A Study on Prediction of the Remaining Useful Life of PEMFC Based on Data-driven CNN-BILSTM
Author:
Affiliation:
1. School of Logistics Engineering, Shanghai Maritime University, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3641343.3641383
Reference23 articles.
1. Research on proton exchange membrane fuel cell life prediction based on machine learning [J];Lan Yu;Modern Machinery
2. Investigation of the effect of cathode stoichiometry of proton exchange membrane fuel cell using localized electrochemical impedance spectroscopy based on print circuit board
3. PEMFC power generation system FFRLS online identification and real-time optimal temperature generalized predictive control method [J];Yin Liangzhen;Chinese Journal of Electrical Engineering,2017
4. Research on HOSM observer suitable for peroxide estimation in PEMFC systems [J];Deng Huiwen;Chinese Journal of Electrical Engineering,2017
5. Proton exchange membrane fuel cell degradation prediction based on Adaptive Neuro-Fuzzy Inference Systems
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