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分布式电驱车路径跟踪分层协调控制方法研究

周枫林 钦宇 游雨龙 邹腾安 李光 张智永 常雨康

周枫林, 钦宇, 游雨龙, 邹腾安, 李光, 张智永, 常雨康. 分布式电驱车路径跟踪分层协调控制方法研究[J]. 机械科学与技术, 2023, 42(7): 1140-1149. doi: 10.13433/j.cnki.1003-8728.20220012
引用本文: 周枫林, 钦宇, 游雨龙, 邹腾安, 李光, 张智永, 常雨康. 分布式电驱车路径跟踪分层协调控制方法研究[J]. 机械科学与技术, 2023, 42(7): 1140-1149. doi: 10.13433/j.cnki.1003-8728.20220012
ZHOU Fenglin, QIN Yu, YOU Yulong, ZOU Tengan, LI Guang, ZHANG Zhiyong, CHANG Yukang. A Hierarchical Coordinated Control Method for Tracking Path of Distributed Electric Vehicle[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(7): 1140-1149. doi: 10.13433/j.cnki.1003-8728.20220012
Citation: ZHOU Fenglin, QIN Yu, YOU Yulong, ZOU Tengan, LI Guang, ZHANG Zhiyong, CHANG Yukang. A Hierarchical Coordinated Control Method for Tracking Path of Distributed Electric Vehicle[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(7): 1140-1149. doi: 10.13433/j.cnki.1003-8728.20220012

分布式电驱车路径跟踪分层协调控制方法研究

doi: 10.13433/j.cnki.1003-8728.20220012
基金项目: 

湖南省自然科学基金项目 2021JJ30211

湖南省自然科学基金项目 2021JJ50043

详细信息
    作者简介:

    周枫林(1986-), 副教授, 博士后, 研究方向为装备智能化设计制造与控制技术, 164499487@qq.com

  • 中图分类号: TP273

A Hierarchical Coordinated Control Method for Tracking Path of Distributed Electric Vehicle

  • 摘要: 针对分布式电驱车路径跟踪问题,基于分层协调控制方法,提出了一种路径跟踪策略。由电驱车独立转向/驱动的结构优势,设计四轮阿克曼转向理论,以建立电驱车路径跟踪分层运动学模型,并应用到路径跟踪控制策略中。该策略分为上下两层控制。在上层控制中,将上层运动学模型作为模型预测控制算法的预测模型,通过设定最优目标函数和约束条件将未来控制增量的求解问题转换为二次规划的最优解问题,计算出最优转角和速度控制量。下层控制中,通过下层运动学,将上层控制得到的控制量映射到四轮的转角和速度控制量,应用模糊PID算法,实现电驱车的路径跟踪控制。在基于Carsim/Simulink的仿真平台上进行圆形路径跟踪仿真验证,结果表明,该控制器能够使分布式电驱车实现路径的准确跟踪;在实车试验中进行换道路径跟踪,简单MPC(模型预测控制算法)与分层协调控制数据结果对比表明分层协调控制方法能够有效的改善控制性能,提供路径跟踪的精确性和稳定性。
  • 图  1  分层协调控制理论下的分布式人车路径跟踪控制框架

    Figure  1.  Distributed manned vehicle path tracking control framework under layered coordinated control theory

    图  2  全电驱分布式电驱车动力学模型

    Figure  2.  Dynamic model of a fully electric-driven distributed electric vehicle

    图  3  MATLAB/Simulink下的仿真模块

    Figure  3.  MATLAB/Simulink Simulation module

    图  4  电驱车6种转向运动学分析

    Figure  4.  Analysis of 6 steering motions of electric vehicles

    图  5  分布式电驱车路径跟踪运动学模型

    Figure  5.  Kinematic model for path tracking of distributed electric vehicles

    图  6  四轮阿克曼转向模型

    Figure  6.  Four-wheel Ackermann steering model

    图  7  自适应模糊PID控制器流程示意图

    Figure  7.  Flowchart of the adaptive fuzzy PID controller

    图  8  基于自适应模糊PID控制的附加横摆力矩控制器

    Figure  8.  Additional yaw moment controller based on adaptive fuzzy PID control

    图  9  参数自整定模糊PID工作流程图

    Figure  9.  Workflow diagram of self-tuning fuzzy PID

    图  10  自适应模糊PID控制中ΔKp输出曲面

    Figure  10.  The ΔKp output surface of adaptive fuzzy PID control

    图  11  自适应模糊PID控制中ΔKi输出曲面

    Figure  11.  The ΔKi output surface of adaptive fuzzy PID control

    图  12  自适应模糊PID控制中ΔKd输出曲面

    Figure  12.  The ΔKd output surface of adaptive fuzzy PID control

    图  13  不同圆形半径路径跟踪效果对比图

    Figure  13.  Comparison of path tracking effects for different circular radii

    图  14  不同速度下的路径跟踪效果图

    Figure  14.  Path tracking effects at different speeds

    图  15  半径为15 m, 速度36 km/h的跟踪状态信息

    Figure  15.  Tracking state information for a radius of 15 m and a speed of 36 km/h

    图  16  路径跟踪状态信息误差图

    Figure  16.  Error graph of path tracking state information

    图  17  整车控制逻辑

    Figure  17.  Overall vehicle control logic

    图  18  期望斜形换道路径

    Figure  18.  Desired slalom lane change path

    图  19  测试路面期望路径标记

    Figure  19.  Marking of the desired path on the test road surface

    图  20  MPC控制下四轮滑移率

    Figure  20.  Four-wheel slip ratio under MPC control

    图  21  分层协调控制下四轮滑移率

    Figure  21.  Four-wheel slip ratio under layered coordinated control

    图  22  分层协调控制和MPC控制下速度跟踪对比

    Figure  22.  Comparison of speed tracking under layered coordinated control and MPC control

    图  23  分层协调控制和MPC控制下路径跟踪对比

    Figure  23.  Comparison of path tracking under layered coordinated control and MPC control

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  • 收稿日期:  2021-04-02
  • 刊出日期:  2023-07-25

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