Skip to main content
main-content
Top

Hint

Swipe to navigate through the chapters of this book

2020 | OriginalPaper | Chapter

Optimization of a Tram Wheel Profile to Reduce Flange Wear on Sharp Curves

Authors: Zhang Chen, Liang Ling, Yu Sun, Yichang Zhou, Kaiyun Wang, Wanming Zhai

Published in: Advances in Dynamics of Vehicles on Roads and Tracks

Publisher: Springer International Publishing

share
SHARE

Abstract

Owing to the existing of many sharp curves, the fast wear of wheel flanges has become a big problem in a Chinese tramway. To reduce the wheel flange wear rate and increase the lifetime of tram wheels, the authors have conducted extensive experimental measurements and numerical analyses. The long-term tracking measurement concentrating on the natural wear process of the tram wheels have been carried out. This paper reports the flange wear characteristics and developing law of the tram wheels based on measured data. An optimal wheel profile for the tram vehicle was proposed based on a large number of multi-body dynamics simulations. The wear and curving performances of the original and optimal wheel profiles were compared through dynamics simulation. The results show that the optimal profile can improve both the wear and dynamic curving performances of the tram vehicle.
Literature
1.
go back to reference Choi, H., Lee, D., Lee, J.: Optimization of a railway wheel profile to minimize flange wear and surface fatigue. Wear 300, 225–233 (2013) CrossRef Choi, H., Lee, D., Lee, J.: Optimization of a railway wheel profile to minimize flange wear and surface fatigue. Wear 300, 225–233 (2013) CrossRef
2.
go back to reference Szabó, A., Zobory, I.: On deterministic and stochastic simulation of wheel and rail profile wear process. Period. Polytech. Transp. Eng. 26(1–2), 3–17 (1998) Szabó, A., Zobory, I.: On deterministic and stochastic simulation of wheel and rail profile wear process. Period. Polytech. Transp. Eng. 26(1–2), 3–17 (1998)
3.
go back to reference Persson, I., Iwnicki, S.: Optimisation of railway profiles using a genetic algorithm. Veh. Syst. Dyn. 41, 517–527 (2004) Persson, I., Iwnicki, S.: Optimisation of railway profiles using a genetic algorithm. Veh. Syst. Dyn. 41, 517–527 (2004)
4.
go back to reference Braghin, F., Lewis, R., Dwyer-Joyce, R., Bruni, S.: A mathematical model to predict railway wheel profile evolution due to wear. Wear 261(11), 1253–1264 (2006) CrossRef Braghin, F., Lewis, R., Dwyer-Joyce, R., Bruni, S.: A mathematical model to predict railway wheel profile evolution due to wear. Wear 261(11), 1253–1264 (2006) CrossRef
5.
go back to reference Enblom, R.: Deterioration mechanisms in the wheel-rail interface with focus on wear prediction: a literature review. Veh. Syst. Dyn. 47(6), 661–700 (2009) CrossRef Enblom, R.: Deterioration mechanisms in the wheel-rail interface with focus on wear prediction: a literature review. Veh. Syst. Dyn. 47(6), 661–700 (2009) CrossRef
6.
go back to reference Liu, B., Mei, T., Bruni, S.: Design and optimisation of wheel–rail profiles for adhesion improvement. Veh. Syst. Dyn. 54, 429–444 (2016) CrossRef Liu, B., Mei, T., Bruni, S.: Design and optimisation of wheel–rail profiles for adhesion improvement. Veh. Syst. Dyn. 54, 429–444 (2016) CrossRef
7.
go back to reference Sun, Y., Guo, Y., Zhai, W.: Prediction of rail non-uniform wear–Influence of track random irregularity. Wear 420–421, 235–244 (2019) CrossRef Sun, Y., Guo, Y., Zhai, W.: Prediction of rail non-uniform wear–Influence of track random irregularity. Wear 420–421, 235–244 (2019) CrossRef
8.
go back to reference Meghoe, A., Loendersloot, R., Tinga, T.: Rail wear and remaining life prediction using meta-models. Int. J. Rail Transp. 8, 1–26 (2019) CrossRef Meghoe, A., Loendersloot, R., Tinga, T.: Rail wear and remaining life prediction using meta-models. Int. J. Rail Transp. 8, 1–26 (2019) CrossRef
Metadata
Title
Optimization of a Tram Wheel Profile to Reduce Flange Wear on Sharp Curves
Authors
Zhang Chen
Liang Ling
Yu Sun
Yichang Zhou
Kaiyun Wang
Wanming Zhai
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-38077-9_94

Premium Partner