Estimation of Road Load Parameters via On-road Vehicle ... · Slide 1 Estimation of Road Load...
Transcript of Estimation of Road Load Parameters via On-road Vehicle ... · Slide 1 Estimation of Road Load...
Slide 1
Estimation of Road Load Parameters via On-road Vehicle Testingg
Dr. Rahul Ahlawata, Dr. Jürgen Bredenbeckb & Mr. Tatsuo Ichigec
a A&D Technology, Michigan, USA b A&D Europe GmbH, Griesheim, Germanyc A&D Company, Tokyo, Japan
Tire Technology Expo 2013February 5-7 Cologne Germany
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February 5-7, Cologne, Germany
Slide 2
Energy Loss in VehiclesgyStandby17%(4%)
Accessories2%(2%)
Aerodynamic Drag3%(11%)
Fuel Tank100%(100%)
3%(11%)
Rolling Resistance4%(7%)( ) 4%(7%)
Braking6%(2%)
Engine Loss Drivetrain Loss
6%(2%)
62%(69%) 6%(5%)
Losses of fuel energy in a vehicle in city usage (highway usage)
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[U.S. National Academy of Science, 2006]
Slide 3
Energy Loss in VehiclesgyStandby17%(4%)
Accessories2%(2%)
Aerodynamic Drag3%(11%)
Fuel Tank100%(100%)
3%(11%)
Rolling Resistance4%(7%)( ) 4%(7%)
Braking6%(2%)
Engine Loss Drivetrain Loss
6%(2%)
Vehicle Road Load Road Grade62%(69%) 6%(5%)
Road load is define as the “…force or torque which opposes the movement of
Vehicle Road Load Road Grade
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Road load is define as the …force or torque which opposes the movement of a vehicle…”[ISO 10521‐1, 2006]
Slide 4
Significance of Road Load DeterminationE
Vehicle platooning [1,2] Roll‐over prevention [3]Energy
management [4,5]
[SARTRE project test, Sweden]
[Toyota]Offline modeling & control development [6] Engine certification [7]Engine certification [7]
[Mathworks]
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[Mathworks]
Slide 5
Objectivej
Estimate the road load parameters of a vehicle Focus on rolling resistance & aerodynamic drag Focus on rolling resistance & aerodynamic drag Use on‐road testing of a production vehicle Use a novel force measurement method & compare results p
with traditional method(s)
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Slide 6
Outline
1. Introduction
2. Road load fundamentals
3. Instrumentation & sample data
4. Coast down method
5. Force measurement method
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6. Summary
Slide 7
Rolling Resistance
Mg: Vertical load on the tire due to sprung & unsprung massv : Tire longitudinal velocity ω: Tire angular speed R : Ground reaction force
For a free rolling tire under no slip:
vx vx vx
vx: Tire longitudinal velocity ω: Tire angular speed Rz: Ground reaction forceRx: Rolling resistance force Mrr: Rolling resistance moment r: Loaded tire radius
ω ω ωMg Mg MgMrr
RxRx
R R
aTire normal force distribution is asymmetric. The resultant normal force
xx
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Rz RzThe resultant normal force acts towards the leading
edge.a∙Rz = Mrr= r∙ Rx
Rolling resistance force
Slide 8
Aerodynamic Dragy g
[BMW]
Density of airFrontal area of the vehicle
Coefficient of aerodynamic dragl i l i f h hi l h i d
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Relative velocity of the vehicle wrt the wind
Slide 9
Total Road LoadThe most commonly used form of road load equation is:
P d i tl l d I l d i flPredominantly includes the
effect of rolling
Includes aerodynamic drag
Includes influence of road grade
effect of rolling resistance Includes dependence
of rolling resistance on velocity & drivetrain
losses• ‘b’ term is not always included• A number of other formulations exist [8], including
• Influence of rotational inertias
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• Correction factors• Additional dependencies
Slide 10
Road Load Measurement Methods1. Individual component measurements
[Nissan][Terrametrix]
[M t k][Volvo]
[Maptek]Rolling resistance: Tire
testingAerodynamic drag: Wind tunnel testing Grade: Road profiling
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Pros: High repeatability, aids in parametric evaluationCons: Higher cost, may not represent real driving conditions
Slide 11
Road Load Measurement Methods2. Coast‐down method [8,10] 3. Torque measurement [9]
[Timken][VTI Sweden] [Timken][VTI Sweden]
Pros: Less instrumentationCons: Time consuming tests include
[9]
Pros: Drivetrain losses are excludedCons: Difficult to install on
