吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (3): 845-852.doi: 10.13229/j.cnki.jdxbgxb20170069

• Orginal Article • Previous Articles     Next Articles

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

TIAN Yan-tao1,2, ZHANG Yu1, WANG Xiao-yu1, CHEN Hua1   

  1. 1.College of Communication Engineering,Jilin University,Changchun 130022,China;
    2.Key Laboratory of Bionic Engineering,Ministry of Education,Jilin University,Changchun 130022,China
  • Received:2016-12-15 Online:2018-05-20 Published:2018-05-20

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Abstract: 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.

Key words: automatic control technology, estimation of side-slip angle, cornering stiffness of tire, square-root unscented Kalman filter(SR-UKF) algorithm, least square method

CLC Number: 

  • TP273
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