• 论文 •    

基于灰色理论的车门系统参数多目标优化

华尔天,周科,费玉莲,曹魏魏   

  1. 浙江工商大学 计算机与信息工程学院,浙江杭州310018
  • 出版日期:2012-03-15 发布日期:2012-03-25

Multi-objective optimization for automotive door parameters based on grey theory

HUA Er-tian, ZHOU Ke, FEI Yu-lian, CAO Wei-wei   

  1. College of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
  • Online:2012-03-15 Published:2012-03-25

摘要: 针对车门系统设计参数选择问题,提出了一种基于灰色理论的参数多目标优化方法。对车门系统设计参数中的可控因子进行正交试验设计,利用有限元方法获取车门下沉量和车门质量在不同参数组合下的响应值,并依据不同参数组合下的车门制造工艺确定车门成本。采用灰色相关理论对试验结果进行计算和分析,得到各因子在不同水平下与车门下沉量、车门质量、车门成本的关联系数和关联度,确定了一组各因子的优选组合,经试验验证,取得了较好的效果。

关键词: 灰色关联度, 车门系统, 正交试验, 多目标优化

Abstract: Aming at the selection problem of automotive door system design parameters, a multi-objective parameters optimization approach based on grey theory was proposed. The controllable factors in door design parameters were designed by orthogonal experiment. The influence value of sinking and mass under different parameters combination were obtained by using finite element method, and the door cost was determined according to different door manufacturing process. The test results were calculated and analyzed by grey theory, thus the correlation coefficient and correlation degree between factors in different level and sinking, mass and cost of automotive door were obtained. A set of optimum combination of each factor was determined, and the well effect was achieved by experimental verification.

Key words: grey correlation, automotive door system, orthogonal experiment, multi-objective optimization

中图分类号: