RESEARCH ARTICLE


Comparisons Between Braking Experiments and Longitudinal Train Dynamics Using Friction Coefficient and Braking Pressure Modeling in a Freight Train



Don Bum Choi1, *, Rag-Gyo Jeong2, Yongkook Kim3, Jangbom Chai4
1 Urban Transit Research Team, Korea Railroad Research Institute, Uiwang 16105, Korea
2 Autonomous Train Research Team, Korea Railroad Research Institute, Uiwang 16105, Korea
3 Railroad Type Approval Team, Korea Railroad Research Institute, Uiwang 16105, Korea
4 Mechanical Engineering, 206 Wordlcup-ro, Yeongtong-gu, Suwon16499, Korea


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Creative Commons License
© 2020 Choi et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Urban Transit Research Team, Korea Railroad Research Institute, Uiwang 16105, Korea, Tel:+82314605563;
E-mail: eye@krri.re.kr


Abstract

Background:

This paper describes the predictions and validation of the pneumatic emergency braking performance of a freight train consisting of a locomotive and 20 wagons, generally operated in Korea. It suggests the possibility of replacing the expensive and time-consuming train running tests with longitudinal train dynamic simulations.

Methods:

The simulation of longitudinal train dynamics of a freight train uses the time integration method of EN 14531. For reasonable simulation results, the characteristics of the train and brake equipment must be considered. For the train characteristics, specifications provided by the vehicle manufacturer are used. The braking characteristics are analyzed by friction coefficient tests and a braking pressure model. The friction coefficients of a locomotive and wagons are tested with a dynamo test bench and statistically expanded to account for variability. Freight trains should take into account the braking delay time. To reflect this in the simulation, the brake cylinder pressure pattern model uses pressures and exponential empirical equations measured at selective positions in a train of 50 vehicles. The simulation results are validated in comparison with those of the braking tests of a freight train consisting of 1 locomotive and 20 wagons.

Results:

The results of the longitudinal dynamics simulation show very similar results to the running test results based on the speed profile and braking distance.

Conclusion:

In particular, the statistical expansion method of the friction coefficient enables robust prediction of the distribution of the braking distance. The simulation can reduce or make up for costly and time-consuming repeated braking tests and reduce the risks that may arise during testing.

Keywords: Freight trains, Composite shoes, Friction coefficient, Brake cylinder pressure, Longitudinal train dynamics, Wagon.