The road feeling control system on the steer by wire system uses fuzzy logic control based on swarm optimization

This paper presents an optimal control system for enhancing road feel in a steer-by-wire (SbW) system using fuzzy logic control (FLC) optimized with modified quantum particle swarm optimization (MQPSO). The objective is to improve the driver experience by providing realistic torque feedback, thereby replicating the steering sensations typically generated by road conditions. This feedback is essential for conveying information about vehicle dynamics and road surface variations through opposing torque applied to the steering interface. An artificial intelligence-based control system utilizing FLC was developed to manage the road feel feedback within the SbW system. The inputs to the FLC include steering angle, vehicle speed, and steering ratio, as well as key physical factors such as inertia and friction, all of which influence the generation of steering torque. The FLC parameters were optimized using MQPSO to achieve a more accurate and responsive road feel torque output. A Simulink model was constructed to simulate the proposed system. The simulation results demonstrate that the optimized FLC significantly improves the performance of the steering motor torque feedback mechanism. This study contributes to the advancement of steer-by-wire technology by proposing an optimal torque control framework and highlighting the effectiveness of integrating FLC with MQPSO in enhancing road feel dynamics.