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基于FFUKF路面附着系数估计的汽车牵引力控制

汪洪波 王春阳 高含 徐世寒

汪洪波, 王春阳, 高含, 徐世寒. 基于FFUKF路面附着系数估计的汽车牵引力控制. 力学学报, 2022, 54(7): 1866-1879 doi: 10.6052/0459-1879-22-211
引用本文: 汪洪波, 王春阳, 高含, 徐世寒. 基于FFUKF路面附着系数估计的汽车牵引力控制. 力学学报, 2022, 54(7): 1866-1879 doi: 10.6052/0459-1879-22-211
Wang Hongbo, Wang Chunyang, Gao Han, Xu Shihan. Vehicle traction force control based on the road adhesion coefficient estimation by FFUKF. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1866-1879 doi: 10.6052/0459-1879-22-211
Citation: Wang Hongbo, Wang Chunyang, Gao Han, Xu Shihan. Vehicle traction force control based on the road adhesion coefficient estimation by FFUKF. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1866-1879 doi: 10.6052/0459-1879-22-211

基于FFUKF路面附着系数估计的汽车牵引力控制

doi: 10.6052/0459-1879-22-211
基金项目: 国家重点研发计划(2021YFE0116600)资助项目
详细信息
    作者简介:

    汪洪波, 副教授, 主要研究方向: 车辆动力学与控制. E-mail: bob.627@163.com

  • 中图分类号: U461

VEHICLE TRACTION FORCE CONTROL BASED ON THE ROAD ADHESION COEFFICIENT ESTIMATION BY FFUKF

  • 摘要: 以后驱牵引车为研究对象, 设计了基于路面附着系数估计的牵引力控制系统(TCS). 在路面附着系数估计方面, 针对传统卡尔曼滤波难以跟踪时变非线性系统的问题, 本文将模糊控制理论和衰减记忆滤波思想引入无迹卡尔曼滤波, 设计一种基于模糊遗忘因子的无迹卡尔曼滤波路面附着系数估计方法, 提高了算法的跟踪性能. 牵引力控制包括扭矩控制和制动控制. 在TCS扭矩控制方面, 分别利用路面附着系数和驱动轮滑转率在目标滑转率附近时的车辆加速度计算目标基础扭矩, 根据车辆行驶状态和抖振度参量, 基于可拓控制理论划分经典域、可拓域和非域, 通过可拓集的关联函数得到动态权重系数, 将上述两种方法计算得到的目标基础扭矩进行可拓融合设计出基础扭矩. 之后, 以实际滑转率和目标滑转率之间的误差作为输入, 采用模糊自整定PI控制器得到目标反馈扭矩. 在制动控制方面, 针对两种典型路面分别设计了PI控制压力和附着差压力. 实车试验结果表明, 基于模糊遗忘因子的无迹卡尔曼滤波算法能够更加快速地跟踪路面附着系数的变化, 同时基于路面附着系数估计的TCS控制策略能够有效抑制驱动轮过度滑转, 将驱动轮滑转率控制在最佳范围内, 显著提高了车辆的动力性.

     

  • 图  1  五自由度车辆动力学模型简图

    Figure  1.  Diagram of 5-DOF vehicle dynamics model

    图  2  Dugoff轮胎模型输入和输出

    Figure  2.  The input and output of Dugoff tire model

    图  3  模糊控制的隶属度函数

    Figure  3.  Membership function of fuzzy control

    图  4  对接路面仿真结果

    Figure  4.  Simulation results of joint road

    图  5  对开路面仿真结果

    Figure  5.  Simulation results of split road

    图  6  穿越计次法示意图

    Figure  6.  Schematic diagram of traverse method

    图  7  可拓集合划分

    Figure  7.  Extension set division

    图  8  模糊自整定PI隶属度函数

    Figure  8.  Membership function of the fuzzy adaptive PI

    图  9  制动控制结构框图

    Figure  9.  Block diagram of brake control structure

    图  10  对开路面驱动轮受力分析

    Figure  10.  Force analysis of drive wheel on split road

    图  11  均一低附路面实车试验结果

    Figure  11.  Real vehicle results on the uniform road with low road adhesion coefficient

    图  12  对接路面实车试验结果

    Figure  12.  Real vehicle test results on joint road

    图  13  对开路面实车试验结果

    Figure  13.  Real vehicle test results on split pavement

    表  1  模糊推理则表

    Table  1.   Fuzzy inference table

    NB NMZO PM PB
    NB LL LM BM BM M
    NM LM LM BM M M
    ZO LM M BB M LM
    PM M M BM LM LM
    PB M BM BM LM LL
    下载: 导出CSV

    表  2  模糊自整定PI的模糊规则

    Table  2.   Fuzzy rules of fuzzy adaptive PI

    $ |E| $LLLMMBMBB
    $ {k_p} $LLLMMBMBB
    $ {k_i} $BBBMMLMLL
    下载: 导出CSV

    表  3  试验车辆参数配置

    Table  3.   Vehicle parameters

    ParameterValue
    m/kg6800
    L/m3.9
    $ {L_f} $/m1.49
    $ {L_r} $/m2.485
    $ {h_g} $/m1.123
    $ {P_m} $/kW370
    $ {T_m} $/(N·m)2300
    下载: 导出CSV
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  • 收稿日期:  2022-05-21
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  • 刊出日期:  2022-07-15

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