Vehicle Motion Observer - TU Dortmund · Chassis Systems Control Networking of system domains...

1 Dr. Oliver Öttgen | 7/3/2008 | © Robert Bosch GmbH 2008. All rights reserved, also regarding any disposal, exploitation, reproduction, editing, distribution, as well as in the event of applications for industrial property rights.

Chassis Systems Control

Vehicle Motion Observer –Bestimmung der Fahrzeugbewegung ohne Fahrzeug- und Reifenmodelle

Dortmunder Regelungstechnische Kolloquien 2008

2

Vehicle Motion Observer (VMO)

Dr. Oliver Öttgen | 7/3/2008 | © Robert Bosch GmbH 2008. All rights reserved, also regarding any disposal, exploitation, reproduction, editing, distribution, as well as in the event of applications for industrial property rights.


ContentsIntroduction

System Overview

Vehicle Motion ObserverPhysical BasicsDevelopment Process

Results of Test Drives

Conclusion and Outlook

3




Networking of system domains

ActiveSafety

Systems

PassiveSafety

Systems

DriverAssistanceSystems

ChassisSystems

ESP®ESP®

TCSTCS

ABSABS

Combined Active & Passive Safety(CAPS)

Combined Active & Passive Safety(CAPS)

Active SteeringActive

Steering

ACCACC

NavigationNavigation Seat Belt

Seat Belt

AirbagAirbagActive Suspension

Active Suspension

Vehicle Dynamics Management (VDM)Vehicle Dynamics

Management (VDM)

4




ESP® Features and Benefits

Increases driving stability actively in all driving situations

Vehicle stabilization by individual wheel braking and engine management control

Reduced risk of skidding

Maneuverability maintained even in extreme situations

Significant decrease of severe and fatal accidents

Customer benefits

Road safety relies on ESP® market availability

5




Working Principle of ESP®

Yaw momentψ∆

Oversteering:Vehicle is spinning (rear axle of the vehicle is sliding towards the outside of the curve)Yaw velocity is too largeStabilization by brake intervention at the curve outer front wheel

Yaw momentψ∆

Understeering:The front axle of the vehicle slides towards the outside of the curveYaw velocity is too smallStabilization by brake intervention at the curve inner rear wheel

vvx

vyβ

6




ESP® Value-added Functions (Examples)

Load Adaptive Control Mode (LAC)Adjusts ESP® interventions based on loading level (actual weight, center of gravity)

Roll Over Mitigation (ROM)Mitigates dangerous rollover at quasi-stationary maneuvers, e.g. motorway exit

Saf

ety

Hill Hold Control (HHC)Automatic hold of vehicle on hills, facilitated drive-off on slopes without roll-back

Hill Descent Control (HDC)Cruise Control for functionality for downhill driving at low speed

Com

fort

7





System Overview




8




Domain Control Unit (DCU) 1/2

9




FeaturesScalability

Inertial sensors up to 6 d.o.f. (plus redundancy)scalable microcontroller performance

CommunicationFlexRay interfaceCAN interface

IntegrationSensor signal processingOEM and 3rd party software

Domain Control Unit (DCU) 2/2

YX

Z

Integration platform for Vehicle Motion Observer

10




System Overview – DCU w/ VMO

Scalable DCU(Domain Control Unit)

HardwareIntegration

platform

HardwareIntegration

platform

SoftwareIntegrationplatform

SoftwareIntegrationplatform

InertialsensorsInertialsensors

Performanceand

Communication

Performanceand

Communication

Scalable hardware & software integration platform

AdvantagesAdvantages

Computation of vehicle velocities, sideslip angle, roll/pitch angles


New functions, e.g. vehicle stability control based on side slip angle


Vehicle Motion Observer(vehicle dynamics operating system)

Functions (for Safety, Agility & Comfort)

Vehicle MotionManagement:•VDM•CAPS

Environment& Interaction

VehicleEgo Motion

Veh

icle

obs

erve

r

sideslip angle

vehicle velocities

roll- and pitch angles

environment (road)

driving situation

processed 6D signals

vehicle parameters

Failure Strategy

11





System Overview




12




Overview Vehicle Motion Observer

6Dinertial

sensorsV

ehic

le M

otio

n O

bser

ver

Engine Interface

Stability and Assistance Functions

CAN /FlexRay

Input

DCU + vehicle motion observer = vehicle dynamics operating system

sideslip angle

vehicle velocities

roll- and pitch angles

environment (road)

driving situation

processed 6D signals

vehicle parameters

FunctionsComputation

ESP Interface

3x angular velocities

3x accelerations

13




Advantages

• Exact relation

no vehicle and tire models

• State of the art (e.g. aviation)

Challenges

• Complex algorithms

• Sensitive with respect to signal errors

Physical Basics

• Measurement in all 6 d. o. f.

