基于自适应Kalman滤波的汽车横摆角速度软测量算法  

Soft measurement method for vehicle yaw rate based on adaptive Kalman filter

作　　者：高越[1] 高振海[1] 李向瑜[2] 

机构地区：[1]吉林大学汽车动态模拟国家重点实验室,吉林长春130025 [2]吉林大学汽车工程学院,吉林长春130025

出　　处：《江苏大学学报（自然科学版）》2005年第1期24-27,共4页Journal of Jiangsu University：Natural Science Edition

基　　金：高等学校骨干教师计划基金资助项目(GG-580-10183-1995)

摘　　要：利用参数软测量技术,提出了基于自适应Kalman滤波和汽车两自由度动力学模型的横摆角 速度软测量算法.该算法实现了横摆角速度的线性最小均方误差估计,且可对汽车行驶过程中的系 统噪声和观测噪声统计特性进行在线估计.仿真与场地试验结果对比验证了该算法的有效性,同时 软测量技术的采用也为汽车状态参数测量提供了一条可行的、准确且低成本的研究思路.With soft measurement technique, the soft measurement algorithm of vehicle yaw rate is proposed based on adaptive Kalman filter and two-degree-of-freedom vehicle dynamic model. This algorithm can realize linear minimum mean square error estimation of yaw rate, and on-line estimate statistical characteristic of system noise and observation noise during vehicle running. The contrastive results of simulation and field experiment verify the effectiveness of this algorithm. The technique provides a feasible, accurate and low-cost way for the measurement of vehicle state parameter.

关 键 词：汽车 横摆角速度 软测量 自适应滤波 状态估计 

分 类 号：U467[机械工程—车辆工程]