45
0
50
100
150
200
250
300
350
400
Time (ms)
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GMC Envoy EDR Δv with
Curve Fit
CDR
0
-5
Δv (mph)
-10
-15
-20
-25
-30
-35
-40
-45
0
50
100
150
200
250
300
350
400
Time (ms)
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GMC Envoy Δv with
Curve Fit
Accelerometer
0
CDR
-5
Δv (mph)
-10
-15
-20
-25
-30
-35
-40
-45
0
50
100
150
200
250
300
350
400
Time (ms)
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Brad Muir on
EDR DATA ANALYSIS AND
DISCUSSION
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ACM – Internal Components*
*Source: Chidester Paper – NTSB Symposia

Accelerometer



May have x and y
Low pass filter
Microcontroller

ROM – Contains program



RAM – Captures data
EEPROM or Flash Memory



Crash sensing and diagnostic
Crash Data and DTC info storage
Capacitors – Energy Reserve
Mechanical Safing sensor

Newer use Electronic Safing
Sensor
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Auxiliary Sensors




Additional sensors to assist in
decision making
Front / Rear and Side
Early sensors were
mechanical
Latest generation provide
acceleration data to ACM
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When do air bags deploy?


At the onset of an event, the ACM
detects acceleration sufficient to
wakeup the crash sensing /
decision making algorithm
Based on an evaluation of the
sensed acceleration, potentially
along information from auxiliary
sensors, the ACM makes a decision
to Deploy or Not Deploy the
supplemental restraints
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Predictive Decision Making

The ACM decision is anticipatory
based on pre-programmed criteria



“Jerk” and other criteria are evaluated
as long as the crash sensing algorithm
is awake
It does not / can not wait for some
minimum delta-v threshold to be
met
Deployment decision has to be
made early to allow time for airbag
inflation
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Ideal Airbag Deployment Timing

It is generally held the ideal decision
window is ~15-50ms to allow for airbag
inflation before occupant contact
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Deployment Decision Ideal Time Line
(Takata example)
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Delta-v at Deployment
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Time to Maximum Delta-v
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Decision Making Comparison
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Deployment Timing Example
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Less than ideal timeline
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When air bags may not
deploy
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SCARS 2013 – Crash #6
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SCARS 2013 – Crash #6

Crown Victoria

Impact Speed:



Delta-Vx:



38mph – VBox GPS (61 km/h)
38mph – CDR (PCM)
IST: -37.21mph @ 261ms
CDR: -36.31mph @ 656ms (Algorithm Run
Time)
Airbag (driver) deployed
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THP 2014 - Crash #1
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THP 2014 - Crash #1
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THP 2014 - Crash #1
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Leica ScanStation Data
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THP 2014 - Crash #1
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THP 2014 - Crash #1
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THP 2014 - Crash #1
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THP 2014 - Crash #1
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THP 2014 - Crash #1
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THP 2014 - Crash #2
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THP 2014 - Crash #2
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THP 2014 - Crash #2
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THP 2014 - Crash #2
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THP 2014 - Crash #2
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THP 2014 - Crash #2
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Jerk Defined

In physics:


Jerk = the rate of change of acceleration




also known as jolt, surge, or lurch
the derivative of acceleration with respect to
time
the second derivative of velocity
the third derivative of position.
Sometimes the guy behind the steering
wheel!
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Jerk – Related to Airbag
Deployment Decision Making
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Jeremy Daily on
DETROIT DIESEL ECM DATA
AND NETWORK TRAFFIC
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‘02 Envoy Crash Test
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‘02 Envoy Crash Test
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DDEC Reports
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Graph Data
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Table Data
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Detroit Diesel Diagnostic Link
DDDL

Compare ECM Time Clock
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Speed Record
Comparison
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Remarks




