汽车工程 ›› 2023, Vol. 45 ›› Issue (2): 253-262.doi: 10.19562/j.chinasae.qcgc.2023.02.010

所属专题: 智能网联汽车技术专题-控制2023年

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四轮独立驱动电动汽车路径跟踪鲁棒控制

张新荣1,谭宇航1,贾一帆2(),黄晋2,许权宁1   

  1. 1.长安大学,道路施工技术与装备教育部重点实验室,西安  710064
    2.清华大学车辆与运载学院,北京  100084
  • 收稿日期:2022-07-31 修回日期:2022-08-29 出版日期:2023-02-25 发布日期:2023-02-21
  • 通讯作者: 贾一帆 E-mail:jiayifan@mail.tsinghua.edu.cn
  • 基金资助:
    国家自然科学基金(61901056);陕西省科技统筹创新工程计划基金(2016KTZDGY-02-03);中央高校基本科研业务费项目(300102259306)

Robust Control of Path Tracking for Four-Wheel Independent Drive Electric Vehicles

Xinrong Zhang1,Yuhang Tan1,Yifan Jia2(),Jin Huang2,Quanning Xu1   

  1. 1.Chang’an University,Key Laboratory of Road Construction Technology and Equipment of the Ministry of Education,Xi’an  710064
    2.School of Vehicle and Mobility,Tsinghua University,Beijing  100084
  • Received:2022-07-31 Revised:2022-08-29 Online:2023-02-25 Published:2023-02-21
  • Contact: Yifan Jia E-mail:jiayifan@mail.tsinghua.edu.cn

摘要:

针对四轮独立驱动电动汽车具有结构参数、外部干扰不确定性与非线性和过驱动等特征,提出了一种分层控制框架,以实现前轮转向与直接横摆力矩控制系统协同的车辆路径跟踪控制。首先,基于路径跟踪运动学模型,将车辆的路径跟踪问题转化为约束跟随问题;其次,设计了基于约束跟随的自适应鲁棒上层控制算法,该方法可以有效处理由模型不确定性和外部干扰引起的失配问题,并保证闭环系统的一致有界性和一致最终有界性;最后,设计了一种基于二次规划的下层分配算法满足所需的直接横摆力矩,并在Simulink-Carsim平台进行联合仿真。通过不同工况的仿真结果表明,所设计的自适应鲁棒控制算法具有良好的路径跟踪精度和鲁棒性。

关键词: 自动驾驶车辆, 车辆横向动力学, 路径跟踪控制, 直接横摆力矩控制, 鲁棒控制

Abstract:

For the characteristics of four-wheel independent drive electric vehicles, such as structural parameters, external disturbance uncertainty, nonlinearity, and over-drive, a hierarchical control framework is proposed to realize the vehicle path tracking control with the coordination of front wheel steering and direct yaw torque control system. Firstly, based on the path tracking kinematics model, the vehicle path tracking problem is transformed into a constrained following problem. Secondly, an adaptive robust upper-layer control algorithm based on constrained following is designed, which can effectively deal with the mismatch problem caused by model uncertainty and external disturbances, and guarantee the consistent boundedness and consistent ultimate boundedness of the closed-loop system. Finally, a quadratic programming-based lower-level allocation algorithm is designed to satisfy the required direct yaw moment. Co-simulation is conducted on the Simulink-Carsim platform. The simulation results of different working conditions show that the designed adaptive robust control algorithm has good path tracking accuracy and robustness.

Key words: autonomous vehicle, vehicle lateral dynamics, path following control, direct yaw moment control, robust control