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VRIM: Vehicle Road Interaction Modelling for Estimation of Contact Forces

Jan 02, 2016

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VRIM: Vehicle Road Interaction Modelling for Estimation of Contact Forces. N. K. M'SIRDI¹, A. RABHI¹, N. ZBIRI¹ and Y. DELANNE² ¹ LRV , FRE 2659 CNRS, Université de Versailles St Quentin, France ² LCPC : Division ESAR; (Nantes) BP 44341 44 Bouguenais cedex. Outline. - PowerPoint PPT Presentation
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Page 1: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

VRIM: Vehicle Road Interaction Modelling for Estimation of Contact Forces

N. K. M'SIRDI¹, A. RABHI¹, N. ZBIRI¹ and Y. DELANNE²

¹LRV, FRE 2659 CNRS, Université de Versailles St Quentin, France² LCPC: Division ESAR; (Nantes) BP 44341 44 Bouguenais cedex

Page 2: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Outline

Problematic for on line estimation

Contact models (static & dynamic ones)

Vehicle Dynamics an Estimation model

Design of a nonlinear robust observer

Simulations results

Conclusion

Page 3: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Need of On line Estimation of contact forces

The knowledge of the tire/road contact is necessary for vehicle control, road safety, ...

Dynamics: Use of the “Relaxation Length” leads to dynamic equation of the longitudinal tire force.

Appropriate formulation of the model to permit the on-line estimation of tire forces.

– Stochastic behaviour (not completely deterministic)– Nonstationary processus (time varying)

Speed Vx

Re

brakeforce

braketorque

IntroductionProblematic for on line estimation

Page 4: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Braking and Tractive forces at given Slip Angles vs. Slip Ratio

Slip Ratio vs. Lateral Force at given Slip Angles

100

Fx à 50 km/h sol sec MXT 175 R14

-9000

-8000

-7000

-6000

-5000

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

-100 -80 -60 -40 -20 0 20 40

60 80

700 daN500 daN300 daN

Longitudinal Forces in function of Fz at

given Velocity

Various intereting Contact Models Exist

s

2a

k

i

p

2bkis

Braking Vx

Vx

”still no internal dynamics”

Contact models (static or steady state)

Page 5: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

« Coefficient longitudinal » influence of Velocity

1020

3040

5060

7080

90100

90

80

70

60

50

400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

µ

% glissem ent

vitesse km /h

Relation µx = f(%glissement, vitesse)

Longitudinal Models

0 10 20 30 40 50 60 70 80 90 1000

0.5

1

1.5

Glissement (%)

Mu

µxmax

Kx

µxbloq

-6000

-5000

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

6000

-10 -8 -6 -4 -2 0 2 4 6 8 10

drift

eff

ort

Y

Slip: 0

Influence of Load

7000 N5000 N

3000 N

carrossage: 0

pressure : 2.5 bars

Transverse Forces in function of Fz

Cannot be reduced to y(

”still no internal dynamics”

Page 6: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Contact Models

PhysicalProperties

- adhesion/Slipping- Pressure distribution- Stiffness Kx et Ky

Assume - constant Velocity, slip angle, - invariant Stifness Kx,Ky, Fz constant,…Uniformity of behaviour

Dugoff, Sakai, Gim, Guo, Lee, Brush Model

Mechanical Properties

- Elasticity theory

Pacejka, Fiala , …

Friction Models

LuGre, Bliman, …

- Relaxation length- contact dynamics…

has internal dynamics

Assumptions: ponctual, never lost, Stationary pressure distribution, symmetry,

perfect rotation, road curvature invariant, …

Page 7: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

One-wheel dynamics

One-wheel dynamics

rFfTI w 2vCFvm x

where : angular wheel velocity, v : vehicle velocityF : tire force, T : applied torques : wheel-slipI : wheel inertia, r : Wheel radium, m : vehicle masseCx : aerodynamic drag, fw : friction coefficient

L o n g i tu d in a l w h e e l s l ip0 0 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9 1

