Optimal Adhesion Control of High-speed Trains Based on Fuzzy Identification of Rail Surface Conditions

doi:10.3901/JME.2025.16.273

Abstract

Abstract: In order to deal with the incidental wheel slipping behavior of high-speed trains under poor friction conditions, an optimal adhesion control strategy base on fuzzy identification of rail surface status was proposed. To achieve the purpose of optimal adhesion utilization, this method determines the similarities between the current rail surface and the standard rail surfaces through fuzzy logical reasoning, and then calculates the optimal creepage threshold which is subsequently referred by PID controller to adjust the motor torque. The analysis of the effects of different anti-slip control strategies on the wheel/rail dynamic interactions under complex adhesion conditions is involved in this study thanks to the high-speed train-track coupled dynamics model, which is established based on the vehicle-track coupled dynamics theory. The simulation results show that under complex adhesion conditions, the fuzzy identification approach is more robust than the variance identification approach in determining the rail surface status and calculating the optimal creepage threshold. The PID control is able to keep the motor torque at the proper value and the phenomenon of wheel slipping is restrained. Consequently, the optimal adhesion control based on fuzzy identification of rail surface conditions can effectively improve the utilization rate of wheel/rail adhesion.

Key words: high-speed train, rail surface identification, adhesion control, vehicle-track coupled dynamics, fuzzy identification

CLC Number:

TG156

MIAO Yuhao, LING Liang, YANG Yunfan, WANG Kaiyun, ZHAI Wanming. Optimal Adhesion Control of High-speed Trains Based on Fuzzy Identification of Rail Surface Conditions[J]. Journal of Mechanical Engineering, 2025, 61(16): 273-282.

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