Abstract
The CRH1 train is one of the main commuter trains in China which is mostly operating on typical and high-speed lines. Previously, a high-speed car wheel profile was used on the CRH1 train, but it does not match well with the train suspension parameters and also causes the instability of the train on tangent track and large curved track. Therefore, a new profile was designed as the replacement of the old one for the CRH1 train. However, the use of the new profile results in the serious wheel flange and rail gauge corner wear but it can provide better stability compared to the old profile. This paper first presents the evaluation of using the two profiles, and then a development of the wheel profile is objected in terms of both currently used profiles, which is not only to minimize the flange wear and also take the vehicle dynamic behavior into consideration. A multi-objective optimization method was, therefore, to propose for the minimization of the lateral force and the stability of wheelsets. The requirements of the wheel profile geometry are investigated through proposed optimization method. Finally, the profile satisfied the safety requirements of the vehicle has been provided by using the particle swarm optimization method. Furthermore, the evaluation of vehicle dynamic has been performed by using Multi-Body Simulation Software. The entire design process has been completed in a closed-loop procedure programed in MATLAB. The findings show that the developed profile after the optimization procedure is fairly acceptable for the requirements of the wheel-rail interface and dynamic behavior of CRH1 train.
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Funding
The present work has been supported by the National Natural Science Foundation of China (Nos. 51605394 and U1434210), the Department of Education Foundation of Sichuan Province (No. 16ZB0011), and the Key Research Project of Leshan City (No. 16ZDYJ0147).
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Cui, D., Wang, R., Allen, P. et al. Multi-objective optimization of electric multiple unit wheel profile from wheel flange wear viewpoint. Struct Multidisc Optim 59, 279–289 (2019). https://doi.org/10.1007/s00158-018-2065-5
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DOI: https://doi.org/10.1007/s00158-018-2065-5