摘要
介绍了一种应用扩展Kalman滤波技术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Kalman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。
A control algorithm using the extended Kalman filtration(EKF) to estimate the vehicle state was suggested.The algorithm based on a 3-DOF nonlinear vehicle model was applied to estimate the yaw rate,the longitudinal velocity,and the ride slip angle of the mass center in the vehicle driving.The estimated vehicle state parameters were compared with the results from the vehicle field test.The comparison demonstrated that the EKF based algorithm can estimate quite accurately the above-mentioned vehicle driving s...
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2009年第1期7-11,共5页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(50775096)
关键词
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
vehicle engineering
extended Kalman filtration（EKF）
vehicle driving state
state parameter estimation
nonlinearity
