Road Friction Coefficient Estimation based on Nonlinear Tire Force Observer for Distributed Driven Electric Vehicles

Road friction coefficient is an important characteristic parameter of the interaction force between road surface and tire, which plays a crucial role in vehicle dynamics control. At present, it is difficult to measure the road friction coefficient directly. Therefore, it is a challenge to estimate the road adhesion coefficient accurately and reliably. Considering that tire force is an important reflection of road adhesion coefficient, a road adhesion coefficient estimation method based on nonlinear tire force observation is proposed in this paper. First, based on the nonlinear Dugoff tire model, the nonlinear observer of tire longitudinal force is established. Then a 7-degree-of-freedom (DOF) nonlinear vehicle model is established, and the noise adaptive square root cubature kalman filter (ASRCKF) method is used to estimate the lateral force of the front and rear wheels. Finally, based on the ASRCKF algorithm, combined with the longitudinal force and lateral force information, the all-wheel road surface adhesion coefficient estimator is designed. The road surface friction coefficient estimator is verified by the simulation, and the results show that the proposed algorithm can improve the estimation accuracy and has better stability.