Nonlinear Estimation of Vehicle Sideslip Angle Based on Adaptive Extended Kalman Filter
An adaptive sideslip angle observer based on discrete extended Kalman filter (DEKF) is proposed in this paper and tire-road friction adaptation is also considered. The single track vehicle model with nonlinear tire characteristics is adopted. The tire parameters can be easily obtained through road test data without using special test rig. Afterwards, this model is discretized and the maximum value of tire-road friction is modeled as the third state variable. Through the measurement of vehicle lateral acceleration and yaw rate, the tire-road adhesion coefficient can be timely updated. Simulations with experimental data from road test and driving simulator have confirmed that DEKF has very high accuracy. The convergent speed of DEKF relies on the magnitude of lateral excitation.