MPC based Rear Wheel Torque Vectoring Near the Limits of Handling
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MPC based Rear Wheel Torque Vectoring Near the Limits of Handling
Efstathios Siampis
Dr Efstathios Velenis, Dr Stefano Longo
Cranfield University
UKACC PhD Presentation Showcase
UKACC PhD Presentation Showcase Slide 2
Introduction
Velocity regulation becomes important in terminal understeer cases
Design an active safety system that: Stabilizes the vehicle using combined velocity, yaw and sideslip
control Accounts for the important in limit handling conditions system
constraints
UKACC PhD Presentation Showcase Slide 3
Approach to Problem
Rear wheel torques
-
MPCs
Driver Intention
RWD Vehicle
Driver inputs (using the steering, throttle, and brake pedal)
Velocity, sideslip angle and yaw rate
+
UKACC PhD Presentation Showcase Slide 4
Approach to Problem: Target Generation
- MPCs
Driver Intention
RWD Vehicle
+
Steady state cornering analysis of a nonlinear four-wheel vehicle model to derive feasible targets
Then the requested path radius from the driver can be feasible, or not
13.2 13.4 13.6 13.8 14 1
1.5
2
2.5
3
3.5
4
4.5
5
RSS
(m)
SS (
deg)
Rkin
VSS
=10.75m/s, SS=10deg
13.8 14 14.2 14.41
1.5
2
2.5
3
3.5
4
RSS
(m)
SS (
deg)
Rkin
VSS
=11.25m/s, SS=10deg
13.8 14 14.2 14.41
1.5
2
2.5
3
3.5
4
RSS
(m)
SS (
deg)
Rkin
VSS
= 11m/s, SS=10deg
UKACC PhD Presentation Showcase Slide 5
Approach to Problem: Controller Design
- MPCs
Driver Intention
RWD Vehicle
+
For the MPC, we linearize the nonlinear four-wheel vehicle model and use the rear wheel slip as inputs
Constraints are set on yaw rate and sideslip angle, but also on the rear wheels’ slip ratios and torques
Then a sliding mode controller calculates the necessary torques on the rear wheels
MPC SMC
Rear wheel slip ratios
Rear wheel torques
0 2 4 6 8 10 12-6
-4
-2
0
2
4
6
t (s)
Sid
eslip
ang
le (
deg)
UncontrolledLQRMPCsMPCs constraints
0 2 4 6 8 10 12-40
-30
-20
-10
0
10
20
30
40
t (s)
Yaw
rat
e (d
eg/s
)
UncontrolledLQRMPCsMPCs constraints
0 2 4 6 8 10 1250
60
70
80
90
100
110
120
t (s)
Vel
ocity
(km
/h)
UncontrolledLQRMPCsVmax (MPCs)
0 2 4 6 8 10 12-120
-100
-80
-60
-40
-20
0
20
40
t (s)
Whe
el s
teer
ing
inpu
t (d
eg)
UncontrolledLQRMPCs
UKACC PhD Presentation Showcase Slide 6
Simulations: U-turn scenario
UncontrolledLQRMPCs
UKACC PhD Presentation Showcase Slide 7
Simulations: Double-lane Change Scenario
0 1 2 3 4 5 6 7 8 9 10-600
-500
-400
-300
-200
-100
0
100
200
300
400
t (s)
Whe
el s
teer
ing
inpu
t (d
eg)
UncontrolledLQRMPCs
0 1 2 3 4 5 6 7 8 9 1020
30
40
50
60
70
80
t (s)
Vel
ocity
(km
/h)
UncontrolledLQRMPCsVmax (MPCs)
0 1 2 3 4 5 6 7 8 9 10
-50
-40
-30
-20
-10
0
10
20
30
40
t (s)
Yaw
rat
e (d
eg/s
)
UncontrolledLQRMPCsMPCs constraints
0 1 2 3 4 5 6 7 8 9 10
-10
-8
-6
-4
-2
0
2
4
6
8
t (s)
Sid
eslip
ang
le (
deg)
UncontrolledLQRMPCsMPCs constraints
UncontrolledLQRMPCs
UKACC PhD Presentation Showcase Slide 8
Conclusions and Future Work
Conclusions Lateral control only not enough for terminal understeer mitigation Accounting for the system constraints can prevent instability
Future Work Exploration of different vehicle topologies Controller testing in the HIL facility of the Automotive Department
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