Administrator by China Associction for Science and Technology
Sponsored by China Society of Automotive Engineers
Published by AUTO FAN Magazine Co. Ltd.

Automotive Engineering ›› 2025, Vol. 47 ›› Issue (3): 481-488.doi: 10.19562/j.chinasae.qcgc.2025.03.010

Previous Articles    

Vehicle Yaw Stability Control Based on Multi-agent Model Prediction Control

Kefan Zhao1,2,Xiaofei Pei1,2(),Zhenfu Chen1,2,Hongbo Xiang1,2   

  1. 1.School of Automotive Engineering,Wuhan University of Technology,Wuhan 430070
    2.Wuhan University of Technology,Hubei Key Laboratory of Modern Auto Parts,Wuhan 430070
  • Received:2024-05-20 Revised:2024-09-16 Online:2025-03-25 Published:2025-03-21
  • Contact: Xiaofei Pei E-mail:peixiaofei7@whut.edu.cn

Abstract:

With the rapid development of automotive active safety technology, the chassis electronic control unit of modern electric vehicles has seen explosive growth. In order to improve the real-time performance and accuracy of chassis active safety control, for the rapid growth of chassis electronic control units and the coupling conflict problems of low integration degree of control system and multi-objective co-optimization, in this paper firstly a chassis system integration control architecture based on multi-agent is established, and a hierarchical control system integrating the front and rear wheels' active steering system and the differential braking control system is proposed. Secondly, based on this, the state equations of each agent and its contribution to the vehicle's center of mass model are established and combined with the model predictive control to consider the characteristics of constraints. The cost function containing global state tracking error and local control effort is designed considering both the actuator constraints and the ground friction ellipse constraints. Finally, each agent realizes its collaborative control through the interaction of dynamic information of its respective contribution. The results show that the vehicle stability control method based on multi-agent model prediction proposed in this paper has obvious improvement in terms of traverse stability compared with independent control of each active safety unit under the driving conditions of high and low road attachment and large curvature curves, which has certain value for engineering application.

Key words: multi-agent, model predictive control, stability control, active steering, differential braking