火车
汽车工程
量具(枪械)
工程类
变量(数学)
控制理论(社会学)
计算机科学
数学
人工智能
材料科学
数学分析
地图学
控制(管理)
冶金
地理
作者
Yayun Qi,Huanyun Dai,Gan Feng,Hao Gao
标识
DOI:10.1080/00423114.2023.2186250
摘要
Wheel profile optimisation for variable gauge high-speed trains is required to ensure good vehicle operation performance with two rail gauges, therefore, there is an urgent need to further optimise the wheel profile of variable gauge high-speed trains. This paper proposed the IRSFT-KSM-NSGA-II method to optimise a new wheel profile. Firstly, a new three-parameter improved rotary-scaling fine-tuning (IRSFT) wheel profile generation method was proposed. Then a dynamic model of a variable gauge high-speed train is established, and the clearance between the bushings is considered. The dynamic responses of the vehicle with the generated profiles are calculated and analysed. The wheel profile is optimised using the Kriging surrogate model-Non dominated sorting genetic algorithm-II (KSM-NSGA-II) algorithm. Finally, the dynamic and wear performance of the vehicle before and after the wheel optimisation is verified. The critical speed of the variable gauge high-speed trains is effectively increased, and the ride indexes and safety indexes are improved. When the optimised wheel profile LMB10opt is matched with the rail profile CHN60, the maximum wear depth of the wheel profile is reduced by 11.6%. When the LMB10opt is matched with the P65, the maximum wear depth is reduced by 9.7% and the wear is more uniform.
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