An Explainable Data-Driven Framework for Fuel Cell Aging Prediction Under Dynamic Condition-Reference-Cited by-同舟云学术

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An Explainable Data-Driven Framework for Fuel Cell Aging Prediction Under Dynamic Condition

Published:2023-06 Issue:6 Volume:70 Page:5960-5970
ISSN:0278-0046
Container-title:IEEE Transactions on Industrial Electronics
language:
Short-container-title:IEEE Trans. Ind. Electron.

Author:

Xie Renyou¹^ORCID,Li Chaojie²^ORCID,Ma Rui¹^ORCID,Xu Liangcai³^ORCID,Zhou Xiaojun⁴^ORCID

Affiliation:

1. School of Automation, Northwestern Polytechnical University, Xi'an, China

2. School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia

3. Department of Mechanical Engineering, National University of Singapore, Singapore

4. School of Automation, Central South University, Changsha, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/41/10026526/09866604.pdf?arnumber=9866604

Reference26 articles.

1. Prognostic for fuel cell based on particle filter and recurrent neural network fusion structure

2. A hybrid remaining useful life prognostic method for proton exchange membrane fuel cell

3. Remaining Useful Life Prediction and Uncertainty Quantification of Proton Exchange Membrane Fuel Cell Under Variable Load

4. Proton exchange membrane fuel cell degradation prediction based on Adaptive Neuro-Fuzzy Inference Systems

5. Remaining useful life prediction of PEMFC based on long short-term memory recurrent neural networks

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1. A real-time prediction method for PEMFC life under actual operating conditions;Sustainable Energy Technologies and Assessments;2024-10

2. Degradation prediction of PEMFC based on BiTCN-BiGRU-ELM fusion prognostic method;International Journal of Hydrogen Energy;2024-10

3. Health state monitoring and predicting of proton exchange membrane fuel cells: A review;Journal of Power Sources;2024-08

4. A model with high-precision on proton exchange membrane fuel cell performance degradation prediction based on temporal convolutional network-long short-term memory;International Journal of Hydrogen Energy;2024-07

5. A novel generalized prognostic method of proton exchange membrane fuel cell using multi-point estimation under various operating conditions;Applied Energy;2024-03

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