(3 angular rates, 3 accelerations)

• enables a kinematic approach

differential equations of rigid

body dynamics

14




XR

ZR

YR

X´

Y´

αzXR

ZR, Z´

YR

αz

X´

XR

ZR,Z´

YR

X´´

αy´

Z´´

Y´, Y´´

αz

αz

αy´

αx´´

X´

XR

ZR,Z´

YR

X´´, X´´´

Z´´´

Y´, Y´´Y´´´

αx´´

Z´´

αy´

αz

αz

αy´

Differential Equations

(1)

⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜

⎝

⎛ −⋅−

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛⋅⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜

⎝

⎛

−−

−−=

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

'''

'''

'

coscoscossin

sin

00

0

yx

yx

y

z

y

x

z

y

x

xy

xz

yz

z

y

xg

aaa

vvv

vvv

dtd

αααα

α

ωωωω

ωω

(2)

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛⋅

⎟⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜⎜

⎝

⎛

−=⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

z

y

x

y

x

y

xxx

yxyx

z

y

x

dtd

ωωω

αα

αα

αααααα

ααα

'

''

'

''''''

''''''

'

''

coscos

cossin

0

sincos0tancostansin1

∫ dt

15





System Overview




16




Development ProcessRequirements

FunctionDesign

Software Specification Module Tests

(PC)

System Tests(Rapid Prototyp. / Target HW)

Integration Tests(PC / Rapid Prototyp.)

Coding

QA

QA

QA QA

QA

QA

Reviews

Inputs Outputs

Failure Strategy

Signal Processing

Signal Monitoring

Signal Estimation Controller

Func. n

Func. 1

ESP

Common

Req.

Func. n

Func. 1

ESP

Common

Req.

Func. n

Func. 1

ESP

Common

Req.

ESP

ECU 1

ECU n

ECUw/ VMO

conditioned VM

O signals

…

6D Estimation

vX,Y,Z^

αX,Y,Z^

signal processing

aX,Y,Z

ωX,Y,Z

signal processing

aX,Y,Z

ωX,Y,Z

β̂β computation β̂β computation

aX,Y,Z

ωX,Y,Z

aX,Y,Z

ωX,Y,Zsystem equations vX,Y,Z

αX,Y,Z

^^

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

θϕθϕ

θ−⋅−

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛⋅⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ωω−ω−ω

ωω−−=

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ωωω

⋅

⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜

⎝

⎛

θϕ

θϕ

ϕ−ϕθϕθϕ

=⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ψθϕ

coscoscossin

sing

aaa

vvv

00

0

vvv

coscos

cossin

0


z

y

x

z

y

x

xy

xz

yz

z

y

x

z

y

x

qualifierqualifier

vwhl,i

ωZ

vX estimationδS

vwhl,i

ωZ

vX estimationδS

Kalman gains

measurementequations

measurementvX Whl^

constraints

+-

Kalman gains


measurementvX Whl^

constraints

+-

Inputs Outputs

Failure Strategy

Signal Processing

Signal Monitoring


Func. n

Func. 1

ESP

Common

Req.

Func. n

Func. 1

ESP

Common

Req.

Func. n

Func. 1

ESP

Common

Req.

ESP

ECU 1

ECU n

ECUw/ VMO

conditioned VM

O signals

…

6D Estimation

vX,Y,Z^

αX,Y,Z^

signal processing

aX,Y,Z

ωX,Y,Z

signal processing

aX,Y,Z

ωX,Y,Z

β̂β computation β̂β computation

aX,Y,Z

ωX,Y,Z

aX,Y,Z


αX,Y,Z

^^

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

θϕθϕ

θ−⋅−

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛⋅⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ωω−ω−ω

ωω−−=

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ωωω

⋅

⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜

⎝

⎛

θϕ

θϕ

ϕ−ϕθϕθϕ

=⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ψθϕ

coscoscossin

sing

aaa

vvv

00

0

vvv

coscos

cossin

0


z

y

x

z

y

x

xy

xz

yz

z

y

x

z

y

x

qualifierqualifier

vwhl,i

ωZ

vX estimationδS

vwhl,i

ωZ

vX estimationδS

Kalman gains


measurementvX Whl^

constraints

+-

Kalman gains


measurementvX Whl^

constraints

+-

17




Merge of Requirements on Central Signal Provider

Func. n

Func. 1

ESP

Common

Req.

