Journal of South China University of Technology (Natural Science Edition) ›› 2020, Vol. 48 ›› Issue (3): 100-107.doi: 10.12141/j.issn.1000-565X.190319

• Mechanical Engineering • Previous Articles     Next Articles

Stability Control for Distributed Drive Electric Vehicle Under Steering Condition

GUO Lie1 GE Pingshu2,3 XU Linna1 LIN Xiao1    

  1. 1. School of Automotive Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China; 2. College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian 116600, Liaoning, China; 3. School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China
  • Received:2019-06-04 Revised:2019-09-09 Online:2020-03-25 Published:2020-03-01
  • Contact: 葛平淑（1983-），女，博士，副教授，主要从事车辆动力学与控制技术研究。 E-mail:gps@dlnu.edu.cn
  • About author:郭烈（1978-），男，博士，副教授，博士生导师，主要从事智能车辆技术研究。E-mail:gou_lie@dlut.edu.cn
  • Supported by:
    Supported by the National Natural Science Foundation of China (51975089, 51575079), the China Postdoctoral Science Foundation (2018M641688) and the Scientific Research Fund from the Education Department of Liaoning Province (LJYT201915)

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Abstract: A neural network PID method based steering stability controller was proposed by using particle swarm optimization. It aims to improve the steering stability of distributed drive electric vehicle and solve the problems of slow convergence and easy to fall into local optimal solution based on neural network control algorithm. This method can realize the yaw rate control and slip rate control of each wheel by yaw moment and slip rate adjustment torque. Based on this, an optimal torque distribution algorithm under steering condition was studied. The modified torque was obtained by correcting the driving torque with the fuzzy control algorithm. Then the modified torque was optimally distributed together with the yaw moment and slip rate adjustment torque of the stability controller as a quadratic programming problem to obtain the optimal driving torque of each wheel. Finally, the performance comparison tests under typical working conditions such as double lane shifting condition and serpentine condition were carried out based on the joint simulation platform. The results show that this algorithm can maintain the stability of the vehicle while maintaining good vehicle dynamics. The stability controller can reduce the slip phenomenon by 36． 4% under slalom condition, and the optimal torque distribution algorithm can improve the stability by 31． 2% under the double lane change condition.

Key words: distributed drive electric vehicle, steering stability, neural networks PID, optimal torque distribution

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