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Cons: Time consuming tests, include drivetrain losses
Cons: Difficult to install on production vehicle
Slide 12
Road Load Measurement Methods4. Complete vehicle measurement system
[A&D][A&D]
[A&D]
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Slide 13
On-road Vehicle Testing
SStop
Test Vehicle: FWDMini Cooper S StartTest Vehicle: FWD Mini Cooper S
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Test Track: Proving ground in Tochigi, Japan
Slide 14
Instrumentation
6‐Component Wheel Force Transducer
AnemometerMeasures wind velocity & direction
(Fx, Fy, Fz, Mx, My, Mz)o Distributed force bridges with model based decomposition to get
orthogonal force components
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o Very low cross sensitivity, interference & temperature sensitivity and high sampling rate
o 0.1% resolution (6N or 1.8Nm)
Slide 15
Instrumentation
6‐Component Wheel Force Transducer
AnemometerMeasures wind velocity & direction
p(Fx, Fy, Fz, Mx, My, Mz)
I fl f d i i l i i l d d i hi
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Influence of a and b terms is included in this measurement (ignoring bearing friction and wheel well aerodynamic losses)
Influence of drivetrain losses is included in this measurement
Slide 16
Vehicle Instrumentation IILaser Doppler SensorMeasures vehicle velocity & slip angleangleGPS Sensor & In‐vehicle Network
Measures vehicle longitude, latitude, altitude, and ECU CAN
communicationInertial SensorInertial SensorMeasures vehicle roll, pitch and yaw
Wheel Position SensorMeasures 6 degrees of freedom of the tireMeasures 6 degrees of freedom of the tire
Digital Signal Processing & A i iti
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& Acquisition 100Hz sampling (max 100kHz)
Slide 17
Sample Data
FL FRRL RRRR
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Slide 18
Sample DataAcceleration Coast‐down Acceleration Braking
FL FRRL RRRR
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Slide 19
Sample DataAcceleration Coast‐down Acceleration Braking
Contribution of a and b terms
FL FRRL RRRR
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Slide 20
Outline
1. Introduction
2. Road load fundamentals
3. Instrumentation & sample datasample data
4. Coast down method
5. Force measurement method
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6. Summary
Slide 21
Coast-down TestsProcedure:• Conduct tests on a flat road with low wind conditions• Accelerate the vehicle and put the transmission in N• Accelerate the vehicle and put the transmission in N• Begin coast down in a straight line• Record vehicle velocity and vehicle velocity relative to wind as a function
f i
30
35
of time
20
25
30
)
10
15
20
Vel
ocity
(m/s
)
Coast‐down
0
5
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0 10 20 30 40 50 60 70 80 90-5
Time (sec)
Slide 22
Coast-down TestsProcedure:• Conduct tests on a flat road with low wind conditions• Accelerate the vehicle and put the transmission in N• Accelerate the vehicle and put the transmission in N• Begin coast down in a straight line• Record vehicle velocity and vehicle velocity relative to wind as a function
f iof time
Flat road assumption6
Road grade (deg)
2
4
e (d
eg)
-2
0
Roa
d gr
ad
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-4
Time (sec)
Slide 23
Coast-down TestsProcedure:• Conduct tests on a flat road with low wind conditions• Accelerate the vehicle and put the transmission in N• Accelerate the vehicle and put the transmission in N• Begin coast down in a straight line• Record vehicle velocity and vehicle velocity relative to wind as a function
f iof time
• Use linear regression to obtain coefficients a, b & cUse linear regression to obtain coefficients a, b & c• Use minimization of • Verify by Simulated Annealing
• SAE J1263 J2263 and ISO 10521 1 contain more detailed procedures
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• SAE J1263, J2263 and ISO 10521‐1 contain more detailed procedures
Slide 24
Coast-down Test Results
800
1000
1200
Measured road load forceRegression estimates
Coefficient of • Front tires: Bridgestone
400
600
800
Forc
e (N
)
determination, R2=0.9087 Sneaker• Rear tires: Bridgestone
Sneaker
0
200• Estimated Values:a = 194.87, b = 3.87, c = 0.37Data‐sets augmented
35
Measured velocityCalculated velocity
0 10 20 30 40 50 60 70 80 90-200
Time (sec)
95% C fid b d(33m/s, 118km/hr, 73mph)
