Optimization Method for Road Surface Recognition Based on Dynamic Slip Rate Bounds

Due to the fixed slip ratio threshold being difficult to balance accuracy and response speed in estimating tire-road friction coefficient, this paper proposes a method that combines a seven degree-of-freedom vehicle dynamics model, a tire kinematics model, and a Kalman filter to estimate lateral and longitudinal forces on the vehicle’s tires. Then, the brush tire model and recursive least squares estimation method are employed to identify the tire-road friction coefficient during overtaking maneuvers. Finally, a dynamic slip ratio boundary is designed to optimize the road recognition algorithm. Simulation analysis shows that this proposed algorithm can accurately identify the tire-road friction coefficient and respond to its changes in a timely manner.