基于卡尔曼滤波的车辆状态与路面附着估计  

Estimation of Vehicle State and Road Adhesion Coefficient Based on Kalman Filter

作　　者：李刚[1] 解瑞春 李宁[2] 宗长富[1] 

机构地区：[1]吉林大学汽车仿真与控制国家重点实验室,吉林长春130025 [2]辽宁工业大学汽车与交通工程学院,辽宁锦州121001

出　　处：《华南理工大学学报（自然科学版）》2014年第8期129-135,共7页Journal of South China University of Technology(Natural Science Edition)

基　　金：国家自然科学基金青年基金资助项目(E51305190);辽宁省教育厅项目(L2013253);吉林大学汽车仿真与控制国家重点实验室开放基金资助项目(20111104)

摘　　要：建立了采用Dugoff轮胎模型的三自由度车辆估算模型,设计了基于联邦卡尔曼滤波理论的车辆行驶状态估计算法与基于扩展卡尔曼滤波理论的路面附着系数估计算法,使车辆状态估计与路面附着估计相互联系、闭环反馈、同时进行.选择典型工况,应用Car Sim与Matlab/Simulink联合仿真实验对车辆状态算法和路面附着估计算法进行了验证.结果表明:文中算法能够实现对车辆状态及路面附着系数的准确估计.First,a three-degrees-of-freedom nonlinear estimation model for vehicles is established based on the Dugoff tire model. Then,a vehicle driving state estimation algorithm based on the federal Kalman filter and a road adhesion coefficient estimation algorithm based on the extended Kalman filter are designed to bring about the closedloop feedback and the linkages between the vehicle state estimation and the road adhesion coefficient estimation.Finally,the estimation algorithms of vehicle driving state and road adhesion are verified by adopting a typical situation based on Carsim and Matlab / Simulink co-simulation. The results show that the proposed algorithms can accurately estimate the vehicle state and the road adhesion coefficient.

关 键 词：联邦卡尔曼滤波 Dugoff轮胎模型 车辆状态 路面附着系数 

分 类 号：U461.9[机械工程—车辆工程]