Wheel Profile Evolution Analyses Based on Measured Field Data

Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)


The evolution of three different types of initial wheel profiles in a train with motor and trailer bogies has been investigated. Therefore, wheel profile measurements have been carried out regularly within a wheel re-profiling interval. The wear volume develops in average linearly as a function of mileage. The analysis show, that the initial profile shape and the position where the wheels are located along the train does not significantly influence how the wear volume develops. Furthermore, only little differences were observed when comparing motor and trailer bogies. The same is true for the wear distribution along the profile at the end of the re-profiling interval, although the flange wear of the wheels in the motor bogies is slightly higher. In contrast to this findings the equivalent conicity behaves different. Its development as a function of mileage depends highly on the initial profile shape. Furthermore, it always shows a non-linear s-shaped characteristic. The results of this work are an important basis to develop an advanced methodology which is able to predict the evolution of wheel profiles in an accurate but still efficient way.


Wheel profile evolution Field data Equivalent conicity Wear Wear volume 



The authors would like to acknowledge the financial support of the COMET K2 - Competence Centers for Excellent Technologies Programme of the Federal Ministry for Transport, Innovation and Technology (bmvit), the Federal Ministry for Digital, Business and Enterprise (bmdw), the Austrian Research Promotion Agency (FFG), the Province of Styria and the Styrian Business Promo-tion Agency (SFG). They would furthermore like to express their thanks to their supporting industrial and scientific project partners, namely Siemens Mobility GmbH, voestalpine Schienen GmbH, and to the University of Sheffield.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Virtual Vehicle Research GmbHGrazAustria
  2. 2.Siemens Mobility GmbHGrazAustria

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