Vehicle Sideslip Angle Estimation Based on Fusion of Kinematic Method and Kinematic-geometry Method

Considering the vehicle sideslip angle is difficult to measure directly, a fusion estimation method based on kinematic method and kinematic-geometry method is proposed. An extended Kalman filter(EKF) is constructed based on a 3-DoF vehicle kinematics model to estimate the dynamic value of vehicle sideslip angle. And an estimation method based on kinematic-geometry relationship of vehicle is proposed, which utilizes the geometric relationship between vehicle sideslip angle and tire slip angles, as well as UniTire model to estimate the steady-state value of vehicle sideslip angle. Then, according to the applicable domain of the two estimation results, a data fusion method based on the dynamic characteristic of vehicle sideslip angle is designed to improve the accuracy of the final estimation result. The simulation results with CarSim software show that the proposed method is robust to sensor signal noise and errors, and can accurately estimate vehicle sideslip angle under various road conditions and driving maneuvers.