Title: A novel traction control strategy for an electric bus

Authors: Changcheng Yin; Zhongyi Mei; Ying Feng; Liang Tang

Addresses: Hubei Key Laboratory of Automotive Power Train and Electronic Control, School of Automotive Engineering, Hubei University of Automotive Technology, Shiyan 442000, China ' School of Technology, Beijing Forestry University, Beijing, 100083, China ' Hubei Key Laboratory of Automotive Power Train and Electronic Control, School of Automotive Engineering, Hubei University of Automotive Technology, Shiyan, 442000, China ' School of Technology, Beijing Forestry University, Beijing, 100083, China

Abstract: The traction control system (TCS) of an electric vehicle is the key to ensuring sufficient stability when the vehicle starts with a large throttle opening. Therefore, a novel control method for the TCS of a single-motor, non-fully driven electric vehicle is proposed in this paper. First, to obtain the road type and optimal slip rate of the driving wheels, an extended Kalman filter (EKF) is used to estimate the gradient and total mass of the vehicle, and an unscented Kalman filter (UKF) is used to estimate the road adhesion coefficient. Second, a TCS controller based on the road type and optimal slip rate of the driving wheels is established for coordinated control of the motor torque and brake pressure, including a brake controller for compensating the load on the side with a lower adhesion coefficient on split roads, a model predictive control (MPC) torque controller for wheel slip control, and an additional torque controller for compensating the torque required by crossing roads. Finally, the effectiveness and accuracy of this method are proven by a joint simulation in TruckSim and MATLAB/Simulink. The slip rate of the driving wheels can indeed be kept near the optimal slip rate on various pavements.

Keywords: electric vehicles; model predictive control; EPC; optimal slip rate; traction control system; TCS; unscented Kalman filter; UKF.

DOI: 10.1504/IJVP.2024.137704

International Journal of Vehicle Performance, 2024 Vol.10 No.2, pp.215 - 237

Received: 07 Jun 2023
Accepted: 12 Nov 2023
Published online: 02 Apr 2024 *

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