基于DEKF的车辆状态与参数估计及验证

Estimation and Verification of Vehicle State and Parameters Based on DEKF

针对车辆在行驶过程中的参数变化影响车辆状态估计的数值,开发了一种基于双扩展卡尔曼滤波(Dual Extended Kalman Filter,DEKF)的估计器。双扩展卡尔曼滤波是基于车辆状态和参数估计相互依赖不可分离性,利用两个平行状态下的扩展卡尔曼滤波(EKF)分别对车辆状态和参数进行估计。选用四自由度车辆模型和HSRI轮胎模型,利用DEKF理论设计估计器,采用Trucksim-Simulink联合仿真对估计器进行仿真分析,验证估计器的有效性和准确性。

In view of the vehicle parameters influence on the accuracy of the vehicle state estimation in the process of driving,the paper developed a estimator based on dual extended kalman filter. Based on interdependent and inseparable relation between vehicle state and parameter estimation,it respectively estimate the vehicle state and parameters using two parallel condition of extended kalman filter,selected four degrees freedom vehicle model and HSRI tire model,designed a estimator using the theory of DEKF,analyzed the estimator using Trucksim-Simulink simulation,and verified the validity and accuracy of the estimator.