Online estimation of tire normal force with applying hardware-software couple model

Tire online normal force has effects on vehicle safety and performance and dynamic control systems. It is influenced by too many parameters such as vehicle mass and center of gravity (CG) position and vehicle instantaneous dynamics states. In this paper, a new estimation algorithm is developed to estimate tires’ online normal forces during a maneuver. The proposed algorithm uses GPS/IMU module and artificial neural network (ANN) with a validated hardware-software couple model to make training, testing and validating data for ANN structure. By applying two roll and pitch ANN blocks, it estimates tires’ static normal forces. In this respect, the validated 9-DOF vehicle model instantaneously monitors the estimated values. Comparing the obtained results from the proposed method with the outputs from Carsim indicates the acceptable accuracy of this method. Comparing the obtained results from the proposed method with the outputs from Carsim indicates the acceptable accuracy of this method. Comparing the obtained results from the proposed method with the outputs from Carsim indicates the acceptable accuracy of this method. Comparing the obtained results from the proposed method with the outputs from Carsim indicates the acceptable accuracy of this method.