吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (2): 333-339.doi: 10.13229/j.cnki.jdxbgxb201602001

• Orginal Article •     Next Articles

State estimation of electric vehicle with in-wheel motors based on UKF

SONG Chuan-xue1, XIAO Feng1, LIU Si-han2, LI Shao-kun1, DUAN Liang1, PENG Si-lun1   

  1. 1.State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
    2.College of Mechanical Science and Engineering, Jilin University, Changchun 130022, China
  • Received:2014-09-22 Online:2016-02-20 Published:2016-02-20

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Abstract: For four-wheel independently drive in-wheel motors electric vehicle, the dynamic control systems, such as direct yaw moment control, can be easily achieved. Accurate estimation of vehicle state variables and uncertain parameters can improve the robustness of the vehicle dynamic control system. Various sensors are generally equipped to acquire the vehicle dynamics. For both technical and economic reasons, some fundamental vehicle parameters, such as the sideslip angle and tire-road forces can hardly be obtained directly by sensors. Therefore, a state observer is developed to estimate these parameters based on Unscented Kalman Filter (UKF). In addition, a nonlinear dynamics tire model is utilized to improve the accuracy of tire lateral force estimation. Compared to the reference model built in AMEsim, the simulation results show that the proposed observer can provide the precision values of the vehicle state.

Key words: vehicle engineering, in-wheel-motor vehicle, state estimation, unscented kalman filter

CLC Number: 

  • U461
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