动车组车顶多响应灵敏度优化分析
 李娅娜,刘靖楠
(大连交通大学 机车车辆工程学院,辽宁 大连 116028)
摘要:为了提升动车组车顶结构刚度,减小质量,并研究车顶结构优化对整车弯曲刚度的影响程度,对其进行多目标尺寸优化。基于整车垂向静载荷工况分析结果和位移插值技术建立动车组车顶子模型,采用折衷规划法将多个子目标拟合为一个多目标函数,同时提出一种多响应灵敏度分析,从而选取符合要求的构件进行优化。经优化车顶子模型质量减小5.5%,垂向最大变形减小8.6%,同时一阶垂弯频率提升2.5%。采用优化后的板梁数据重新计算整车的垂向静载荷工况,结果表明整车弯曲刚度提升3.2%,说明可通过提升车顶刚度性能进而提升整车刚度,为动车组车顶优化设计提供技术参考。
关键词:动车组车顶;多响应灵敏度分析;子模型;多目标优化
中图分类号:U266                文献标志码:A            doi:10.3969/j.issn.1006-0316.2024.03.007
文章编号:1006-0316 (2024) 03-0045-07
Optimization Analysis of Multi-Response Sensitivity of EMU Roof
LI Yana,LIU Jingnan
( School of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China )
Abstract:In order to improve the structural stiffness of EMU roof, and reduce the mass, and to study the influence of roof structure optimization on the vehicle bending stiffness, multi-objective dimensional optimization is carried out. In this paper, a submodel of the EMU roof is established based on the analysis results of vertical static load conditions and displacement interpolation technology. The compromise programming method is used to fit multiple subtargets into a multi-objective function, and a multi-response sensitivity analysis is proposed, so as to select the required components for optimization. The mass of the optimized roof submodel is reduced by 5.5%, the maximum vertical deformation is reduced by 8.6%, and the first-order vertical bending frequency is increased by 2.5%. Using the optimized slab-beam data, the vertical static load condition of the vehicle is recalculated. The results show that the bending stiffness of the vehicle is increased by 3.2%, which indicates that the stiffness of the vehicle can be improved by improving the stiffness performance of the roof, and provides technical reference for the roof optimization design of EMU.
Key words:EMU roof;multi-response sensitivity analysis;submodel;multi-objective optimization
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收稿日期:2023-10-10
基金项目:辽宁省教育厅项目(LJKZ0497)
作者简介:李娅娜(1977-),女,辽宁大连人,博士,教授,主要研究方向为车辆CAD/CAE及其关键技术、焊接残余应力与变形,E-mail:lyn1977522@163.com。


 

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