Estimation of side-slip angle of electric vehicle based on square-root unscented Kalman filter algorithm

被引：0
|
作者：
Tian Y.-T. [1 ,2 ]
Zhang Y. [1 ]
Wang X.-Y. [1 ]
Chen H. [1 ]
机构：
[1] College of Communication Engineering, Jilin University, Changchun
[2] Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2018年 / 48卷 / 03期
关键词：
Automatic control technology; Cornering stiffness of tire; Estimation of side-slip angle; Least square method; Square-root unscented Kalman filter(SR-UKF) algorithm;
D O I：
10.13229/j.cnki.jdxbgxb20170069
中图分类号：
学科分类号：
摘要：
The side-slip angle of electric vehicle can not be directly and conveniently measured by using sensors. To solve this problem, a Square-Root Unscented Kalman Filter (SR-UKF) algorithm was proposed to estimate the side-slip angle. First, the lateral dynamics model of the vehicle and the nonlinear dynamics model of the tire were established. Then, based on the models and the estimated side-slip angle, the cornering stiffness of the tire was estimated by using least square method. Experiments were carried out to verify the effectiveness of the algorithm in estimating the side-slip angle of electric vehicle. Results show that the proposed method has high precision and can provide effective vehicle state information for the design of the stability control system of the vehicle. © 2018, Editorial Board of Jilin University. All right reserved.
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页码：845 / 852
页数：7
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