Automotive Research in Vehicle Dynamics Laboratory

Automotive Research in Vehicle Dynamics Automotive Research in Vehicle Dynamics LaboratoryLaboratory

Huei Peng

Department of Mechanical EngineeringThe University of Michigan

Introduction

Active Safety

Hybrid and Fuel Cell Vehicles

Conclusions

Huei Peng Research Summary 2008/02/11 - 2

Vehicle Dynamics LaboratoryVehicle Dynamics Laboratory

Professor Huei Peng

Currently 12 Ph.D. students, 1 M.S. student and 5 visiting scholars


Major Issues of Ground VehiclesMajor Issues of Ground Vehicles Sustainability

Energy Environment

Quality/Functionality

Safety

Workforce


OutlineOutline

Introduction

Active Safety


Conclusions


Active Safety ResearchActive Safety Research

Chassis Control ESC, road departure warning, CW/CA, Rollover

prediction and prevention, Active Suspension, Integrated Chassis Control

Worst-case evaluation methodology

Driver model development through naturalistic driving database


Active Safety TechnologiesActive Safety TechnologiesRollover generation, prediction

and prevention

Performance evaluation of VDC

5.5 km, 2 lanes

ACC effect on Traffic flow

0

500

1000

1500

2000

2500

3000

3500

0 20 40 60 80 100 120

Density(vehicles/lane/km)

Flo

w r

ate(

veh

icle

s/la

ne/

hr)

Aggressive Drivers (Estimated)Conservative Drivers (Estimated)Modified Gipps ModelI 80, Hayward, CA(1995)Merritt Parkway(1957)Lincoln Tunnel(1959)Tokyo-Nagoya(1996)

Driver model development

0 2 4 6 8 10 12-0.5

0

0.5

1

1.5

2

2.5

3

3.5

TTR

ArcSimTTR

seco

ndsTime (sec)


Worst-Case Evaluation MethodWorst-Case Evaluation Method

DASdesign

Open-loop Simulations

HIL Simulations

Field tests

Worst-case Simulations

DesignIteration

Standard test matrix

Worst-case test matrix

Human driver Model

Doi, Nagiri and Amano, Toyota 1998


Mathematical FormulationMathematical Formulation

Given a nonlinear vehicle dynamic model , where the disturbance input includes front wheel steering angle and brake pedal command . The control input includes the ABS pressure command , CDC damping and VDC pressure command . The control algorithms of the ABS and VDC modules are assumed to be known. Find, within saturation bound and , the signal which maximizes a cost function . The matrix Q is selected such that the vehicle side slip or roll angle is maximized.

( , , , )uf x twx w

p

ABSp

VDCP

max max 0 p pmax

u

J(x,w, t) xT0

T (t)Qx(t) uT (t)Ru(t) wT (t)Pw(t)dt

c


Worst-case LibraryWorst-case Library

• A rollover-worst-case database was created. Many result in rollovers, the rest at least single wheel lift-off.

• Useful for VDC evaluation and re-design.


Vehicle or ESC Performance EvaluationVehicle or ESC Performance Evaluation


Rollover Accident due to an Initial Rollover Accident due to an Initial Sideswipe CollisionSideswipe Collision


Rollover Accident Simulation & Avoidance by Rollover Accident Simulation & Avoidance by PISCPISCWithout Control

With PISC Control

C:\Research\Zhou Jing\Ford Alliance\Reports\20070612\20070531_NoCtrl.exe

C:\Research\Zhou Jing\Ford Alliance\Reports\20070612\20070531_PISC.exe


Rollover Accident at an IntersectionRollover Accident at an Intersection


Accident Reconstruction & Control ComparisonAccident Reconstruction & Control Comparison

Red sedan: bullet vehicle

Blue sedan: target vehicle without post-impact control

Yellow sedan: target vehicle with post-impact control

C:\Research\Zhou Jing\Ford Alliance\Reports\20070612\20070517d.exe

C:\Research\Zhou Jing\Ford Alliance\Reports\20070612\20070517c.exe


40 60 80 100 120 140 160 180 200 220-80

-70

-60

-50

-40

-30

-20

-10

0

10

20

Control ends

Longitudinal displacement [ X (m) ]

Lat

eral

dis

pla

cem

ent

[ Y

(m

) ]

Impact begins

1) Differential Braking Only

2) Differential Braking + Active Steering

3) Full Braking, No Steering

4) No Braking, No Steering

Comparison of TrajectoriesComparison of Trajectories

3 lane width

* 1 sec after impact 3 sec after impact


Vehicle Motion DatabasesVehicle Motion Databases

SAVME Urban street Large human driver population but shorter horizon

(<15 seconds)

ICC FOT Highway + local roads (naturalistic use) Relatively longer cases (<200 seconds)

ACAS

RDCW


SAVME data collection & archivingSAVME data collection & archiving

• System for Assessment of the Vehicle Motion Environment

• 30,561 vehicles, Plymouth road, Ann Arbor, MI, USA

600 ft

200 ft

Digital video cameras

100f

t


ICC FOT databaseICC FOT database

HostVehicle

Main beam(133m)

Side beam (32m)

Width4.4m

108 drivers.

