Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (4): 254-256.

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Wheelset speed estimation and simulation based on Kalman filter

CHEN Zheming, FU Lijuan, LIAO Changrong, ZHANG Zhigang   

  1. Chongqing Automobile College, Chongqing University of Technology, Chongqing 400054, China
  • Online:2013-02-15 Published:2013-02-18

基于卡尔曼滤波的轮对速度估计及仿真

陈哲明,富丽娟,廖昌荣,张志刚   

  1. 重庆理工大学 汽车学院,重庆 400054

Abstract: The traditional method of speed measurement and estimation is difficult to get the rapid dynamic change of wheelset speed in the anti-slip braking process of high-speed train because of the small creepage between wheel and rail. For this purpose discrete state equation of vehicle system is established. Kalman filter is used to estimate the speed of wheels. Covariance matrix is corrected in real time to ensure the stability and accuracy based on the changes of wheel speed and wheelset speed with the track surface condition change. Through comparative analysis of three estimation methods, the results show that average estimation method will deviate from the actual value seriously when a sudden change of wheel speed. Maximum estimation method will have greater fluctuations by the impact of rail surface condition. Kalman estimator have validity and accuracy in various conditions.

Key words: high-speed train, wheel-rail creepage, kalman filter, average estimate, maximum estimate

摘要: 高速列车在制动防滑过程中,由于轮轨蠕滑率很小,采用传统的速度测量和估计方法难以获得轮对速度的快速动态变化,为此建立了车辆系统离散状态方程,采用卡尔曼滤波的方法对轮对速度进行估计,并根据车轮速度和轮对减速度随着轨面条件的变化,实时修正协方差矩阵,以保证估计的稳定性和准确性。通过几种估计方法的对比分析结果表明,在轮对速度发生突变时,平均值估算法将严重偏离实际值。受轨面条件的影响,最大值估算法存在较大的波动,不适合应用于防滑过程中轮对速度的估计。卡尔曼估计法在各种条件下具有有效性和准确性。

关键词: 高速列车, 轮轨蠕滑率, 卡尔曼滤波, 平均值估算, 最大值估算