转向工况下的分布式电动汽车稳定性控制

doi:10.12141/j.issn.1000-565X.190319

华南理工大学学报（自然科学版） ›› 2020, Vol. 48 ›› Issue (3): 100-107.doi: 10.12141/j.issn.1000-565X.190319

转向工况下的分布式电动汽车稳定性控制

郭烈¹ 葛平淑^2,3† 许林娜¹林肖¹

１．大连理工大学汽车工程学院，辽宁大连 116024；２．大连民族大学机电工程学院，辽宁大连 116600；３．大连理工大学控制科学与工程学院，辽宁大连 116024

收稿日期:2019-06-04 修回日期:2019-09-09 出版日期:2020-03-25 发布日期:2020-03-01
通信作者: 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
作者简介: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
基金资助:
国家自然科学基金资助项目（51975089，51575079）；中国博士后科学基金资助项目（2018M641688）；辽宁省教育厅科学研究经费项目（LJYT201915）

Stability Control for Distributed Drive Electric Vehicle Under Steering Condition

GUO Lie¹ GE Pingshu^2,3 XU Linna¹ LIN Xiao¹

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)

摘要/Abstract

摘要： 为提高分布式驱动电动汽车转向稳定性，解决传统神经网络控制算法收敛速度慢、易陷入局部最优解的问题，提出一种利用粒子群算法优化神经网络的比例－积分－微分（PID）转向稳定控制器，利用横摆力矩和滑移率调整力矩实现横摆角速度和各轮滑移率的控制。在此基础上研究了一种针对转向工况的最优力矩分配算法，通过模糊控制算法对驱动力矩进行修正得到驱动修正力矩，将其与横摆力矩和滑移率调整力矩一起作为二次规划问题进行最优分配，得到各轮最佳驱动力矩。基于联合仿真平台进行了双移线和蛇形等典型转向工况下的性能对比测试。结果表明：文中提出的算法能在保持车辆良好动力性同时维持稳定性，稳定控制器能将蛇形工况打滑现象降低36.4％，最优力矩分配算法能将双移线工况的稳定性提高31.2％。

关键词: 分布式电动汽车, 转向稳定性, 神经网络 PID, 最优力矩分

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

中图分类号:

U461.6

郭烈, 葛平淑, 许林娜, 等. 转向工况下的分布式电动汽车稳定性控制[J]. 华南理工大学学报（自然科学版）, 2020, 48(3): 100-107.

GUO Lie, GE Pingshu, XU Linna, et al. Stability Control for Distributed Drive Electric Vehicle Under Steering Condition[J]. Journal of South China University of Technology (Natural Science Edition), 2020, 48(3): 100-107.

转向工况下的分布式电动汽车稳定性控制

Stability Control for Distributed Drive Electric Vehicle Under Steering Condition

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 1

编辑推荐

Metrics

本文评价