25
30
m/s
)
Calculated velocity95% Confidence bounds:
a: 184 – 204
15
20
Vel
ocity
(m
b: 2.7 – 5
c: 0.35 – 0.39
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10
Time (sec)
(7.5m/s, 27km/hr, 16mph)
Slide 25
Coast-down Test Results1000
1200
Measured road load forceRegression estimates
Coefficient of • Front tires: Bridgestone
400
600
800
Forc
e (N
)
Coefficient of determination, R2=0.9280 Blizzak
• Rear tires: Bridgestone Sneaker
0
200
400F
• Estimated Values:a = 191.69, b = 2.54, c = 0.41Data‐sets augmented
0 10 20 30 40 50 60 70 80-200
Time (sec)
95% C fid b d35
Measured velocityCalculated velocity95% Confidence bounds:
a: 183 – 200 25
30
m/s
)
Calculated velocity
b: 1.5 – 3.5
c: 0.39 – 0.4315
20
Vel
ocity
(m
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10
Time (sec)
Slide 26
Validation Procedure
During coast‐down:
Generalized equation under all conditions (including coast‐down):
Tire traction/braking force
Wheel force
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Wheel force sensor
measurements
Slide 27
Validation Procedure
35
20
25
30
m/s
)
5
10
15
Vel
ocity
(m
Parameter identification
0 10 20 30 40 50 60 70 80 90-5
0
Time (sec)
Parameter Validation
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Estimates are poor outside the coast‐down region
Slide 28
Residual Analysisy
Analyze cross‐correlation coefficient of residuals:
An example:
0.05
0.1
elat
ion
coef
ficie
nt
0 6
0.8
1
1.2
latio
n co
effic
ient
-0.05
0
rmal
ized
cro
ss c
orre
0
0.2
0.4
0.6rm
aliz
ed c
ross
cor
re
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-1000 -800 -600 -400 -200 0 200 400 600 800 1000-0.1
No
Time-1000 -800 -600 -400 -200 0 200 400 600 800 1000
-0.2
Nor
Time
Slide 29
Residual Analysisy
Analyze cross‐correlation coefficient of residuals:
0.4
0.5
n co
effic
ient
posi
tion)
0.4
0.5
0.6
n co
effic
ient
g an
gle) Residuals & steering angle Residuals & accelerator
pedal position
0 1
0.2
0.3
mal
ized
cro
ss-c
orre
latio
nR
esid
uals
& A
cc p
edal
0.1
0.2
0.3
mal
zed
cros
s-co
rrela
tion
(Res
idua
ls &
Ste
erin
g p p
0 10 20 30 40 50 600
0.1
Time (sec)
Nor
m (
0 10 20 30 40 50 60-0.1
0
Time (sec)
Nor
m
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Slide 30
Limitations of Coast-down TestsProcedure:1. A long straight flat track is needed
• SAE procedures requires a minimum speed band of 70 to 15 mph2. Results include drivetrain losses and may not be suitable for some
applicationspp3. Results are not consistent for all driving conditions, especially outside the
coast‐down region• Residuals are correlated with accelerator pedal position, steeringResiduals are correlated with accelerator pedal position, steering
angle,…4. Predictor basis is not orthogonal giving rise to the mathematical
complications due to multicollinearitycomplications due to multicollinearity• Estimates of a, b, c might be biased or have high variance
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Slide 31
Outline
1. Introduction
2. Road load fundamentals
3. Instrumentation & sample datasample data
4. Coast down method
5. Force measurement th dmethod
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6. Summary
Slide 32
Identification using Force Methodg
Use regression to identify c c = 0.5371
30
35 IDID
20
25
(m/s
)
5
10
15
Vel
ocity
5
0
5
Validation
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0 50 100 150 200 250-5
Time (sec)
Slide 33
Validation Test
R2 0 9926
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R2 = 0.9926
95% confidence limit for c: 0.53‐ 0.55
Slide 34
Comparison of Coast-down & Force Method
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• Front tires: Bridgestone Blizzak• Rear tires: Bridgestone Sneaker
Slide 35
Comparison of Coast-down & Force Method
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Slide 36
Comparison of Coast-down & Force Method
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Slide 37
Cross-correlation of Residuals0.4
0.5
icie
nt)
New residualsCoastdown residualsResiduals & steering angle
0.2
0.3
corre
latio
n co
effi
& S
teer
ing
angl
e)
0 1
0
0.1
Nor
mal
zed
cros
s-(R
esid
uals
&
0 50 100 150 200 250-0.2
-0.1
Time (sec)
N
0.5
0.6
ent
New residualsCoastdown residuals
Residuals & accelerator d l iti
0 2
0.3
0.4
orre
latio
n co
effic
iec
peda
l pos
ition
) pedal position
0
0.1
0.2
mal
ized
cro
ss-c
o(R
esid
uals
& A
cc
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-0.1
