中南大学学报（自然科学版）2024，Vol.55Issue(5)：1989-1999,11.DOI:10.11817/j.issn.1672-7207.2024.05.029
面向脱轨后被动安全防护的转向架结构优化
Structural optimization for post-derailment passive safety protection of bogie
摘要
Abstract
In order to further verify and optimize the effect of passive safety protection of bogie components,a train dynamics modelling method was proposed based on a polygonal contact model(PCM)and train post-derailment dynamics model was established to simulate the running behaviour with different combinations of structural parameters.The obtained lateral displacement and parameter combinations were used as training samples for a Backpropagation(BP)model to fit the nonlinear relationship between them.The TAGA model was employed to search for the minimum solution of lateral displacement and its corresponding parameter combination.Taking the optimization of the brake disc as an example,the proposed optimization model was applied for structural parameter optimization.The results show that at a derailment speed of 100 km/h,the optimal structural parameter combination for the brake disc is a radius of 335 mm,a thickness of 80 mm,and an installation position of 320 mm.Compared to the original design,the lateral displacement of the vehicle after derailment decreases by 80.2%,significantly improving the passive safety protection capability of the brake disc.The modelling method and optimization model proposed in this paper can be widely applied to the validation and optimization of the passive safety protection capability of other train structures after derailment,demonstrating promising engineering practical value.关键词
脱轨后行为/多边形接触模型(PCM)/结构参数优化/反向传播神经网络/遗传算法Key words
post-derailment behaviour/polygonal contact model(PCM)/structural parameter optimisation/backpropagation neural network/genetic algorithms分类
交通工程引用本文复制引用
胡玉炜,唐兆,陈涛,彭子豪,庄达源..面向脱轨后被动安全防护的转向架结构优化[J].中南大学学报（自然科学版）,2024,55(5):1989-1999,11.基金项目
国家自然科学基金资助项目(52172407) （52172407）
四川省自然科学基金资助项目(2022NSFSC0415) （2022NSFSC0415）
西南交通大学轨道交通运载系统全国重点实验室自主研究课题(2024RVL-T14)(Project(52172407)supported by the National Natural Science Foundation of China （2024RVL-T14）
Project(2022NSFSC0415)supported by the Natural Science Foundation of Sichuan Province （2022NSFSC0415）
Project(2024RVL-T14)supported by the Independent Research Project of the State Key Laboratory of Rail Transit Vehicle System of Southwest Jiaotong University) （2024RVL-T14）
