Variable Domain Fuzzy PID Driven Anti-Skid Control with Integrated Road Surface Recognition

Abstract

Traction control is a critical component in ensuring both vehicle performance and safety. Traditional traction control strategies, often based on fixed-parameter controllers, struggle to adapt to complex and variable road surface conditions. This is particularly evident on low-friction surfaces, where response delays or excessive intervention frequently occur. To address this, this paper proposes an integrated traction control method combining fuzzy road surface recognition with variable domain fuzzy PID control. A fuzzy inference system is constructed to achieve online identification of the optimal slip rate for the road surface. Based on this, a variable domain fuzzy PID controller with an adaptive scaling factor is designed. This controller dynamically adjusts its domain range according to the road surface recognition results and vehicle state, enabling precise and smooth regulation of drive torque. Joint simulations using CarSim and MATLAB demonstrate that the optimal slip rate recognition error is 5.3% on snow-covered surfaces and 4.7% on dry gravel surfaces. Compared to traditional PID and conventional fuzzy PID controllers, this strategy exhibits reduced overshoot, accelerates convergence of slip rates to optimal values across all wheels, and enhances vehicle stability during both acceleration and steady-state driving.