Abstract: In order to study the driving stability control problem of four-wheel-drive in-wheel motor electric vehicles, an intelligent drive system was proposed to regulate the four-wheel torque output characteristics of the vehicle in the driving state, and the target vehicle model was established by Adams and Matlab/Simulink software, Build a joint simulation platform. Taking body slip angle, yaw rate, and yaw moment as control variables, design a fuzzy PID-based drive controller to work out the yaw moment and longitudinal force required to maintain the normal driving of the vehicle, and use particle swarm optimization algorithm to drive the real-time torque distribution of the four wheels of the vehicle realizes optimal control, and the reasonable distribution of the torque to the four wheels realizes the optimization and adjustment of the output torque of the four wheels of the vehicle; the target model is imported into the Adams software, and a representative in-loop serpentine process is completed. The simulation test of high and low adhesion roads under the conditions, and compared with the conventional PID control. The results show that the fuzzy control strategy can track the state of the target vehicle well. Under the same conditions, the maximum deviation of the yaw rate of the vehicle body can be reduced by 47% in this system, which significantly improves the driving stability of the vehicle.