基于扩展Kalman滤波的汽车行驶状态估计.PDFVIP

39 1 吉林 大 学 学报 ( 工 学版) V ol. 39 N o . 1 2009 1 J ournal o f Jilin U niv ersity ( Engineering and T echnolo gy Edition) J an. 2009 K alm an 宗长富, 胡 丹, 杨 肖, 潘 钊, 徐 颖 ( 吉林大学 汽车动态模拟国家重点实验室, 长春 130022) 介绍了一种应用扩展 K alm an 滤波技 估计车辆行驶状态的控制算法该算法以非 线性三自由度车辆模型为基础, 对汽车在行驶过程中的横摆角速度纵向车速和质心侧偏角分 别进行了估计为验证该算法的准确度, 将估计获得的状态值与实车场地实验测得的数据进 行了比较比较结果说明, 应用扩展K alm an 滤波算法能够较为准确地估计出车辆的横摆角 速度纵向车速和质心侧偏角 车辆工程; 扩展卡尔曼滤波; 汽车行驶状态; 状态参数估计; 非线性 U 463. 4 A 167154 97( 2009) 0 1000705 Vehicle driving state estimation based on extended Kalman filter ZO N G Ch angf u, H U Dan, Y A N G Xiao, PA N Zh ao, XU Y ing ( StateK ey L aboratory of A utomobiles Dynamic Simulation, Jil in Univ ersity , Changchun 130022, China) Abstract: A contr ol alg orit hm u sing the ext ended K alman filt rat ion( EKF ) t o est im at e t he v ehicle st at e w as sug gest ed. T he alg orit hm b ased on a 3DO F nonlinear v ehicle model w as applied t o estim at e the yaw rat e, t he longit u dinal velocit y, and t he ride sl ip ang le of t he mas s center in t he v ehicle dr iv ing. T he est imat ed v ehicle st at e p aram et ers w ere com pared w it h t he r esult s fro m t he vehicle f ield t est . T he com pariso n demon st rat ed th at t he EK F based alg orit hm can est im at e quit e accurat ely t he abov e ment ioned v ehicle driving st ate p arameters . Key words: vehicle engineering; ext ended K alman f iltr at ion ( EKF ) ; vehicle driv ing st at e; st at e paramet er est imat io n; nonlinearit y , , , , ( A BS) ( ) , ( DY C ) ( ) , ( A CC) ,