Wheel Slip Control Enhancement Considering Pitch Dynamics, and Neural-network-based Wheel Slip Reference Model

One of the most significant operational aspects of vehicles is their safety in critical braking maneuvers. Proper braking performance occurs when the stopping distance is minimized while the vehicle’s steerability is maintained. To meet these objectives, the tire slip ratio should be regulated at its optimum value. In this study, a control system is designed for simultaneously controlling the brake torque of the front and rear wheels using the nonlinear prediction-based control method. In the control design process, the pitch dynamics have been considered which plays an important role in braking maneuvers. Moreover, the instantaneous optimum wheel slip is determined via an artificial neural network (ANN) to improve the performance of the system and achieve the maximum possible brake deceleration. The performance of the designed control system is investigated through conducted simulations in the CarSim and Matlab/Simulink software environments. The obtained results confirm the enhancement in the braking performance along with a considerable reduction in the stopping distance.