Real-time prediction models for remaining cold start time in proton exchange membrane fuel cell based on stack temperature

Real-time prediction models for remaining cold start time in proton exchange membrane fuel cell based on stack temperature

In order to mitigate the irreversible damage caused by cold start and preserve cell performance, this paper proposes a real-time prediction method based on the remaining cold start time of the proton exchange membrane fuel cell (PEMFC). This method can protect the cell by referencing the current col...

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Podrobná bibliografie
Hlavní autoři: Huiying Zhang, Yuhang Wang, Suoying He, Ming Gao
Médium: Článek
Jazyk:English
Vydáno: Elsevier 2023-12-01
Edice:Case Studies in Thermal Engineering
Témata:
Back propagation neural network
Cold start
Hybrid prediction method
Long short-term memory neural network
Proton exchange membrane fuel cell
Real-time prediction
On-line přístup:http://www.sciencedirect.com/science/article/pii/S2214157X23010006

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