Estimation of vehicle speed and friction force using moving horizon strategy

A moving horizon estimation (MHE) approach to vehicle speed and tire-road friction force estimation is presented in this paper. The proposed method is an optimal strategy that explicitly allows for nonlinear and inequality constraints. The Kalman filter and moving horizon estimation are established to handle abrupt wheel skid and poor signal-to-noise sensor data. A distributed model of friction force is used to calculate the friction force. The simulation results show that the accurate estimate of the vehicle speed can be obtained even under heavy skid condition, and corrupted sensor noise. Additional, the MHE strategy proposed in this paper can handle the constraints effectively and avoid the fallacious estimate results.