Optimal adhesion control of high-speed train based on fast adaptive super-twisting algorithm

被引:0
|
作者
Li, Zhongqi [1 ,2 ]
Zhang, Junhao [1 ,2 ]
机构
[1] School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang,330013, China
[2] State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure, East China Jiaotong University, Nanchang,330013, China
关键词
Adhesion - Braking - Controllers - Creep - MATLAB - Railroad cars - Railroad transportation - Railroads - Sliding mode control - Torque - Traction control - Wheels;
D O I
10.19713/j.cnki.43-1423/u.T20211128
中图分类号
学科分类号
摘要
In order to solve the problem that the train traction and braking force are not effectively exerted when the rail surface state changes, a fast adaptive super-twisting (FAST) sliding mode controller was designed considering the strong nonlinearity and time-varying nature of the wheel-rail adhesion state. The train model was established according to the wheel-rail adhesion mechanism and the train operation principle, and the load torque was observed using a full-dimensional state observer and the current rail adhesion coefficient was calculated. On this basis, the sliding mode extreme value algorithm was used to dynamically search for the optimal creep slip speed of the current rail surface. The traction motor torque was controlled by the sliding mode controller designed with the fast adaptive super-twisting algorithm, which enabled the train creep speed to be tracked steadily at the optimal creeping speed of the current rail surface. The MATLAB software was used to simulate the train operation control system designed by the FAST sliding mode controller, and the simulation results were compared with those of the super-twisting sliding mode controller and the standard sliding mode controller. The results show that the FAST algorithm reduces the system stabilization time to 5 seconds and the convergence speed is faster. The creep-slip speed searched at different rail surfaces is stable between the optimal threshold of 1.4~ 1.5 m/s. The trend of torque change is consistent with the trend of rail surface change when the rail surface changes, and the values are stable around 67 200 and 32 720 respectively. After adding disturbance to the model, the system can be stabilized quickly and the relative error of torque is less than ±0.05%, and the controller has strong robustness. It can be seen that the fast adaptive super-twisting algorithm achieves the fast tracking of the best creep speed of the train under different rail surfaces, and makes full use of the maximum adhesion coefficient of the current rail surface. It greatly exerts the train traction and braking force, and realizes the optimal adhesion control of the high-speed train. © 2022, Central South University Press. All rights reserved.
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页码:2143 / 2150
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