Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO
Aiming at the problem that the aggravation of the wheel tread wear of high-speed trains leads to the deterioration of train operation performance and an increase in re-profiling times, a multi-objective data-driven optimization design method for the wheel profile is proposed. Firstly, the chaotic ma...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/13/7/623 |
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| _version_ | 1849246325150842880 |
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| author | Mao Li Hao Ding Meiqi Wang Xingda Yang Bin Kong |
| author_facet | Mao Li Hao Ding Meiqi Wang Xingda Yang Bin Kong |
| author_sort | Mao Li |
| collection | DOAJ |
| description | Aiming at the problem that the aggravation of the wheel tread wear of high-speed trains leads to the deterioration of train operation performance and an increase in re-profiling times, a multi-objective data-driven optimization design method for the wheel profile is proposed. Firstly, the chaotic map is introduced into the population initialization process of the golden jackal algorithm. In the later stage of the algorithm iteration, random disturbance is introduced with optimization algebra as the switching condition to obtain an improved optimization algorithm, and the performance index of the optimization algorithm is verified to be superior to other algorithms. Secondly, the improved multi-objective optimization algorithm and data-driven model are used to optimize the tread coordinates and obtain an optimized profile. The vehicle dynamics performance of the optimized profile and the wheel wear evolution after long-term service are compared. The results show that the tread wear index of the left and right wheels in a straight line is reduced by 62.4% and 62.6%, respectively, and the wear index of the left and right wheels in a curved line is reduced by 26.5% and 5.5%, respectively. The stability and curve passing performance of the optimized profile are improved. Under the long-term service conditions of the train, the wear amount of the optimized profile is greatly reduced. After the wear prediction of 200,000 km, the wear amount of the optimized profile is reduced by 60.1%, and it has better curve-passing performance. |
| format | Article |
| id | doaj-art-6e996b006e6d4e10a65a97d47c57b843 |
| institution | Kabale University |
| issn | 2075-1702 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj-art-6e996b006e6d4e10a65a97d47c57b8432025-08-20T03:58:31ZengMDPI AGMachines2075-17022025-07-0113762310.3390/machines13070623Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJOMao Li0Hao Ding1Meiqi Wang2Xingda Yang3Bin Kong4Guoneng Shuohuang Railway Development Co., Ltd., Cangzhou 062350, ChinaGuoneng Shuohuang Railway Development Co., Ltd., Cangzhou 062350, ChinaSchool of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, ChinaSchool of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, ChinaGuoneng Shuohuang Railway Development Co., Ltd., Cangzhou 062350, ChinaAiming at the problem that the aggravation of the wheel tread wear of high-speed trains leads to the deterioration of train operation performance and an increase in re-profiling times, a multi-objective data-driven optimization design method for the wheel profile is proposed. Firstly, the chaotic map is introduced into the population initialization process of the golden jackal algorithm. In the later stage of the algorithm iteration, random disturbance is introduced with optimization algebra as the switching condition to obtain an improved optimization algorithm, and the performance index of the optimization algorithm is verified to be superior to other algorithms. Secondly, the improved multi-objective optimization algorithm and data-driven model are used to optimize the tread coordinates and obtain an optimized profile. The vehicle dynamics performance of the optimized profile and the wheel wear evolution after long-term service are compared. The results show that the tread wear index of the left and right wheels in a straight line is reduced by 62.4% and 62.6%, respectively, and the wear index of the left and right wheels in a curved line is reduced by 26.5% and 5.5%, respectively. The stability and curve passing performance of the optimized profile are improved. Under the long-term service conditions of the train, the wear amount of the optimized profile is greatly reduced. After the wear prediction of 200,000 km, the wear amount of the optimized profile is reduced by 60.1%, and it has better curve-passing performance.https://www.mdpi.com/2075-1702/13/7/623high-speed trainwheel profilemulti-objective optimizationvehicle dynamics |
| spellingShingle | Mao Li Hao Ding Meiqi Wang Xingda Yang Bin Kong Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO Machines high-speed train wheel profile multi-objective optimization vehicle dynamics |
| title | Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO |
| title_full | Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO |
| title_fullStr | Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO |
| title_full_unstemmed | Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO |
| title_short | Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO |
| title_sort | research on multi objective optimization design of high speed train wheel profile based on rpstc gjo |
| topic | high-speed train wheel profile multi-objective optimization vehicle dynamics |
| url | https://www.mdpi.com/2075-1702/13/7/623 |
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