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Degradation trajectories prognosis for fuel cell based on MP-NBEATS
编号：31 访问权限：仅限参会人 更新：2023-11-20 13:45:34 浏览：501次 口头报告

报告开始：2023年12月10日 11:15（Asia/Shanghai）

报告时间：15min

所在会场：[S10] Electric Machine Design and control [S10] Electric Machine Design and control

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摘要
The performance degradation trajectory of fuel cells has strong nonlinear characteristics, and accurate and efficient long-term prediction of fuel cell performance degradation is of great significance to protect the safe operation of batteries. Since long-term forecasting of time series is difficult to predict its trend and fluctuation, this paper proposes a multi periodic neural basis expansion analysis for interpretable time series forecasting (MP-NBEATS). This method obtains multiple periods of the series by decomposing the voltage series, and integrates the prediction results of neural basis expansion analysis for interpretable time series forecasting (NBEATS) under different periods, and finally realizes long-term prediction. Compared with the traditional method, this method can better predict the trend and seasonal characteristics of the time series. Finally, through experimental verification, the error of the proposed method can reach 0.983%.
关键词
Fuel cell,Degradation trajectories,MP-NBEATS
报告人
Yuxuan Zheng
Mr. University of Electronic Science and Technology of China

稿件作者
Yuxuan Zheng University of Electronic Science and Technology of China
Huiwen Deng Sichuan Energy Industry Investment Group CO, LTD,
Jianjun Chen University of Electronic Science and Technology of China
Jiaxiang Hu University of Electronic Science and Technology of China
Weihao Hu University of Electronic Science and Technology of China
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重要日期

  • 会议日期

    12月08日

    2023

    至

    12月10日

    2023

  • 11月01日 2023

    初稿截稿日期

  • 12月10日 2023

    注册截止日期

主办单位
IEEE IAS
承办单位
Southwest Jiaotong University (SWJTU)
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