Road-Feeling Simulation of SBW System Based on Kalman Filter Fusion Estimation

Due to the elimination of the mechanical connection between the steering column and steering gear in the Steer-by-Wire (SBW) system, the road-feeling simulation is mainly supplied by the road-feeling motor which loads a drag torque on the steering wheel rather than the actual torque transmitted from the road. To obtain more realistic steering wheel torque, a novel feedback torque of the road-feeling motor fusion estimation method based on the Kalman filter is presented in this paper. Firstly, the model-based estimation method is utilized to estimate the aligning torque between tires and ground which is converted into the rack force through the steering system. Then the estimated rack force is used as the observed data for the Kalman Filter of the sensor-based method and the Kalman Filter-based fusion estimation method is resulted, through which the more realistic feedback torque of the road-feeling motor can be obtained. This fusion estimation method is compared with the model-based estimation method and sensor-based method, and the accuracy of the model is verified under the slalom and double lane change maneuver test respectively. The results show that the presented road-feeling simulation model based on Kalman filter fusion estimation can effectively improve the accuracy of road-feeling simulation and reflect road information realistically.