自然激励下某电动汽车白车身模态参数识别
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TH113. 1;TN06

基金项目:

广东省特色创新项目(自然科学类)(2017KTSCX218)资助


Modal parameter identification of an electric vehicle body-in-white based on natural excitation
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为了研究电动汽车白车身的动态特性,提出了一种基于自然激励的结构模态参数识别方法。 利用此方法对某电动汽车 白车身进行了结构模态参数识别,得到了其前三阶结构模态参数。 并将利用该方法识别的结果和传统方法识别结果进行了对 比,发现固有频率最大误差为 1. 8%,阻尼比最大误差为 13%,振型基本一致,进而验证了方法的正确性。 之后利用识别的模态 参数结合电动汽车工作特性,对该白车身的动态特性进行了评价。 提出的方法不需要专用的激励设备,可应用于不易激励的大 型、重型结构模态参数识别。 模态参数识别的结果对电动汽车白车身动态特性设计具有一定的指导意义。

    Abstract:

    In order to study the dynamic characteristics of electric vehicle body-in-white, a structural modal parameter identification method based on natural excitation is proposed. By this method, the structural modal parameters of an electric vehicle body-in-white is identified. The first three-order structural modal parameters of the electric vehicle body-in-white are obtained, then the results of identification by this method are compared with those by traditional methods. It is found that the maximum error of natural frequency is 1. 8%, the maximum error of damping ratio is 13%, the modal shape is consistent, the correctness of this method is verified. Then, the dynamic characteristics of the Body-in-white of the electric vehicle are evaluated by the identified structural modal parameters and the working characteristics of the electric vehicle. The proposed natural excitation method simplifies the identification process of structural modal parameters, and can be applied to identify modal parameters of large and heavy structures which are not easy to excite. The results of modal parameter identification have certain guiding significance for the dynamic characteristic design of electric vehicle body in white.

    参考文献
    相似文献
    引证文献
引用本文

李长玉,余莎丽,林子涵,张继华.自然激励下某电动汽车白车身模态参数识别[J].电子测量与仪器学报,2020,34(8):167-173

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2023-11-20
  • 出版日期: