双质量飞轮参数影响规律分析及优化设计

IF 3.4 Q1 ENGINEERING, MECHANICAL 国际机械系统动力学学报(英文) Pub Date : 2022-07-20 DOI:10.1002/msd2.12046
Guangqiang Wu, Guoqiang Zhao
{"title":"双质量飞轮参数影响规律分析及优化设计","authors":"Guangqiang Wu,&nbsp;Guoqiang Zhao","doi":"10.1002/msd2.12046","DOIUrl":null,"url":null,"abstract":"<p>The influence of the dynamic parameters of a dual mass flywheel (DMF) on its vibration reduction performance is analyzed, and several optimization algorithms are used to carry out multiobjective DMF optimization design. First, the vehicle powertrain system is modeled according to the parameter configuration of the test vehicle. The accuracy of the model is verified by comparing the simulation data with the test results. Then, the model is used to analyze the influence of the moment of inertia ratio, torsional stiffness, and damping in reducing DMF vibration. The speed fluctuation amplitude at the transmission input shaft and the natural frequency of the vehicle are taken as the optimization objectives. The passive selection method, multiobjective particle swarm optimization, and the nondominated sorting genetic algorithm based on an elite strategy are used to carry out DMF multiobjective optimization design. The advantages and disadvantages of these algorithms are evaluated, and the best optimization algorithm is selected.</p>","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.12046","citationCount":"8","resultStr":"{\"title\":\"Parameter influence law analysis and optimal design of a dual mass flywheel\",\"authors\":\"Guangqiang Wu,&nbsp;Guoqiang Zhao\",\"doi\":\"10.1002/msd2.12046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The influence of the dynamic parameters of a dual mass flywheel (DMF) on its vibration reduction performance is analyzed, and several optimization algorithms are used to carry out multiobjective DMF optimization design. First, the vehicle powertrain system is modeled according to the parameter configuration of the test vehicle. The accuracy of the model is verified by comparing the simulation data with the test results. Then, the model is used to analyze the influence of the moment of inertia ratio, torsional stiffness, and damping in reducing DMF vibration. The speed fluctuation amplitude at the transmission input shaft and the natural frequency of the vehicle are taken as the optimization objectives. The passive selection method, multiobjective particle swarm optimization, and the nondominated sorting genetic algorithm based on an elite strategy are used to carry out DMF multiobjective optimization design. The advantages and disadvantages of these algorithms are evaluated, and the best optimization algorithm is selected.</p>\",\"PeriodicalId\":60486,\"journal\":{\"name\":\"国际机械系统动力学学报(英文)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2022-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.12046\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"国际机械系统动力学学报(英文)\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/msd2.12046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"国际机械系统动力学学报(英文)","FirstCategoryId":"1087","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/msd2.12046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 8

摘要

分析了双质量飞轮(DMF)动力学参数对其减振性能的影响,并采用几种优化算法进行了多目标DMF优化设计。首先,根据试验车辆的参数配置,对整车动力总成系统进行建模。通过仿真数据与试验结果的对比,验证了模型的准确性。然后,利用该模型分析了转动惯量比、扭转刚度和阻尼对DMF减振的影响。以变速器输入轴处的速度波动幅值和车辆固有频率为优化目标。采用被动选择法、多目标粒子群算法和基于精英策略的非支配排序遗传算法进行DMF多目标优化设计。对这些算法的优缺点进行了评价,并选择了最佳的优化算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Parameter influence law analysis and optimal design of a dual mass flywheel

The influence of the dynamic parameters of a dual mass flywheel (DMF) on its vibration reduction performance is analyzed, and several optimization algorithms are used to carry out multiobjective DMF optimization design. First, the vehicle powertrain system is modeled according to the parameter configuration of the test vehicle. The accuracy of the model is verified by comparing the simulation data with the test results. Then, the model is used to analyze the influence of the moment of inertia ratio, torsional stiffness, and damping in reducing DMF vibration. The speed fluctuation amplitude at the transmission input shaft and the natural frequency of the vehicle are taken as the optimization objectives. The passive selection method, multiobjective particle swarm optimization, and the nondominated sorting genetic algorithm based on an elite strategy are used to carry out DMF multiobjective optimization design. The advantages and disadvantages of these algorithms are evaluated, and the best optimization algorithm is selected.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.50
自引率
0.00%
发文量
0
期刊最新文献
Issue Information Cover Image, Volume 4, Number 3, September 2024 Design of bionic water jet thruster with double-chamber driven by electromagnetic force A data-assisted physics-informed neural network (DA-PINN) for fretting fatigue lifetime prediction Comparison of the performance and dynamics of the asymmetric single-sided and symmetric double-sided vibro-impact nonlinear energy sinks with optimized designs
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1