An LSTM and ANN Fusion Dynamic Model of a Proton Exchange Membrane Fuel Cell-Reference-Cited by-同舟云学术

An LSTM and ANN Fusion Dynamic Model of a Proton Exchange Membrane Fuel Cell

Published:2023-04 Issue:4 Volume:19 Page:5743-5751
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Li Wei¹^ORCID,Wang Xinli¹^ORCID,Wang Lei¹^ORCID,Jia Lei¹^ORCID,Song Rui¹^ORCID,Fu Zhichao²,Xu Wenjie³

Affiliation:

1. School of Control Science and Engineering, Shandong University, Jinan, China

2. Wuhan Institute of Marine Electric Propulsion, Wuhan, China

3. Foresight Energy Co., Ltd., Suzhou, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Science Fund for Creative Research Groups

Young Scholars Program of Shandong University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/10081096/09851451.pdf?arnumber=9851451

Reference28 articles.

1. Performance prediction and power density maximization of a proton exchange membrane fuel cell based on deep belief network

2. Online system identication of a fuel cell stack with guaranteed stability for energy management applications;kandidayeni;IEEE Trans Energy Convers,2021

3. A Control-Oriented Model of a PEM Fuel Cell Stack Based on NARX and NOE Neural Networks

4. An intelligent parametric modeling and identification of a 5 kW ballard PEM fuel cell system based on dynamic recurrent networks with delayed context units;gomathi;Int J Hydrogen Energy,2021

5. Identification of a Proton-Exchange Membrane Fuel Cell’s Model Parameters by Means of an Evolution Strategy

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