机械工程

轿车窗台外侧密封条装配性能的分析与优化方法

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  • 1. 华南理工大学 机械与汽车工程学院,广东 广州 510640; 2. 西南交通大学 机械工程学院,四川 成都 610031; 3. 宁波宏协承汽车部件有限公司,浙 江 宁波 315822
李旻(1974-) ,男,博士,副教授,主要从事机械设计及理论研究

收稿日期: 2017-10-01

  修回日期: 2018-02-28

  网络出版日期: 2018-04-03

基金资助

国家自然科学基金资助项目( 11472107) ;国家留学基金委资助项目( 201706155069)

A Method to Analyze and Optimize Assembly Performance of Outer Seals of Car Window Belt-Line
 

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  • 1. School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,Guangdong, China; 2. School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,Sichuan,China; 3. Ningbo Hongxiecheng Auto Parts Co. ,Ltd. ,Ningbo 315822,Zhejiang,China
李旻(1974-) ,男,博士,副教授,主要从事机械设计及理论研究

Received date: 2017-10-01

  Revised date: 2018-02-28

  Online published: 2018-04-03

Supported by

 Supported by the National Natural Science Foundation of China( 11472107) and China Scholarship Council ( 201706155069) 

摘要

轿车窗台外侧密封条起防水、隔声和美观装饰等作用,装配性能和压缩变形特性 是评价其设计效果的重要指标. 文中提出了窗台外侧密封条装配性能的计算方法,计算了 其装配性能指标,并进行了密封条样品装配性能测试,结果证实了计算方法的正确性. 文 中还以夹持齿的长度、厚度及干涉量等因素为设计变量,建立了窗台外侧密封条的优化模 型. 基于响应面模型和多目标粒子群算法,给出了窗台外侧密封条装配性能的优化方法和 最大改善选解法. 

本文引用格式

李旻 谭孟 上官文斌 李志超 刘杰 尤黎民 . 轿车窗台外侧密封条装配性能的分析与优化方法[J]. 华南理工大学学报(自然科学版), 2018 , 46(5) : 117 -124 . DOI: 10.3969/j.issn.1000-565X.2018.05.016

Abstract

Outer seals of car window beltline play an important role in waterproof,noise insulation and decoration. The assembly and compression performance is an important factor for the evaluation of the design of the outer seals of car window beltline. In this paper,a calculation method for estimating the assembly performance of the outer seals of car window beltline is proposed,and assembly performance parameters are calculated and compared with measured values. The results show that the simulation and calculation method is correct. Then, taking the length, the thickness and the interference of the clamping tooth as design variables,a parametric model of the seals is established. On this basis, the optimization method of the assembly performance of the seals is presented by using the response surface model and multi-objective particle swarm optimization.

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