ESP

ECU 1

ECU n

ECUw/ VMO

conditioned VM

O signals

Func. 2

ESP Func. 1

Func. n

Implementation & Release of VMO signals

…

18




6D Estimation

vX,Y,Z^

αX,Y,Z^

signal processing

aX,Y,Z

ωX,Y,Z

β̂β computation

Function Design

aX,Y,Z


αX,Y,Z

^^

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

θϕθϕ

θ−⋅−

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛⋅⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ωω−ω−ω

ωω−−=

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ωωω

⋅

⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜

⎝

⎛

θϕ

θϕ

ϕ−ϕθϕθϕ

=⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛

ψθϕ

coscoscossin

sing

aaa

vvv

00

0

vvv

coscos

cossin0


z

y

x

z

y

x

xy

xz

yz

z

y

x

z

y

x

qualifier

vwhl,i

ωZ

vX estimationδS

Kalman gains


measurementvX Whl^

constraints

+-

19




Software Specification

20

Inputs Outputs

Failure Strategy

Signal Processing

Signal Monitoring


InternalSignalsDCU

ExternalSignalsCAN, ESP S

AS

AX

S

AY

S

AZS

RR

S

PR

S

YR

S

WS

SInternalSignalsDCU

ExternalSignalsCAN, ESP S

AS

AX

S

AY

S

AZS

RR

S

PR

S

YR

S

WS

SW

SS Actuators

e.g. Steering AFS, Brake ESP, Suspension




Software Specification

21

Offline Online




PC Offline Simulation

DCUSample

PC

PhysicalExperiment

Implementation Experiment

ManeuverDatabase

Module Tests & SW Integration Tests

e.g.: Functional Verification, Validation of Implementation, etc.

22

Online




Rapid Prototyping / Target Hardware

Integration Tests & System Tests

e.g.: Communication, Functional Validation, Safety Requirements, etc.

Online

AUTOSAR RTE

Rapid Prototyp.

Phys. / Implem.Experiment

DCUSample

Target(DCU Sample)

Implemented Code

a) b)

23





System Overview




24




Experimental Vehicle (Winter Testing 2007/2008)Vehicle: BMW 530d automatic (E61)Drive Train: 3.0L diesel, 235 hp, RWDSensors: DCU with 6D inertial sensors (sample)Actuators: ESP®premium (production level), AFS (ZFLS)

25

Double Lane Change on Ice w/ ESPPerformance of sideslip angle estimation

Understeering and oversteering situation detection flag




Sideslip angle Situation detection

Trajectory

26

Vx

[kph

]

0

10

20

30

40

50

60

reference signalaiding source vx,whlestimated signal

0 10 20 30 40

time [s]




Double Lane Change on Ice w/o ESPV

y[k

ph]

-20

-10

0

10

20

0 10 20 30 40

time [s]

side

slip

ang

le [°

]

0 10 20 30 40-20

-10

0

10

20

27

0 20 40 60 80 100 120 1400

20

40

60

80lo

ng. v

eloc

ity [k

ph]

0 20 40 60 80 100 120 140-40

-20

0

20

40

time [s]

side

slip

ang

le [d

eg]

ReferenceVMO

ReferenceVMO




Freestyle Driving on Ice Circle w/o ESP

28




Banked Curve with nearly Constant VelocityEstimation of absolute roll angle in a steep banked curve

reference signal

estimated signal

time [s]

roll

angl

e an

d ba

nked

cur

ve [d

eg] reference signal

estimated signal

time [s]

roll

angl

e an

d ba

nked

cur

ve [d

eg]

29




Slopes with nearly Constant Velocity

0 2 4 6 8 10 12 14 16 18 20-20

-10

0

10

0 2 4 6 8 10 12 14 16 18 20-20

-10

0

10

pitc

h an

gle

and

slop

e [d

eg]

0 2 4 6 8 10 12 14 16 18 20-20

-10

0

10

time [s]

Slope 10%

Slope 15%

Slope 20%

Estimation of absolute pitch angle with several slopes

nominalslope angle

30





System Overview




31




Conclusion and OutlookVehicle Motion Observer

improved accuracy of established signal: long. velocity

high accuracy of new signals: lat. velocity, sideslip angle, etc.

accuracy of VMO signals suitable for vehicle dynamics control

Operating System for current and new vehicle dynamics control systems

small set of VMO interface signals to other ECUs

central signal processing and monitoring

enhancement of safety, agility and comfort by sideslip angle control

32





Stability

AgilityControl & limit side slip angle

Minimize side slip angle

Differentcustomer

expectations

Sport Function

Agility Function

Stability Function

Demonstration functions: Body-slip angle control functions

Vehicle Observer

Over-Steer

Sport

Agility

33 Dr. Oliver Öttgen | 7/3/2008 | © Robert Bosch GmbH 2008. All rights reserved, also regarding any disposal, exploitation, reproduction, editing, distribution, as well as in the event of applications for industrial property rights.


Thank you for your attention!Thank you for your attention!

Vehicle Motion Observer –Bestimmung der Fahrzeugbewegung ohne Fahrzeug- und Reifenmodelle

Dortmunder Regelungstechnische Kolloquien 2008

34

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35

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Vehicle Motion Observer - TU Dortmund · Chassis Systems Control Networking of system domains...

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