• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2021, Vol. 57 ›› Issue (6): 142-155.doi: 10.3901/JME.2021.06.142

• 运载工程 • 上一篇    下一篇

扫码分享

基于转向与主动横摆力矩协调的四轮驱动智能电动汽车路径跟踪控制

梁艺潇1,2,3, 李以农1,2, KHAJEPOUR Amir3, 郑玲1,2   

  1. 1. 重庆大学机械传动国家重点实验室 重庆 400044;
    2. 重庆大学机械与运载工程学院 重庆 400044;
    3. 滑铁卢大学机械与机电工程学院 滑铁卢 N2L 3G1 加拿大
  • 收稿日期:2020-04-20 修回日期:2021-01-25 出版日期:2021-03-20 发布日期:2021-05-25
  • 通讯作者: 李以农(通信作者),男,1961年出生,博士,教授,博士研究生导师。主要研究方向为智能汽车、车辆系统振动噪声主动与半主动控制、汽车系统动力学。E-mail:ynli@cqu.edu.cn
  • 作者简介:梁艺潇,男,1993年出生,博士研究生。主要研究方向为智能汽车、汽车系统动力学与控制。E-mail:liangyixiao1119@foxmail.com
  • 基金资助:
    国家重点研发计划子课题(2017YFB0102603-3)、国家自然科学基金(51875061)、国家留学基金委员会(201906050066)和重庆市研究生科研创新(CYB19063)资助项目。

Path Following Control for Four-wheel Drive Electric Intelligent Vehicle Based on Coordination between Steering and Direct Yaw Moment System

LIANG Yixiao1,2,3, LI Yinong1,2, KHAJEPOUR Amir3, ZHENG Ling1,2   

  1. 1. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044;
    2. School of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044;
    3. Mechanical and Mechatronic Engineering, University of Waterloo, Waterloo N2L 3G1 Canada
  • Received:2020-04-20 Revised:2021-01-25 Online:2021-03-20 Published:2021-05-25

摘要: 为提高智能汽车的路径跟踪能力,并保证其在极限工况下的动力学稳定性,以四轮驱动智能电动汽车为研究对象,根据转向和主动横摆力矩(Direct yaw moment,DYC)系统的特点分别设计控制律进行协调控制。首先,针对汽车在转向过程中轮胎侧偏刚度的不确定性,利用线性矩阵不等式(Linear matrix inequality,LMI)理论构造可实现系统区域极点配置的鲁棒控制器,并研究其求解方案。然后,采用分层架构设计主动横摆力矩的控制律;其中,上层控制器通过车-路运动学关系,基于线性时变模型预测控制(Linear-time-varying model predictive control,LTV-MPC)计算期望横摆角速度;下层采用基于双曲正切趋近函数的滑模控制计算主动横摆力矩,为了在提高跟踪精度的同时确保汽车动力学稳定性,在滑模面中引入质心侧偏角的控制权重,其大小根据质心侧偏角稳定性相图确定。考虑到在大多数常见工况中,转向系统单独作用就已经可以取得良好的控制效果,对主动横摆力矩系统设置激活机制,使其仅在转向系统被判定难以完成当前控制目标时才介入,避免了正常工况下的非必要激活引起的耗能。最后,通过Simulink-CarSim联合仿真进行了算法验证,结果表明,即使在较极端的工况下,所提出的控制方法仍然能保持良好的循迹控制效果,并且可以很好地确保汽车的动力学稳定性。

关键词: 智能汽车, 四轮驱动电动汽车, 路径跟踪控制, 主动横摆力矩, 协调控制

Abstract: In order to improve the path following performance of intelligent vehicles while ensure their dynamics stability in extreme conditions, control and coordination algorisms are designed based on the respective characteristics of steering and direct yaw moment (DYC) systems for four-wheel drive electric intelligent vehicles. Firstly, for the uncertainties of tire cornering stiffness during steering maneuvers, a robust controller is proposed based on linear matrix inequality (LMI) theory, which also has the ability to realize the regional pole assignment. And the solution of the controller is also investigated. For the DYC system, a hierarchical structure is proposed; a linear-time-varying model predictive control (LTV-MPC) method is utilized to generate the desired yaw rate in the upper-level controller based on the kinematics relationship between vehicle and road; the lower level controller obtains the active yaw moment by hyperbolic-tangent based sliding mode controller, and to ensure the stability of vehicle, the side slip angle is considered in the sliding surface, with its weight decided by side slip phase plane index. Considering that in most situations, the steering system alone can achieve satisfactory performance, an activate mechanism is introduced for DYC. Under the mechanism, DYC will not be involved until the steering system is judged unable to complete the control task, this can prevent the energy lost caused by most unnecessary involvement of DYC. Finally, results based on Simulink-CarSim co-simulation shows that the proposed controller can still have satisfactory path following performance even under relatively extreme conditions, while the dynamics stability is well maintained.

Key words: intelligent vehicle, 4WID electric vehicle, path following control, direct yaw moment, coordinative contro

中图分类号: