Title: Research on ABS control strategy of cornering braking of electric vehicle with four in-wheel-motors

Authors: Kun Yang; Jinzhao Xiao; Di Tan; Chao Ma; Zhaoqiao Gao; Jilei Wang

Addresses: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China ' Hyundai Automobile R & D Center(China) Co., Ltd., Yantai, 264006, China ' School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China ' School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China ' School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255049, China ' Guangdong Zhu Hai Supervision Testing Institute of Quality & Metrology, Zhuhai, 519060, China

Abstract: To solve the problem of increased wheel inertia and significantly different wheel target slip rates during cornering braking of the electric vehicle with four-wheel-motors, the target slip rates were optimised by particle swarm algorithm, and a braking stability control strategy is proposed. The upper controller calculated the required compensating yaw moment and slip rate increment, the lower controller used a logic threshold value ABS control algorithm to control the wheel-braking force using three schemes: single-wheel control, single-side control, and no turn control applied, respectively. The control strategy was verified based on a condition with an initial speed of 90 km/h, a front wheel turning angle of 5.7°, and a braking deceleration of 8 m/s2. The simulation results show that it can adjust each wheel-braking force to produce compensating transverse moments to improve cornering braking stability. The single-side wheel control has better braking performance and cornering braking stability than the single-wheel control.

Keywords: electric vehicle with four in-wheel motors; anti-lock braking system; cornering braking; logic threshold; orthogonal test; particle swarm optimisation algorithm.

DOI: 10.1504/IJVSMT.2023.135444

International Journal of Vehicle Systems Modelling and Testing, 2023 Vol.17 No.3/4, pp.267 - 287

Received: 04 Aug 2022
Received in revised form: 18 Oct 2022
Accepted: 18 Nov 2022
Published online: 13 Dec 2023 *

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