Validation of railway vehicle dynamic models in training simulators

Ozturk V., Arar O. F., Rende F. S., ÖZTEMEL E., SEZER S.

VEHICLE SYSTEM DYNAMICS, vol.55, no.1, pp.41-71, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 55 Issue: 1
  • Publication Date: 2017
  • Doi Number: 10.1080/00423114.2016.1243720
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.41-71
  • Keywords: Railway vehicle dynamics, validation, training simulator, FUZZY-LOGIC CONTROL, TRACK IRREGULARITIES, VIBRATION CONTROL, ALGORITHMS, FORCES, SYSTEM
  • Yıldız Technical University Affiliated: Yes


Training simulators play an important role for sustaining safety, efficiency and cost effective railway transportation. Dynamic modelling of train systems is one of the main modules of training simulators. Validation of the dynamic models with collected real data ensures the fidelity of the simulator utilising the respective models. In this study, a validation process (Dynamic Modelling Validation Process (DyMVaP)) which is developed to support the validation of railway dynamic models is introduced. However, the proposed process can also be used in validating other dynamic models as well. The developed process is based on five steps including the preparation of validation scenarios, sensor deployment, real data collection, data preparation, and comparison of simulated and measured data. Note that the proposed DyMVaP was used for the validation of a full-mission training simulator so called TRENSIM, which was developed for Turkish State Railways. During the study it is realised that the current speed, travelled distance, acceleration (in x, y, z directions), rotation angles (around x, y, z axes), air pressure, in-train pressure/tension forces, traction motor currents, catenary voltage, positions of controllers must be collected synchronously by using proper sensors in order to ensure simulation validation. The required data was collected from locomotive body, bogies, wheel sets and connection of railway cars. The data (approximate to 200GB) collected from the field by applying 27 different scenarios and transformed into appropriate data for utilising the generated dynamic models within the simulator. The measured and simulated data were also compared visually using graphical representation of the parameters as well as performing computations regarding the magnitude, phase and comprehensive error factors.