Estimation of Side Slip Angle for Four In-Wheel Motor Independent Drive Electric Vehicle Based on Singular Decomposition and Unscented Kalman Filter

The practical side slip angle information is crucial for the vehicle stability control systems of four in-wheel motor independent-drive electric vehicle (4MIDEV), although the side slip angle can be directly measured by the expensive sensors, the measurement accuracy is susceptible to environmental factors. Therefore, with the consideration of measurement accuracy and cost, a novel side slip angle estimation method is proposed in this paper based on the singular value decomposition (SVD) and unscented Kalman filter (UKF) algorithm. Firstly, the unscented Kalman filter estimator is designed based on the nonlinear vehicle dynamic model and nonlinear tire model. Then, the singular value decomposition (SVD) is introduced to instead of the Cholesky decomposition in the unscented transformation (UT) to solve the problem of the covariance matrix may lose positive definiteness, then the accurate side slip angle information can be obtained by the SVDUKF estimator. Finally, the simulation model is established in the Carsim and MALAB/Simulink co-simulation platform and the simulation is carried out to verify the effectiveness of the proposed estimation method, the simulation results demonstrate that the side slip angle can be accurately estimated by the SVDUKF estimator.