0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

2 5 0 0

3 0 0 0

3 5 0 0

4 0 0 0

4 5 0 0

Lon

gitu

dina

l ti

re f

orce

(N

)

F 0

s

FC

0

ss

FC

Slip-Tire force characteristic

)(sfF

kinematics relationship of wheel-slip

phaseon accelarati during

phase braking during

rv

=s

v

v=s

s

s

vs represents the slip velocity: vs=v-r

Tire equations

Page 8: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Tire equations

The wheel-slip can be presented by a first order relaxation length :

phaseon acceleratiω

phase braking

s

s

vsrsσ

vvssσ

dt

ds

s

F

dt

dF

Ffs )(1

))(( 1*sκ vsfvCFσ

)(1 Ffsκ s

FC

)(sfF

with

sκvCF-F-vFσ 0*

Tire differential equation ( when s<sc, sc is the critical slip)

Locally we can write

Modelling of Tire Contact

( )F VF C V r

0( ) ( )F V F F C V r

Model has internal dynam

icsO

r mem

ory from on state to the next

Page 9: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Vehicle dynamics

cos( ) sin( )

sin( ) cos( )

sin( ) cos( )

x xf F yf F xr

y xf F yf F yr

z xf f F yf f F r yr

mV F F F

mV F F F

J F l F l l F

1

1

f f f xff

r r r xrr

T rFJ

T r FJ

+ expression of the 4 forces

4 dynamic equations

, , ,xf yf xr yrF F F F

Page 10: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

The model can be written in the state space form

1 2

2 3

3 2 3

( )

( , )

x x

x u x Bu

x x x

1 ,( , , , )f rx x y 2 ,( , , , )x y f rx V V 3 ( , , , )xf xr yf yrx F F F F

Position vectorVelocity vectorForces vector

With State variable:

Unknown parameters: 1 2 3 4 5 6 7 8( , , , , , , , )T

1 3 5 71 1 1 1

; ; ;f r f fl l t t

0 0 0 02 4 6 8; ; ;

xf xr yf yr

f r f f

F F F F

l l t t

x f(x) Bu

y h(x)

State space form:

η

Page 11: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Adaptive Estimation of Tire forces

Robust Observer

2 3 2 2 2

3 2 3 3 2 2

ˆ ˆ ˆ( ) ( )

ˆˆ ˆ ˆ ˆ( , ) ( )

x u x Bu H sign x x

x x x H sign x x

2 3 2 2

3 2 3 2 3 3 2

( ) ( )

ˆˆ ˆ( , ) ( , ) ( )

x u x H sign x

x x x x x H sign x

The dynamics of the estimation errors

The system is linear with regard to the unknown parameters

Adaptive and robust sliding mode observer design

x̂xx~ θ̂θθ

~

))θxΨ(x)(Ψθ)xΨ(θ)xΨ(Ψ(x)θ ˆ(~

ˆˆˆ

Vehicle

Tire/road interface

Observer

Input x x̂

Page 12: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

2 2 21

2TV x x

2 2 3 2 2 2( ) ( ) 0T TV x u x x H sign x

2 2 0x x

Convergence analysis

The system power is limited, then Forces are bounded,The a priori estimation is also bounded.

Then

3x

2H

2 0x 0t t

First step : convergence of 2x

2 0S x the sliding surface S is attractive

gives

Consequently 3 2 2( ) ( )equivx u H sign x [n]

The second step consider the reduced sliding dynamics, xr=(x3)

2 3, H H

Page 13: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

According to equation ( n)

13 2 2 2 3 2 3 3 2ˆˆ ˆ( ( )) ( ( , ) ( , ) ( ))TV H sign x x x x x H sign x

2 3 2 3 ˆˆ ˆ( , ) ( , )x x x x

3 0V

By considering the choice of gain H3>>β we finally obtain the convergence of force estimation:

12 3 3 2ˆ ( , ) ( )x x H sign x

3 2 2( ) ( )x u H sign x

3 3 31

2TV x x

Second step : reduced sliding dynamics, xr=(x3)