Time (sec)
Nor
Slide 38
Traction & Braking ScenariosAssumptions:• Small inclination and side‐slip angles• No vertical displacement of the tirevx Mg
m: Mass of tire wheel assemblyJ: Polar moment of inertia of tire‐wheel assembly about the center of wheel hub
• No slipω
Mg
MZ
yT: Applied torque at wheel hubFa: Tire‐road friction force
Mrr
TX
Z
Fr
Let WFS measurements be represented as Fx, Fz and MyThen, From laser Doppler sensor
Rz
Fa From encoder
RzFa
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Slide 39
Calculation of ‘a’ from Force Method6 constant speed tests for each speed, 18 tests total
RL TireRL Tire
Assuming that wheel well aerodynamic losses are negligible at low g y g gspeeds, calculate
a = 271
Note: Measured value of rolling resistance is much higher than what
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standardized tests predict [11]
Slide 40
Calculation of ‘b’ from Force Method
Mean RRF=85.4381 NσRRF= 1.7629 N Mean RRF=84.5861 N
σ = 1 9318 NσRRF= 1.9318 N
Mean RRF=84.8949 NσRRF= 2.2992 N
Very slight reduction in rolling resistance as speed increases
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b ≈ 0
Slide 41
Summaryy
a = 191 69 b = 2 54 c = 0 41Coast‐down Method Force Method
a 271 b 0 c 0 5371a = 191.69, b = 2.54, c = 0.41• R2 = 0.9280• Estimate variance is higher
a = 271, b = 0, c = 0.5371• R2 = 0.9926• Estimation based on physics; g
• Estimation only over coast‐down; road load is under‐estimated for non coast down conditions
p y ;variance is very low
• Estimation can be carried out d i ll ditinon‐coast‐down conditions
• Residuals are correlated with driver inputs
during all conditions• Correlation is significantly
reduced• Changing the tire changes ‘c’
substantially• Influence of drivetrain losses is
• Changing the tires preserves ‘c’ very closely
• Influence of drivetrain losses is• Influence of drivetrain losses is included
• Less instrumentation is needed
• Influence of drivetrain losses is NOT included
• More instrumentation required
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• Less distortion of vehicle aerodynamic
• Vehicle aerodynamics are modified to a greater extent
Slide 42
Acknowledgementsg
O d d t i iti t• On-road data acquisition team: – Takayasu Sasaki – Yuuki Sakurai– Masaaki Banno– Hiroki Yamaguchi
• Kenji Sato A&D Technology Ann Arbor• Kenji Sato, A&D Technology, Ann Arbor • Dr. Michael Smith, A&D Technology, Ann Arbor
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Slide 43
References1. D.Yanakiev & I.Kanellakopoulos, “Speed Tracking and Vehicle Follower Control Design for
Heavy-Duty Vehicles”, Vehicle System Dynamics, Vol. 25, No. 4, 19962. D.Yanakiev & I.Kanellakopoulos, “Nonlinear spacing policies for automated heavy-duty2. D.Yanakiev & I.Kanellakopoulos, Nonlinear spacing policies for automated heavy duty
vehicles”, IEEE Transactions on Vehicular Technology, Vol. 47, No. 43. Bae, Ryu & Gerdes, “Road grade vehicle parameter estimation for longitudinal control using
GPS”, 2001 IEEE Intelligent Transportation Systems 4. C. Musardo, G. Rizzoni & B.P. Staccia, “A-ECMS: An Adaptive Algorithm for Hybrid Electric
Vehicle Energy Management” 2005 European Control Conference5. Hong Yang & Joel Maguire, “Predictive Energy Management Control Scheme for a Hybrid
Powertrain System” US Patent 2011/0066308 A1Powertrain System , US Patent 2011/0066308 A1 6. www.Carsim.com 7. J Fredriksson, E Gelso, M Åsbogard, M Hygrell, O Sponton, NG Vagstedt, “On emission
certification of heavy-duty hybrid electric vehicles using hardware-in-the-loop simulation”, Chalmers University of Technology, 2011
8. Karlsson, Hammarström, Sörensen & Eriksson, “Road surface influence on rolling resistance - Coastdown measurements for a car and an HGV”, VTI, 2011
9 J Ż b ki “T ti ffi i f h l d t t i t ti ti ” A t ti9. J.Żebrowski, “Traction efficiency of a wheeled tractor in construction operations”, Automation in Construction, Vol. 19, No. 2, 2010
10. Sandburg & Ejsmont, “Noise emission, friction and rolling resistance of car tires – Summary of an experimental study”, National conference on noise control engineering, Dec 3-5, 2000,
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p y , g g, , ,Newport beach, California
11. S.K. Clark, “A handbook for the rolling resistance of pneumatic tires”, 1979
Slide 44
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