• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2026, Vol. 62 ›› Issue (8): 450-461.doi: 10.3901/JME.260138

• 特邀专辑:汽车线控底盘 • 上一篇    下一篇

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瞬时转向中心求解下的角模块车辆路径跟踪预测控制

皮大伟, 李绪航, 张宸硕, 严永俊, 王洪亮, 王显会   

  1. 南京理工大学机械工程学院 南京 210094
  • 收稿日期:2025-05-06 修回日期:2026-01-21 出版日期:2026-04-20 发布日期:2026-06-12
  • 作者简介:皮大伟,男,1983年出生,博士,教授,博士研究生导师。主要研究方向为汽车动力学分析及智能控制技术等。E-mail:pidawei@mail.njust.edu.cn;李绪航,男,2000年出生,硕士研究生。主要研究方向为车辆动力学控制。E-mail:937900370@qq.com;张宸硕,男,2001年出生,硕士研究生。主要研究方向为车辆动力学控制。E-mail:zhangchenshuo@njust.edu.cn;严永俊,男,1995年出生,博士,讲师。主要研究方向为车辆动力学控制、智能车辆决策与控制。E-mail:yanyj@njust.edu.cn;王洪亮,男,1984年出生,博士,教授,硕士研究生导师。主要研究方向为汽车系统动力学、汽车底盘智能线控技术、自动变速器等。E-mail:whl343@163.com;王显会,男,1968年出生,博士,教授。主要研究方向为车辆系统动力学、车辆现代设计理论与方法、汽车线控技术及车辆结构安全与防护。E-mail:11920158@njust.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(52332013)。

Predictive Control for Path Tracking of Corner Module Vehicle Based on Instantaneous Center of Rotation Slover

PI Dawei, LI Xuhang, ZHANG Chenshuo, YAN Yongjun, WANG Hongliang, WANG Xianhui   

  1. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094
  • Received:2025-05-06 Revised:2026-01-21 Online:2026-04-20 Published:2026-06-12

摘要: 智能底盘角模块系统实现了线控驱/制动、线控转向、主动悬架的高度集成,车轮角模块取消了机械连接、减少了大量的机械传动部件,支持车辆各动力学单元独立控制,便于软件定义与冗余可靠性设计,是无人驾驶车辆的理想载体,但是过多的转角控制输入增加了整车的控制难度,仅依赖于传统的转向控制方式很容易使车辆进入非线性失稳状态,为了提高车辆路径跟踪的精度和稳定性,提出基于瞬时转向中心(Instantaneous center of rotation,ICR)的模型预测控制(Model predictive control,MPC)方法。搭建角模块整车动力学模型和路径规划模型,利用笛卡儿坐标系与极坐标系的转化,建立车辆运动与ICR的解耦映射,将传统的车轮角度控制转换为ICR控制,基于模型预测控制实现了侧向运动和偏航运动的协调控制,提出一种能够应用于角模块车辆路径跟踪系统的具有较低系统保守性的车轮转角计算方法,结合闭环系统反馈构建了ICR模型预测控制策略,基于联合仿真与硬件在环测试平台验证了所提控制策略的有效性和实时性。仿真结果表明,所提ICR跟踪控制策略有效地保证了路径跟踪的精度和稳定性,对角模块车辆转向控制系统设计具有重要参考价值。

关键词: ICR控制, 路径跟踪, 模型预测控制, 四轮独立转向, 无人驾驶汽车

Abstract: The intelligent chassis corner module system achieves a high degree of integration of by-wire drive/brake, by-wire steering, and active suspension. The corner module eliminates mechanical connections and reduces a large number of mechanical transmission components, supporting independent control of each dynamic unit of the vehicle. This facilitates software-defined and redundant reliability design, making it an ideal carrier for driverless vehicles. However, excessive steering angle control inputs increase the overall control difficulty of the vehicle. Relying solely on traditional steering control methods can easily lead the vehicle into a nonlinear unstable state. To improve the accuracy and stability of vehicle path tracking, a model predictive control(MPC) method based on the instantaneous center of rotation(ICR) is proposed. A corner module vehicle dynamics model and path planning model are established. By converting between Cartesian and polar coordinate systems, a decoupling mapping between vehicle motion and ICR is established. The traditional wheel angle control is transformed into ICR control. Based on model predictive control, coordinated control of lateral and yaw motions is achieved. A wheel angle calculation method with low system conservatism, applicable to the path tracking system of corner module vehicles, is proposed. Combining with closed-loop system feedback, an ICR model predictive control strategy is constructed. The effectiveness and real-time performance of the proposed control strategy are verified through co-simulation and hardware-in-the-loop testing platforms. Simulation results show that the proposed ICR tracking control strategy effectively ensures the accuracy and stability of path tracking, providing significant reference value for the design of steering control systems in corner module vehicles.

Key words: ICR control, path tracking, model predict control, four wheel independent steering, driverless car

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