Convergence analysis

Now, let us consider a second Lyapunov function:

Note also that the parameters values con also be retrieved

Page 14: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

SimulationsThe parameters of simlation model

Parameter

Value Units

MJzFz

Jf,Jrrf,rr

1600301516000

0.70.27

KgKg.m2

NKg.m2

m

0 1 2 3 4 5 6 7 8 9 10-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

t(s)

Steering Angle

radH2 =

10 0 0 0 0

0 4 0 0 0

0 0 35 0 0

0 0 0 40 0

0 0 0 0 40

104 0 0 30 0

10 40 0 0 0

0 0 500 0 20

0 0 0 140 0

H3 =

Gains and parameters of observer

Vehicle

Tire/road interface

Observer

Input x x̂

Page 15: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

0 5 100

0.5

1

1.5

2Vy

t(s)

m/s

0 5 10-0.02

-0.01

0

0.01

0.02

0.03psip

t(s)

rad/s

0 5 1036

38

40

42

44

46wf

t(s)

rad/s

0 5 1030

35

40

45

50wr

t(s)

rad/s

0 5 10

11

11.5

12

12.5

13

13.5

14Vx

t(s)m

/s Velocities

Page 16: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

0 5 10-500

0

500

1000

1500

2000

2500Fxf

t(s)

N

0 5 10-2000

-1500

-1000

-500

0

500

1000Fxr

t(s)

N

0 5 10-400

-200

0

200

400

600Fyf

t(s)

N

0 5 10-300

-200

-100

0

100

200

300Fyr

t(s)

N

Forces

Page 17: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

Conclusion

An appropriate Model for on line state estimation (can be extended for more than 5 Degres Of Freedom)

Robust Observer for on-line tire force estimation (using concept of relaxation length / local linearization)

The sliding mode technique is used to be robust with respect to uncertainties on the model, and unknown events (finite time convergence)

Possibility to quantify parameters of the tire/road friction.

The simulation result illustrate the ability of this approach to give efficient tire force estimation.

Page 18: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

0 2 4 6 8-0.5

0

0.5

1

1.5

2Vy

t(s)

m/s

0 2 4 6 8-0.1

-0.05

0

0.05

0.1psip

t(s)

rad/

s0 2 4 6 8

35

40

45

50

55wf

t(s)

rad/

s

0 2 4 6 830

35

40

45

50

55wr

t(s)ra

d/s

0 2 4 6 811

12

13

14

15

16Vx

t(s)

m/s

Steering Angle Velocities

0 1 2 3 4 5 6 7 8-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

t(s)

rad

Page 19: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

0 2 4 6 80

100

200

300

400

500

600Fxf

t(s)

N

0 2 4 6 8-1000

0

1000

2000

3000

4000Fxr

t(s)

N

0 2 4 6 8-500

0

500

1000

1500Fyf

t(s)

N

0 2 4 6 8-600

-400

-200

0

200

400

600

800Fyr

t(s)

N

Forces

Page 20: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

0 5 10 15 2010

12

14

16

18

20Vx

t(s)

m/s

0 5 10 15 20-2

0

2

4

6

8Vy

t(s)

m/s

0 5 10 15 20-0.02

0

0.02

0.04psip

t(s)

rad/s

0 5 10 15 2030

40

50

60

70wr

t(s)

rad/s

0 2 4 6 8 10 12 14 16 18 20-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

t(s)

rad

Steering angle

0 100 200 300 4000

20

40

60

80

100trajectory

Velocities

Steering Angle

Page 21: VRIM: Vehicle Road Interaction Modelling   for  Estimation of Contact Forces

LRV: Laboratoire de Robotique de Versailles

0 5 10 15 20-1000

0

1000

2000

3000

4000Fxf

t(s)

N

0 5 10 15 20-2000

-1500

-1000

-500

0

500

1000Fxr

t(s)

N

0 5 10 15 20-1000

-500

0

500

1000Fyf

t(s)

N

0 5 10 15 20-1000

-500

0

500

1000Fyr

t(s)

N

Forces