Impulse and Momentum data is insufficient
to calculate speeds
DeltaV from hvEDR data is not resolved well
Vehicle Network speed has more samples,
thus making it a candidate for data, if
available.
hvEDR follows the J1587 Road Speed Data.
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Patrick Tyrving on
ROTATIONAL MECHANICS
ANALYSIS FOR S10 IMPACT
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S10 Videos
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109
S-10 Crash Analysis
• Location of Center of Mass of Trailer
• Mass Moment of Inertia of Trailer
• Lateral Displacement of Trailer
(Displacement Angle)
• Angular Velocity of Trailer
• Calculating S-10 delta-V
• Calculating pre-impact velocity of S-10
• Accuracy of Calculations vs.
Equipment Data
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Determining the location of Center
of Mass (C.M.) using Static Analysis
Newton’s 3rd Law
“For every action there is an equal but
opposite reaction.”
WTOTAL
WLG
WRA1 WRA2
W
LG
RA1
RA2
Location
Landing Gear
Rear Axle
Front Axle
Tennessee 2014
Left
3800
2600
2200
Right
4400
1800
1900
Total Trailer Weight (Wtotal) =
16,700 lb.
111
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50.3 ft.
d1
d2
9.6
13.6
d3
d4
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38
47.2
113
y
x
WTOTAL
O
x
d1
WLG
WRA1 WRA2
d2
d3
𝑀𝑂 = 0
Tennessee 2014
𝑊𝑅𝐴1 (𝑑1 ) + 𝑊𝑅𝐴2 (𝑑2 ) − 𝑊𝑇𝑂𝑇𝐴𝐿 (𝑋) + 𝑊𝐿𝐺 (𝑑3 ) = 0
114
y
x
WTOTAL
O
x
d1
WLG
WRA1 WRA2
d2
d3
𝑊𝑅𝐴1 (𝑑1 ) + 𝑊𝑅𝐴2 (𝑑2 ) + 𝑊𝐿𝐺 (𝑑3 )
𝑋=
𝑊𝑇𝑂𝑇𝐴𝐿
Tennessee 2014
Location of C.M.
from the rear of the
trailer.
115
y
24.5
WTOTAL
O
x
d1
WLG
WRA1 WRA2
d2
d3
Location of C.M.
from the rear of the
trailer.
𝑋 = 24.5 𝑓𝑡
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116
Displacement Angle
θ
37.6
7.75ft
7.8
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117
Displacement Angle
(Top View)
𝜃=
King-pin
𝑡𝑎𝑛−1
7.8
= 0.204 𝑟𝑎𝑑 = 11.72°
37.6
θ
37.6
7.8
θ
37.6
Rear axle
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7.8
118
Rotational MechanicsMass Moment of Inertia
• Def: Measure of a body’s
resistance to rotational
acceleration about a
specified axis of rotation.
• Depends on geometry and
location of axis of rotation.
• If axis of rotation is NOT
through center of mass,
then Parallel Axis Theorem
must be used.
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Rotational MechanicsMass Moment of Inertia (Yaw)
1
𝐼𝑧 =
𝑚(𝑏 2 + 𝐿2 )
12
m…mass
b…width of trailer
L…length of trailer
Units: lb-ft-s2 , slug-ft2
𝐼𝑧,𝐶𝑀
1 16700
=
(
)(8.52 + 50.32 )
12 32.2
𝐼𝑧,𝐶𝑀 = 112,471.73 𝑙𝑏 ∙ 𝑓𝑡 ∙ 𝑠 2
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Rotational MechanicsParallel Axis Theorem
𝐼𝑧,𝐾𝑃 = 𝐼𝑧,𝐾𝑃 + 𝑚𝑑 2
King-pin
𝐼𝑧,𝐾𝑃 = 112,471.73 + (
16700
32.2
)(22.62 )
d=22.6
𝐼𝑧,𝐾𝑃 = 378,308.8 𝑙𝑏 ∙ 𝑓𝑡 ∙ 𝑠 2
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Rotational MechanicsAngular Velocity
King-pin
h = 35.3
PDOF
(Center of Axle
Assy.)
Tennessee 2014
Assumptions:
-50/50 Left/Right Weight Distribution
-Fully rigid king-pin
-Estimate drag-factor (f)
𝜔=
2𝑤𝑓ℎ𝜃
𝐼𝑧,𝑘𝑝
(eq. 9.67)
f…estimated drag factor (0.6-0.7)
w…weight
h…KP to LOI
θ…displacement angle
I…mass moment of inertia about the King-pin
122
Rotational MechanicsAngular Velocity
Plug in numbers…
King-pin
𝜔
𝜔=
2(0.7)(16700)(35.3)(0.204)
378308.8
h = 35.3
𝜔 = 0.534857 rad/sec
PDOF
(Center of Axle
Assy.)
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123
Delta-V of S-10
King-pin
h = 35.3
PDOF
(Center of Axle
Assy.)
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𝐼𝑧,𝑘𝑝 𝜔
∆𝑣 =
𝑚ℎ
(eq. 9.60)
(378,308.8)(0.535)
∆𝑣 =
3430
(
)(35.3)
32.2
𝑓𝑡
∆𝑣 = 53.9 = 36.7 𝑚𝑝ℎ
𝑠
124
Pre-Impact Velocity of S-10 (v1)
𝑣4 + ∆𝑣
𝑣1 =
1+𝑒
𝑒
(eq. 9.72)
…Coefficient of restitution (typically 0 - 0.15).
Ratio of speeds after and before impact. 1 –
elastic & 0 – perfectly inelastic.
𝑣4 = ℎ𝜔 …linear post-impact velocity of trailer
𝑣1
Tennessee 2014
𝑣4
35.3 0.535 + 53.9
𝑣1 =
1+0
𝑣1 = 72.7 𝑓𝑡/ sec = 49.62 𝑚𝑝ℎ
125
Calculations vs. Instrument Data
Calculated
f Calculated
v1
Radar
0.6
45.94
49.62
48.7
0.65
47.81
0.7
49.62
Instruments
eGPS-200
48.72
VBOX 3i
49.04
VVBOX Lite
48.75
[mph]
This demonstrates that the principles based on Newtonian
physics hold true with a small margin of error. Often times,
this is all we have to rely on when no other facts/data are
available.
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126
Consortium Website
All data from crash testing and this
presentation will be available at
Credentials
User: TUCRRCmember
Password: TUCRRCpassword
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127
Safe Travels and Fair Winds.
THANK YOU
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128

TUCRRC Presentation Tennessee 2014 9526KB Sep 13 2016

Transcription

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