Enhanced Vehicle Sideslip Angle Estimation through Multi-Source Information Fusion

The sideslip angle is one of the most important parameters that characterize the stability performance of the vehicle, which is also used as a key reference for active safety control strategy. In this article, a sideslip angle estimation method based on the fusion of multiple sources of information is proposed to improve the estimation accuracy. Unscented Kalman filter algorithm (UKF) is adopted to construct kinematic-based and dynamic-based observer. According to the analysis of the applicability of the two methods, a fuzzy logic controller is designed to adaptively allocate the weights of the two estimation results. The simulation results in MATLAB/Simulink show the method can be effectively used for a variety of test maneuvers.