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Integration of a Wear Model into Wheel Profile Optimisation on Metro Vehicles to Mitigate Flange Wear

  • Dexiang Ren
  • Gongquan Tao
  • Zefeng WenEmail author
  • Shulin Liang
  • Hongqin Liang
  • Xuesong Jin
Conference paper
  • 2 Downloads
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

Wheel flange wear often occurs on metro trains when they negotiate sharp curves, especially for the poor matching of wheel and rail profiles or lack of lubrication, which evidently increases the maintenance and replacement costs of the wheelsets and rails. The reason for severe flange wear of the original wheel profile on one metro line in China is investigated through field experiments and numerical simulations. An optimal wheel profile is presented based on the rolling radius difference (RRD) to improve curving performance of the vehicle and mitigate flange wear. A wheel wear prediction model, coupling a metro vehicle dynamics model considering multipoint contact with a long-term wear simulation model, is developed, which is validated using field measurement results. The capability of the optimal wheel profile is numerically evaluated. The results show that the improper wheel-rail profile matching of the original wheel profile is responsible for wheel flange wear. The large proportion of sharp curves and the abnormal rail cant also contribute to flange wear. The optimal wheel profile proves to work fine in terms of wheel/rail contact geometry and wear performance. The wheel flange wear of the optimal wheel profile is decreased by over 60% compared with that of S1002 profile.

Keywords

Wheel flange wear Metro vehicles Wear prediction Wheel profile optimisation 

Notes

Acknowledgement

The present work is supported by the Sichuan Science and Technology Program of China (No. 2019YFH0053), International Science & Technology Cooperation Base of Design and Safety Assessment Technology of Modern Rail Vehicle and the Fundamental Research Funds for the Central Universities (No. A0920502051904-43).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Dexiang Ren
    • 1
  • Gongquan Tao
    • 1
  • Zefeng Wen
    • 1
    Email author
  • Shulin Liang
    • 1
  • Hongqin Liang
    • 2
  • Xuesong Jin
    • 1
  1. 1.State Key Laboratory of Traction PowerSouthwest Jiaotong UniversityChengduChina
  2. 2.School of Mechanical EngineeringSouthwest Jiaotong UniversityChengduChina

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