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An Improved Parallel Inverse Design Method of EMU Wheel Profile from Wheel Flange Wear Viewpoint
Author(s) -
Wenjuan Ren,
Li Li,
Dabin Cui,
Guangxiong Chen
Publication year - 2021
Publication title -
shock and vibration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 45
eISSN - 1875-9203
pISSN - 1070-9622
DOI - 10.1155/2021/8895536
Subject(s) - flange , tread , tangent , displacement (psychology) , structural engineering , track (disk drive) , contact force , radius , engineering , materials science , mechanical engineering , computer science , mathematics , geometry , physics , composite material , psychology , natural rubber , computer security , quantum mechanics , psychotherapist
An improved parallel inverse design method is proposed for wheel profile optimization. The dominant merit of this method is the ability to automatically search the target performance curve and obtain the optimized profile without artificial experience. With the help of vehicle system dynamic theory, an EMU model has been established in Simpack, and the dynamic performance is calculated with two profiles, i.e., optimization profile and original profile. The contact and mechanical characters are analyzed by Hertz’s theory, Kalker global algorithm, and CONTACT program. It is found that the rolling radius difference (RRD) with the optimization profile is higher than the original one, especially when the lateral displacement is greater than 3 mm. The creep force density with the optimization profile is significant with a wheelset displacement of 6∼9 mm. Compared with the original one, the distribution of contact points with the optimization profile is more uniform, and the contact position is more biased towards the root of the wheel flange. It means the optimization profile can provide higher RRD value and creep force with large lateral displacement, which is beneficial for reducing wheel flange wear. The dynamic simulation indicates that the optimization profile can help reduce the wheel flange force and wheel flange wear in a sharp curve. Meanwhile, the dynamic behaviors and wheel tread wear on a tangent track or a large curved track are also favorable with the optimization profile.

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