Research on Data Mining Modeling Technology of Charging Fault Characteristics Based on BP Neural Network
编号:239 访问权限:仅限参会人 更新:2022-05-19 09:14:53 浏览:168次 张贴报告

报告开始:暂无开始时间(Asia/Shanghai)

报告时间:暂无持续时间

所在会场:[暂无会议] [暂无会议段]

视频 无权播放 演示文件 附属文件

提示:该报告下的文件权限为仅限参会人,您尚未登录,暂时无法查看。

摘要
The abnormal state monitoring during the charging process of the electric vehicle is mainly the monitoring of the state of the electric vehicle power battery and the monitoring of the running state of the charging pile. In order to realize the safety of electric vehicle charging, this paper firstly clarifies the data mining process and its specific tasks in the process of electric vehicle charging status data processing. Based on data mining technology, a complete set of electric vehicle charging status data processing flow is established. The network established a data mining model of charging fault characteristics, and verified the model through the data of the charging process of electric vehicles on a certain day. safety, and promote the healthy development of electric vehicles.
关键词
electric vehicle;data mining;BP neural network;condition monitoring
报告人
XiangyuBao
南京邮电大学

发表评论
验证码 看不清楚,更换一张
全部评论
重要日期
  • 会议日期

    05月27日

    2022

    05月29日

    2022

  • 02月28日 2022

    初稿截稿日期

  • 05月29日 2022

    注册截止日期

  • 06月22日 2022

    报告提交截止日期

主办单位
IEEE Beijing Section
China Electrotechnical Society
Southeast University
协办单位
IEEE Industry Applications Society
IEEE Nanjing Section
联系方式
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询