Torque vectoring control of a hybrid drive vehicle to enhance vehicle agility and stability

Abstract

This paper presents a torque vectoring algorithm that enhances the agility and stability of a hybrid drive vehicle that is a rear-wheel-drive vehicle equipped with two front in-wheel motors and an open differential at the rear axle. Vehicle agility and stability are closely related to the understeer gradient and the yaw rate damping coefficient. Based on this relation, the proposed torque vectoring algorithm is designed to modify the two cornering characteristics using steady-state and transient control inputs, each input with its respective purpose. Firstly, the steady-state control input improves vehicle agility by reducing the vehicle understeer gradient. Secondly, the transient control input improves the lateral stability by increasing the yaw rate damping coefficient. The effects of the proposed algorithm on vehicle dynamic responses are analyzed to select proper design parameter values for the algorithm. The proposed algorithm has been validated via both computer simulations and vehicle tests. From the simulation results, the proposed control algorithm showed better control performance compared to that of the sliding mode based yaw rate controllers, fulfilling the objectives of the steady-state and transient control strategies. The vehicle tests have been conducted with the algorithm implemented in a rear-wheel-drive vehicle equipped with two front in-wheel motors. The vehicle test results show that the proposed algorithm can provide superior performance in enhancing vehicle agility and stability compared to that of the uncontrolled case.

Keywords

Chassis control systems hybrid vehicles driver-vehicle systems 4WD yaw behavior

Get full access to this article

View all access options for this article.

References

Piyabongkarn

Lew

Rajamani

, et al. Active driveline torque-management systems. IEEE Control Syst Mag 2010; 30(4): 86–102.

Rubin

Arogeti

. Vehicle yaw stability control using active limited-slip differential via model predictive control methods. Veh Syst Dyn 2015; 53(9): 1315–1330.

Watts

Vallance

Whitehead

, et al. The technology and economics of in-wheel motors. SAE Int J Passeng Cars Electron Electr Syst 2010; 3: 37–55.

Murata

. Innovation by in-wheel-motor drive unit. Veh Syst Dyn 2012; 50(6): 807–830.

Pugi

Favilli

Berzi

, et al. Brake blending and torque vectoring of road electric vehicles: a flexible approach based on smart torque allocation. Int J Electr Hybrid Veh 2020; 12(2): 87.

Chen

Zhao

, et al. Torque optimization control for electric vehicles with four in-wheel motors equipped with regenerative braking system. Mechatronics 2019; 57: 95–108.

Kaiser

Holzmann

Chretien

, et al. Torque vectoring with a feedback and feed forward controller-applied to a through the road hybrid electric vehicle. In: 2011 IEEE intelligent vehicles symposium (IV), 2011. New York, NY: IEEE.

Geng

Uchida

Hori

. Body slip angle estimation and control for electric vehicle with in-wheel motors. In: IECON 2007-33rd annual conference of the IEEE Industrial Electronics Society, 2007. New York, NY: IEEE.

Xiong

Wang

, et al. Vehicle dynamics control of four in-wheel motor drive electric vehicle using gain scheduling based on tyre cornering stiffness estimation. Veh Syst Dyn 2012; 50(6): 831–846.

10.

De Novellis

Sorniotti

Gruber

, et al. Comparison of feedback control techniques for torque-vectoring control of fully electric vehicles. IEEE Trans Vehicular Technol 2014; 63(8): 3612–3623.

11.

Chen

Hedrick

Guo

. A novel direct yaw moment controller for in-wheel motor electric vehicles. Veh Syst Dyn 2013; 51(6): 925–942.

12.

Zhang

Ding

Jiang

. Direct yaw-moment control of in-wheel electric vehicle by sliding mode technique. In: 2016 IEEE international conference on industrial technology (ICIT), 2016. New York, NY: IEEE.

13.

Ding

Liu

Zheng

. Sliding mode direct yaw-moment control design for in-wheel electric vehicles. IEEE Trans Ind Electron 2017; 64(8): 6752–6762.

14.

Nam

Fujimoto

Hori

. Lateral stability control of in-wheel-motor-driven electric vehicles based on sideslip angle estimation using lateral tire force sensors. IEEE Trans Vehicular Technol 2012; 61(5): 1972–1985.

15.

Nam

Fujimoto

Hori

. Design of an adaptive sliding mode controller for robust yaw stabilisation of in-wheel-motor-driven electric vehicles. Int J Veh Des 2015; 67(1): 98–113.

16.

Fujimoto

Takahashi

Tsumasaka

, et al. Motion control of electric vehicle based on cornering stiffness estimation with yaw-moment observer. In: 9th IEEE international workshop on advanced motion control, 2006. New York, NY: IEEE.

17.

Mostefai

Denai

Hori

. Direct yaw-moment control of an in-wheel-motored electric vehicle based on body slip angle fuzzy observer. IEEE Trans Ind Electron 2009; 56(5): 1411–1419.

18.

Vignati

Sabbioni

Tarsitano

. Torque vectoring control for IWM vehicles. Int J Veh Perform 2016; 2(3): 302–324.

19.

Park

Han

Nam

, et al. Torque Vectoring algorithm of Electronic-four-wheel drive vehicles for enhancement of cornering performance. IEEE Trans Vehicular Technol 2020; 69(4): 3668–3679.

20.

Chae

Hyun

, et al. Dynamic handling characteristics control of an in-wheel-motor driven electric vehicle based on multiple sliding mode control approach. IEEE Access 2019; 7: 132448–132458.

21.

Canale

Fagiano

Ferrara

, et al. Vehicle yaw control via second-order sliding-mode technique. IEEE Trans Ind Electron 2008; 55(11): 3908–3916.

22.

Goggia

Sorniotti

Novellis

, et al. Torque-vectoring control in fully electric vehicles via integral sliding modes. In: 2014 American control conference, 2014. New York, NY: IEEE.

23.

Rajamani

. Vehicle dynamics and control. New York, NY: Springer Science & Business Media, 2011.

24.

Pacejka

. Tire and vehicle dynamics. Amsterdam: Elsevier, 2005.

25.

Masato

. Vehicle handling dynamics: theory and application. Amsterdam: Butterworth-Heinemann, 2015.

26.

Milliken

. Race car dynamics. Warrendale: SAE International, 1995.

27.

Yang

Idegren

Jonasson

. Torque vectoring control for progressive cornering performance in AWD electric vehicles. In: Proceedings of AVEC, 2018.

28.

Park

Joa

, et al. Rear-wheel steering control for enhanced steady-state and transient vehicle handling characteristics. IEEE Access 2020; 8: 149282–149300.

29.

Cha

Hyun

, et al. An integrated control of front in-wheel motors and rear electronic limited slip differential for high-speed cornering performance. Proc IMechE, Part D: J Automobile Engineering 2022; 236: 1355–1374.

30.

Kim

Lee

Choi

. A robust road bank angle estimation based on a proportional–integral H∞ filter. Proc IMechE, Part D: J Automobile Engineering 2012; 226(6): 779–794.

31.

Joa

Cha

Hyun

, et al. A new control approach for automated drifting in consideration of the driving characteristics of an expert human driver. Control Eng Pract 2020; 96: 104293.

32.

Fujimoto

Tsumasaka

Toshihiko

. Direct yaw-moment control of electric vehicle based on cornering stiffness estimation. In: 31st Annual conference of IEEE Industrial Electronics Society, IECON2005, 2005. New York, NY: IEEE.

33.

Joa

Park

Koh

, et al. A tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel independent brake from moderate driving to limit handling. Veh Syst Dyn 2018; 56(4): 579–603.

34.

Guo

Guan

. Modelling of driver/vehicle directional control system. Veh Syst Dyn 1993; 22(3–4): 141–184.

35.

Joa

Hyun

. Estimation of the tire slip angle under various road conditions without tire–road information for vehicle stability control. Control Eng Pract 2019; 86: 129–143.

36.

Robert Grover

Hwang

. Introduction to random signals and applied Kalman filtering. New York, NY: Wiley, 1992. Vol. 3.

37.

Lennart

. System identification: theory for the user. Upper Saddle River, NJ: PTR Prentice Hall, 1999. pp.1–14.