Mostly highway

In car instrumentations

114,000 total miles (68,000 miles manual)


ACAS FOT DatabaseACAS FOT Database

•Total traveled distance: 137,000 miles, 1,500 miles per driver.

•Database: 164 GB in volume; contains approx. 400 engineering variables sampled at 10 Hz, as well as synchronized road forward-view video clips.

Category Channel Description Resolution

Driver Driver number 1- 96 - Trip Trip number - Index Time Time since DAS started 0.1 sec AbsSpeed Vehicle speed from ABS 0.3 m/ sec YawRate Yaw rate - positive = turning right 0.01 deg/ sec AxFiltered Filtered longitudinal acceleration 0.01 m/ sec2 CIPVRange Range to closest in-path vehicle 1/ 64 m CIPVRangeRate Range rate of closest in-path vehicle 1/ 8 m/ sec Distance Trip distance 0.01 m HeadingInLane Vehicle heading angle in lane - positive = turning right 0.1 deg

Kinematics

LaneOffset Host offset from lane center - positive = going right 0.05 m Throttle Throttle opening 1% Brake Brake active On-Off Operation Steer Steering wheel angle 1 deg C0 C0 from data fusion - Curvature 1/ m C1 C1 from data fusion - Curvature rate 1/ m2 LaneWidth Lane width 0.05 m

Road

RoadClass Functional Road Class -


Road Departure Crash Warning Road Departure Crash Warning System DatabaseSystem Database

11 test vehicles Nissan Altima 2003

78 FOT drivers Evenly by gender Three age groups 82,773 miles of driving 2,487 hours

Over 400 signals captured at 10 Hz or faster 204 GB numerical data 135 GB video data


OutlineOutline

Introduction

Active Safety


Conclusions


Hybrid Vehicles StudiedHybrid Vehicles Studied

Series Parallel Split

HEV

HHV

FCHV

FTTS (2000)

Power Bus

Gearbox Gearbox Gearbox Gearbox

Motor Motor Motor Motor

Battery

IM

Inte

r co

oler

Air

Exhaust Gas

Gearbox

C

EMT

ICM

Engine

Generator

Power Control Module Power

Requirement

IMIn

ter

coo

ler

Air

Exhaust Gas

TrnsTC

C

EMT

D

Traction Force

PS

DS

DS

ICM

Vehicle Dynamics

EngineDrivetrain

Motor

Battery

Power Control Module

International Truck (2001)

FMTV (2002)

Re s e r v o ir

A c c u m u la t o r

D-R

1

T r an s

T/CICM

D-R

2

Tr-

C

D-F T

r-C G

ear

bo

x

P/ M

Pow e rCont ro lModule

Eaton/Fed Ex (2004)

DCX Natrium (2005)

Super-HMMWV (2006)

Super-HMMWV (2006)

Super-HMMWV (2007)


Key Problems in Hybrid Vehicle DesignKey Problems in Hybrid Vehicle Design

Configuration selection and model generation

Component sizing

Control DP/SDP algorithms as the assessment tool/benchmark SDP/other algorithms for implementation

Power SplitEVT

Vehicle

Engine

M/G2

M/G1

Battery

Vehicle Vehicle ModelModel

Fuel consumption, DistanceFuel consumption, Distance

Input stateInput state Output stateOutput state

Power demandPower demand

Power errorPower error

)(

)(

)(

kV

kGr

kNe

)1(

)1(

)1(

kV

kGr

kNe

ThrottleThrottleGear shiftGear shiftAFM AFM ModeMode


Possible Design ProcessPossible Design Process

Automatically-Generated Dynamic Modelsa. Selection of the powertrain configurationb. Selection of the mechanical parameters c. Selection of the powertrain component sizes

Model Based DP ControlTheoretical best performance (non-causal)

Model Based SDP or ECMS ControlImplementable control strategies

iteration


SummarySummary

Energy

Environment

SafetyEducation

The main research objectives of the Vehicle Dynamics Laboratory at the Michigan Ann Arbor are to enhance the safety/energy/environment performance of ground vehicle—through working with and education top graduate students.

Automotive Research in Vehicle Dynamics Laboratory

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