Modelling of vertical oscillations of a train arising during movement on a railway track with a joint unevenness

Authors

  • Polina Reshetnikova National Technical University «Kharkiv Polytechnic Institute»
  • Oleksandr Zakovorotnyi National Technical University «Kharkiv Polytechnic Institute»

DOI:

https://doi.org/10.26906/SUNZ.2025.1.49-54

Keywords:

mathematical model, decision support system, on-board control systems, rolling stock, oscillatory process, bouncing, galloping, resonant speed

Abstract

Rail transport has been one of the main carriers f goods and passengers in Ukraine for many years. Despite this,
most trains and rails on the main routes are in poor condition. In the context of the ongoing war and the subsequent long post-war
recovery, the issues of extending the life of existing rolling stock and saving energy resources are at the forefront. In addition, to
maintain the competitiveness of trains relative to other modes of transport, the issue of increasing average speeds and passenger
comfort on the railway is crucial. To solve these problems, it is necessary to develop comprehensive models that take into account
factors that significantly affect fuel consumption, safety and passenger comfort. Such factors include rolling stock oscillations This
paper is devoted to the development of a simulation model of vertical oscillations (bouncing and galloping) of the body and bogies of
a train carriage, which depend on unevenness of the railway track. The developed complex simulation model of train car movement
on a track, taking into account vertical oscillations of the car body and its bogies in the MATLAB/Simulink package, allows to study
the dependence of these oscillations on the speed of the rolling stock, parameters of its suspension system and unevenness of the track
under the wheel pairs not only in the mode of maintaining a given speed, but also in the run-up mode and transient modes (acceleration,
deceleration). The obtained simulation model can be used to further study the oscillatory processes of a train on selected sections of
the track, as well as to obtain data for training a neural network for early detection of resonant vibrations of a train car, and can also
be used in decision support systems (DSS) of on-board control systems for rolling stock of Ukrainian trains.

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Published

2025-03-12