Research on information fusion algorithm for vehicle speed information and road adhesion property estimation

To achieve the vehicle speed information and tire-road adhesion property is very important to the vehicle active safety control system. And how to utilize the sensors in vehicle to educe the needed information for these systems while ensuring the accuracy and real-time performance has great significance. In this paper, the state estimation theory of information fusion technology is applied to estimate the vehicle speed and tire-road friction coefficient based on a 3-degree-of-freedom vehicle model containing modified Dugoff tire model, which can not only satisfy the accuracy but also explain the relation of tire-road. Due to the nonlinear characteristic of tire-road behavior, the Extended Kalman Filter (EKF) is applied. By comparing with the outputs signals from CarSim, high accuracy as well as effective availability of this algorithm have been demonstrated.