Research of Maglev Train Dynamics Simulation Based on Levitation Control Algorithm

Authors

Songqi Li, Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, Southwest Jiaotong University, Chengdu 610031, China;
Kunlun Zhang, Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, Southwest Jiaotong University, Chengdu 610031, China;

Abstract

Abstract: A dynamics model for a whole section of the EMS maglev train was built based on MATLAB, the model described the relationship among body - levitation frame - elastic track and had four degrees of freedom. It simulated and analyzed the vehicle-track coupled vibration dynamic behavior while the vehicle passing the elastic tracks at 200 km/h, using three different kinds of control algorithms respectively. The simulation results show that under the condition of a certain speed and fixed vehicle-track physical parameters, the dynamics behaviors of body - levitation frame - track are obviously different by adopting different control algorithm, and the safety and comfort of maglev vehicle is contradict with each other. The ideal suspension controller algorithm should increase comfort as much as possible under the guarantee for safety. And at the same time, by improving the levitation controller algorithm, the dynamic performance of system in the process of coupled vibration can be enhanced. The study is valuable as reference for optimizing the maglev train levitation controller design.

Recommended Citation

Li, Songqi and Zhang, Kunlun (2020) "Research of Maglev Train Dynamics Simulation Based on Levitation Control Algorithm," Journal of System Simulation: Vol. 27: Iss. 1, Article 24.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss1/24

First Page

179

Revised Date

2014-03-13

DOI Link

https://doi.org/

Last Page

184

CLC

TP273

Recommended Citation

Li Songqi, Zhang Kunlun. Research of Maglev Train Dynamics Simulation Based on Levitation Control Algorithm[J]. Journal of System Simulation, 2015, 27(1): 179-184.