An approach to estimate vehicle state and tire-road friction forces using an extended Kalman filter (EKF) is presented. A numerically stable algorithm is used to implement the EKF. This approach does not require knowledge of tire model and road friction coefficient. This is an advantage, because although many tire models have been developed so far, there is still a significant difference between these models and real behavior of tire-road interface. The main advantages of the proposed method are numerical stability, computational efficiency and to use vehicle mounted sensors. Effectiveness of presented method is confirmed by simulation of a lane-change and an ABS braking maneuver for a full vehicle. In these simulations, a seven DOF vehicle model, a Pacejka tire model and a nonlinear model for hydraulic brake system are used. The results show that the EKF has good performance in presence of significant sensor noise in both scenarios.
Real-time estimation of vehicle state and tire-road friction forces
American Control Conference, 2001 ; 3318-3323
2001
6 Seiten, 13 Quellen
Conference paper
English
Vehicle State and Tire-Road Friction Coefficient Estimation
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