基于辅助粒子滤波的汽车轮胎参数和行驶状态估计
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国家留学基金资助项目(留金发 [2013]3018号)


Vehicle Tire Parameter and State Estimation under Driving Situation Based on Auxiliary Particle Filter Method
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    摘要:

    单独的轮胎魔术公式参数通常需要通过昂贵的试验设备和大量的试验数据才能够确定,之后这些参数在设计阶段将被应用于车辆模型来模拟车辆的操纵动力学行为。建立了包含定常统计特性噪声的汽车动力学模型,利用龙格—库塔方法模拟模型,引入辅助粒子滤波技术,通过二次加权操作,较好地实现了轮胎参数的估计,并最终代入动力学方程,实现了车辆侧向力等参数的估计。同时进行了场地试验。结果表明,辅助粒子滤波技术改善了标准粒子滤波算法的精度,验证了算法的有效性。

    Abstract:

    Individual tire magic formula parameter is traditionally derived from expensive equipment in laboratory which needs a large number of experimental data. And then the parameter is transferred to vehicle model at a design stage to simulate the vehicle handling behavior. The main source of uncertainty in this type of models lies in the tire—road interaction due to high nonlinearity. Proper estimation of tire model parameters is important for obtaining reliable results. A vehicle dynamics system containing constant noise and non-linear model was established,and the Runge—Kuttta method was used to simulate the model. The parameters were estimated by using auxiliary particle filter through two rounds weighted processes, and the vehicle dynamic parameters such as tire lateral forces could be estimated by using the parameters estimated before. Meanwhile, the field test was done. The measurements under several standard handling maneuvers (step-steer, double-lane-change, etc.) were presented, and the results showed that the proposed algorithm improved the accuracy of standard particle filter.

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包瑞新,Edoardo Sabbioni,于会龙,张涛.基于辅助粒子滤波的汽车轮胎参数和行驶状态估计[J].农业机械学报,2015,46(4):282-288,301.

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  • 收稿日期:2014-09-22
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  • 在线发布日期: 2015-04-10
  • 出版日期: 2015-04-10