Anti-slip optimization control strategy for high-speed train

Abstract

In response to the problem of low adhesion utilization in traditional anti-slip control, this paper designs an anti-slip optimization control strategy for high-speed train. The full-order closed-loop state observer is used to estimate the rail surface adhesion coefficient in real time, and the real-time search of adhesion peak point is realized by combining slip velocity and other information. The sliding mode control algorithm dynamically adjusts the motor torque to track the maximum adhesion point, which improves the robustness of the system. A sliding mode control algorithm based on Power Rate Exponential Reaching Law (PRERL) is proposed to address the chattering problem of traditional sliding mode controllers. Simulation verification was conducted on the MATLAB/Simulink model, and the results showed that the proposed anti-slip control strategy had good control effect and achieved the high adhesion utilization.