基于无迹卡尔曼滤波的车辆状态与参数估计
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国家高技术研究发展计划(863计划)资助项目(2008AA11A146)


State and Parameters Estimation of Vehicle Based on UKF
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    摘要:

    准确获取车辆运动过程中的状态变量和时变模型参数可以提高动力学控制的鲁棒性。引入了车辆模型时变参数的概念,建立了车辆动力学状态空间模型,应用无迹卡尔曼滤波(UKF)算法对车辆状态变量和参数进行了估计。与车辆动力学软件CarMaker建立的参考模型对比表明,该估计方法具有可行性和准确性。在估计系统中,提出含自适应参数的简化魔术公式来表达轮胎侧偏力,减少了模型参数,并且实现了对轮胎侧向力的准确估计。

    Abstract:

    Accurate estimation of vehicle state variables and uncertain parameters can improve the robustness of vehicle dynamic control system. The concept of uncertain vehicle parameter-set was proposed. The state space model for the estimation system was established. The estimation of the state variables and uncertain parameter-set were completed based on the UKF theory. The comparison with the reference model showed that the estimation method was effective and could get the precise results. A transformed magic formula tire model was also proposed to calculate the cornering force in the estimation process. The tire model reduced the parameters and could realize the precise estimation of tire lateral force. 

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解少博,林程.基于无迹卡尔曼滤波的车辆状态与参数估计[J].农业机械学报,2011,42(12):6-12.

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  • 在线发布日期: 2011-12-19
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