Numerical Modeling of Wear on Powered Railway Wheelset Under Various Operating Conditions

Abstract

Wheel wear prediction is a high priority in rolling stock research since it has a significant influence on performance, maintenance, and safety risks. It is crucial for the planning of reprofiling and replacement operations, estimating residual life, and managing the wheels supply chain. The evolution of wheel profile due to wear is a critical and complex issue strongly depending on operating conditions. In this work, a numerical modeling process, based on a multi-body modeling approach for wheel wear prediction, is presented and applied to a locomotive designed to operate in various operational situations. The modeling methodology includes track and vehicle multi-body model, wheel-rail contact solving with Hertz and FASTSIM models and wear computation using Archard model. Numerical simulations have been performed for different operating configurations in order to evaluate the influence of rail profile, track curves, and operating speed on volume and depth distribution of wheel wear in locomotive’s powered wheelset. The results show that the UIC60 rail profile is significantly better than the AREMA profile for wheels with the S1002 profile. It has been also found out that both increasing the speed and reducing the radius of curvature increase wheel wear.