基于轨面状态模糊辨识的高速列车最优黏着控制策略研究

doi:10.3901/JME.2025.16.273

摘要/Abstract

摘要： 针对低黏着接触状态下高速列车车轮易打滑问题，提出一种基于轨面状态模糊辨识的最优黏着控制策略。为了实现轮轨最优黏着利用的目的，通过模糊逻辑推理判断当前轨面黏着状态与标准轨面的相似程度，实时辨识其最优轮轨蠕滑率阈值，然后利用PID控制算法对电机输出转矩进行调整。基于车辆-轨道耦合动力学理论，建立高速车辆-轨道垂纵耦合动力学模型，对比分析复杂黏着条件下不同防滑控制策略对轮轨系统动态相互作用的影响。仿真结果表明，在复杂黏着条件下，相比于方差辨识方法，模糊辨识方法能够更稳健地判别轨面黏着状态并计算最优轮轨蠕滑率阈值。PID控制算法可及时对电机转矩做出调整，实现对车轮空转打滑现象的预防抑制。因此采用基于轨面状态模糊辨识的最优黏着控制策略可有效提高轮轨黏着利用率。

关键词: 高速列车, 轨面辨识, 黏着控制, 车辆-轨道耦合动力学, 模糊辨识

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

中图分类号:

TG156

苗堉淏, 凌亮, 杨云帆, 王开云, 翟婉明. 基于轨面状态模糊辨识的高速列车最优黏着控制策略研究[J]. 机械工程学报, 2025, 61(16): 273-282.

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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