Estimation of vehicle states and tire-road friction using parallel extended Kalman filtering

作     者：Chang-fu ZONG Pan SONG Dan HU 

作者机构：State Key Laboratory of Automotive Simulation and Control Jilin University Changchun 130025 China 

出 版 物：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 (浙江大学学报（英文版）A辑（应用物理与工程）)

年 卷 期：2011年第12卷第6期

页      面：446-452页

核心收录：

学科分类：082304[工学-载运工具运用工程] 08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0823[工学-交通运输工程] 

基　　金：Project (Nos.50775096 and 51075176) supported by the National Natural Science Foundation of China 

主　　题：Vehicle dynamics State estimation and system identification Active safety and passive safety 

摘      要：A model-based estimator design and implementation is described in this paper to undertake combined estimation of vehicle states and tire-road friction *** estimator is designed based on a vehicle model with three degrees of freedom(3-DOF) and the dual extended Kalman filter(DEKF) technique is *** of the estimation is examined and validated by comparing the outputs of the estimator with the responses of the vehicle model in CarSim in three typical road adhesion conditions(high-friction,low-friction,and joint-friction roads).Simulation results demonstrate that the DEKF estimator algorithm designed is able to obtain vehicle states(e.g.,yaw rate and roll angle) as well as road friction coefficients with reasonable accuracy.