重庆理工大学学报2025，Vol.39Issue(15)：60-68,9.DOI:10.3969/j.issn.1674-8425(z).2025.08.008
卡尔曼滤波及其衍生算法在车辆动力学参数估计中的应用比较
Application comparison of Kalman filter and its derived algorithms in vehicle dynamic parameter estimation
摘要
Abstract
To better represent the driving state of the vehicle under different working conditions and realize the relevant stability control,Kalman and its derivative algorithm are designed on the premise of mathematical analysis and model unification,and the lateral deflection angle of the center of mass and yaw angle velocity of the vehicle are estimated and compared.Matlab/Simulink is employed to build the algorithm model of parameter estimation,vehicle dynamics model and CarSim for co-simulation.The characteristics,advantages and disadvantages of the algorithm are verified and analyzed from the simulation duration and error results.The traditional Kalman has obvious real-time advantage in all working conditions,and the estimation accuracy is only guaranteed in the linear state of the system.Extended Kalman simulation takes a long time,the estimation is reliable under linear and partial nonlinear states,and the data performance deviates from the standard under strong nonlinear states.The estimation accuracy is higher in all working conditions without trace Kalman,but the real-time simulation is poor.Under volumetric Kalman variable condition,the estimation accuracy is high,the error distribution stable,and the real-time simulation of the algorithm sub-optimal.关键词
车辆动力学/参数估计/卡尔曼滤波/卡尔曼衍生算法Key words
vehicle dynamics/parameter estimation/Kalman filtering/Kalman derived algorithm分类
信息技术与安全科学引用本文复制引用
屈翔,周卓,李亚娟,张君,王伟..卡尔曼滤波及其衍生算法在车辆动力学参数估计中的应用比较[J].重庆理工大学学报,2025,39(15):60-68,9.基金项目
重庆市科委应用开发计划项目(cstc2014yykfB70008) （cstc2014yykfB70008）
