文献类型：期刊文献

英文题名：Degradation prediction of proton exchange membrane fuel cell based on Bi-LSTM-GRU and ESN fusion prognostic framework

作者：Li, Songyang[1];Luan, Weiling[1];Wang, Chang[1];Chen, Ying[1];Zhuang, Zixian[1]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Key Lab Pressure Syst & Safety MOE, Key Lab Power Battery Syst & Safety CPCIF, Shanghai 200237, Peoples R China

年份：2022

卷号：47

期号：78

起止页码：33466

外文期刊名：INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

收录：;EI(收录号：20223512646138);WOS:【SCI-EXPANDED(收录号:WOS:000864865800001)】；

基金：Acknowledgment This work was supported by Shanghai Automobile Industry Science and Technology Development Foundation (2111) , Fundamental Research Funds for the Central Universities (JKG01211523) .

语种：英文

外文关键词：PEMFC; Prognostic; Remaining useful life; Bi-LSTM-GRU; Deep learning

摘要：The durability of proton exchange membrane fuel cell (PEMFC) is one of the technical challenges restricting its commercial applications. To enhance the reliability and durability of PEMFC, a fusion prognostic framework is proposed based on bi-direction long short-term memory (Bi-LSTM), bi-direction gated recurrent unit (Bi-GRU) and echo state network (ESN), which can achieve short-term degradation prediction and remaining useful life (RUL) estimation of PEMFC with fewer training datasets. For short-term prediction, using the first 200 h of voltage degradation data for training can achieve an acceptable and accurate prediction, with the root mean square error (RMSE), mean absolute error (MAE) and coef-ficient of determination (R2) of 0.0235, 0.0195 and 0.9822, respectively. Compared with traditional machine learning methods, the proposed fusion prognostic framework shows a better predictive performance. In addition, a 100-step-sliding-windows method based on the fusion prognostic framework was implemented for RUL estimation. The results show that the percentage error (Er) is only 1.22% with the first 200 h of training data. The pro-posed method has great significance for online testing and health management of PEMFC.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.