Multi-objective optimization of high-speed train suspension parameters for improving hunting stability
Excellent hunting stability is required for the operation of high-speed trains. The suspension parameter design needs to avoid primary and secondary hunting instability for the low and high wheel–rail contact conicity, respectively, as well as to enhance the robustness of hunting stability in face of the variations in wheel–rail contact parameters. In this paper, the indices of low equivalent conicity stability, high conicity stability, and equivalent conicity robustness are defined and chosen as the optimization objectives for the optimal design of key suspension parameters. The multi-objective optimization method is used, and the obtained Pareto set can guide the matching laws of suspension parameters. Four groups of typical parameter sets are selected, and their stability characteristics, such as speed robustness and equivalent conicity robustness, are analysed in detail, followed by the selection of equivalent conicity and motor flexible suspension parameters. Two parameter design modes for the hunting stability can be reflected.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/23248378
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Supplemental Notes:
- © 2021 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Chen, Xiangwang
- Yao, Yuan
- Shen, Longjiang
- Zhang, Xiaoxia
- Publication Date: 2022-3
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 159-176
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Serial:
- International Journal of Rail Transportation
- Volume: 10
- Issue Number: 2
- Publisher: Taylor & Francis
- ISSN: 2324-8378
- EISSN: 2324-8386
- Serial URL: http://www.tandfonline.com/loi/tjrt20
Subject/Index Terms
- TRT Terms: Dynamic stability; High speed rail; Hunting (Dynamics); Optimization; Rolling contact; Suspension systems
- Subject Areas: Railroads; Vehicles and Equipment;
Filing Info
- Accession Number: 01840462
- Record Type: Publication
- Files: TRIS
- Created Date: Mar 28 2022 10:27AM