Machine learning for guiding high-temperature PEM fuel cells with greater power density

Machine learning for guiding high-temperature PEM fuel cells with greater power density

Summary: High-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs) are enticing energy conversion technologies because they use low-cost hydrogen generated from methane and have simple water and heat management. However, proliferation of this technology requires improvement in power densi...

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Bibliographic Details
Main Authors: Luis A. Briceno-Mena, Gokul Venugopalan, José A. Romagnoli, Christopher G. Arges
Format: Article
Language:English
Published: Elsevier 2021-02-01
Series:Patterns
Subjects:
high-temperature polymer electrolyte membrane (HT-PEM) fuel cell
machine learning
modeling
clustering
dimension reduction
Online Access:http://www.sciencedirect.com/science/article/pii/S2666389920302579

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http://www.sciencedirect.com/science/article/pii/S2666389920302579

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