基于自适应卡尔曼算法的重型半挂车状态估计研究  

State Estimation of Heavy Tractor Semitrailers Based on Adaptive Kalman Filter

作　　者：张不扬[1] 宗长富[1] 王化吉[1] 郑宏宇[1] 

机构地区：[1]吉林大学汽车仿真与控制国家重点实验室

出　　处：《汽车技术》2012年第7期1-5,共5页Automobile Technology

基　　金：国家自然科学基金资助(编号:51075176);中国博士后基金资助项目(编号:20110490158)

摘　　要：在建立三轴重型半挂车简化动力学模型的基础上,提出了用于估计重型半挂车运动状态的自适应卡尔曼滤波估计算法。利用动力学软件Trucksim对该估计算法进行了验证,验证结果表明,所提出的自适应卡尔曼滤波算法能够在车速为30 km/h与60 km/h的两种扫频工况下,准确估计重型半挂车横摆角速度和铰接角,为重型半挂车的稳定性控制奠定了基础。An estimation algorithm based on Adaptive Kalman filter is developed on the basis of a developed dynamics model of a three-axle heavy tractor-semitrailer. By verifying the estimation results with the real states from Trucksim, it shows that this proposed algorithm can estimate the yaw rate and articulated angle accurately in the sine sweep condition at both the speed 30 km/h and 60 km/h. This research lays a ground for the stability control of heavy tractor-semitrailers.

关 键 词：重型半挂车 状态估计 自适应卡尔曼滤波 

分 类 号：U463.91[机械工程—车辆工程]