Research on Active Rear-Wheel Steering Control Method With Sliding Mode Control Optimized by Model Predictive

Chuanwei Zhang; Peng Gao; Jianlong Wang; Meng Dang; Xinyue Yang; Yansong Feng

doi:10.1109/ACCESS.2023.3283330

IEEE Access (Jan 2023)

Research on Active Rear-Wheel Steering Control Method With Sliding Mode Control Optimized by Model Predictive

Chuanwei Zhang,
Peng Gao,
Jianlong Wang,
Meng Dang,
Xinyue Yang,
Yansong Feng

Affiliations

Chuanwei Zhang: College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Peng Gao: ORCiD; College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Jianlong Wang: College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Meng Dang: College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Xinyue Yang: College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Yansong Feng: College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China

DOI: https://doi.org/10.1109/ACCESS.2023.3283330
Journal volume & issue: Vol. 11
pp. 57228 – 57239

Abstract

Read online

At present, the rapid development of electric vehicles and the innovation of related technologies have made the active steering control technology of electric vehicles a hot research topic. In this paper, a rear-wheel active steering control strategy based on sliding mode predictive control algorithm was proposed to improve the handling stability and active safety of electric vehicles. Among them, for the jitter problem of the sliding mode control algorithm this paper corrects and optimizes the control rate of the sliding mode control algorithm by adopting the ideas of feedback correction and rolling optimization in the model predictive control algorithm to suppress the jitter problem of the sliding mode control algorithm. At the same time, joint Carsim/Simulink simulation experiments and hardware-in-the-loop experiments were completed under different working conditions, and the simulation results were compared and analyzed with those of front-wheel steering vehicles with the same parameters and active rear-wheel steering vehicles with the sliding mode control algorithm. According to the experimental results, the sliding mode control algorithm optimized based on the model prediction algorithm proposed in this paper reduces the steady-state error of the vehicle yaw rate and the overshoot of the yaw rate by 30.012% and 18.103%, respectively, compared with the sliding mode control algorithm, and the output of the controller eliminates its jitter. The results showed that the proposed sliding mode predictive control algorithm had better control accuracy, better transient response characteristics, and smoother control output. Compared with the front-wheel steering vehicle, the ideal value yaw rate and target trajectory were accurately tracked, and the deviations of yaw rate and sideslip angle were reduced by 28.324% and 68.517%, respectively. The results showed that the proposed active rear-wheel steering control strategy provided better high-speed handling stability and active safety for the vehicle.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

About the journal

Abstract

Keywords