{"title":"Optimization of Positioning Parameters for McPherson Front Suspension Based on ADAMS/Car","authors":"Jingjun Zhang, X. Jia, Ziyue Zhao, Ruizhen Gao","doi":"10.1109/CSMA.2015.66","DOIUrl":null,"url":null,"abstract":"A virtual prototype model of a McPherson front suspension is built that is used of ADAMS/Car and based on multi-body system dynamics and conducted the parallel wheel travel simulation. After sensitivity analysis of suspension design factor and optimization of multiple iterations using ADAMS/Insight, the design factor parameter that has great influence for the optimization goal sensitivity is found under the optimization constraints finally. The problem of suspension positioning parameters optimization is better solved by optimizing the design factor parameters.","PeriodicalId":205396,"journal":{"name":"2015 International Conference on Computer Science and Mechanical Automation (CSMA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Computer Science and Mechanical Automation (CSMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSMA.2015.66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A virtual prototype model of a McPherson front suspension is built that is used of ADAMS/Car and based on multi-body system dynamics and conducted the parallel wheel travel simulation. After sensitivity analysis of suspension design factor and optimization of multiple iterations using ADAMS/Insight, the design factor parameter that has great influence for the optimization goal sensitivity is found under the optimization constraints finally. The problem of suspension positioning parameters optimization is better solved by optimizing the design factor parameters.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
