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Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments

This study looks into how to make proton exchange membrane (PEM) fuel cells work more efficiently in environments that change over time using new Maximum Power Point Tracking (MPPT) methods. We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo Search (CS) algorithms in a...

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Main Authors: Bouguerra, Assala, Badoud, Abd Essalam, Mekhilef, Saad, Kanouni, Badreddine, Bajaj, Mohit, Zaitsev, Ievgen
Format: Article
Published: Nature Research 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.um.edu.my/46884/
https://doi.org/10.1038/s41598-024-64915-7
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spelling my.um.eprints.468842025-01-16T02:09:03Z http://eprints.um.edu.my/46884/ Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments Bouguerra, Assala Badoud, Abd Essalam Mekhilef, Saad Kanouni, Badreddine Bajaj, Mohit Zaitsev, Ievgen TK Electrical engineering. Electronics Nuclear engineering This study looks into how to make proton exchange membrane (PEM) fuel cells work more efficiently in environments that change over time using new Maximum Power Point Tracking (MPPT) methods. We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo Search (CS) algorithms in adapting to varying conditions, including fluctuations in pressure and temperature. Through meticulous simulations and analyses, the study explores the collaborative integration of these techniques with boost converters to enhance reliability and productivity. It was found that FSSO consistently works better than CS, achieving an average increase of 12.5% in power extraction from PEM fuel cells in a variety of operational situations. Additionally, FSSO exhibits superior adaptability and convergence speed, achieving the maximum power point (MPP) 25% faster than CS. These findings underscore the substantial potential of FSSO as a robust and efficient MPPT method for optimizing PEM fuel cell systems. The study contributes quantitative insights into advancing green energy solutions and suggests avenues for future exploration of hybrid optimization methods. Nature Research 2024-06 Article PeerReviewed Bouguerra, Assala and Badoud, Abd Essalam and Mekhilef, Saad and Kanouni, Badreddine and Bajaj, Mohit and Zaitsev, Ievgen (2024) Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments. Scientific Reports, 14 (1). p. 13946. ISSN 2045-2322, DOI https://doi.org/10.1038/s41598-024-64915-7 <https://doi.org/10.1038/s41598-024-64915-7>. https://doi.org/10.1038/s41598-024-64915-7 10.1038/s41598-024-64915-7
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Bouguerra, Assala
Badoud, Abd Essalam
Mekhilef, Saad
Kanouni, Badreddine
Bajaj, Mohit
Zaitsev, Ievgen
Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
description This study looks into how to make proton exchange membrane (PEM) fuel cells work more efficiently in environments that change over time using new Maximum Power Point Tracking (MPPT) methods. We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo Search (CS) algorithms in adapting to varying conditions, including fluctuations in pressure and temperature. Through meticulous simulations and analyses, the study explores the collaborative integration of these techniques with boost converters to enhance reliability and productivity. It was found that FSSO consistently works better than CS, achieving an average increase of 12.5% in power extraction from PEM fuel cells in a variety of operational situations. Additionally, FSSO exhibits superior adaptability and convergence speed, achieving the maximum power point (MPP) 25% faster than CS. These findings underscore the substantial potential of FSSO as a robust and efficient MPPT method for optimizing PEM fuel cell systems. The study contributes quantitative insights into advancing green energy solutions and suggests avenues for future exploration of hybrid optimization methods.
format Article
author Bouguerra, Assala
Badoud, Abd Essalam
Mekhilef, Saad
Kanouni, Badreddine
Bajaj, Mohit
Zaitsev, Ievgen
author_facet Bouguerra, Assala
Badoud, Abd Essalam
Mekhilef, Saad
Kanouni, Badreddine
Bajaj, Mohit
Zaitsev, Ievgen
author_sort Bouguerra, Assala
title Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
title_short Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
title_full Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
title_fullStr Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
title_full_unstemmed Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
title_sort enhancing pem fuel cell efficiency with flying squirrel search optimization and cuckoo search mppt techniques in dynamically operating environments
publisher Nature Research
publishDate 2024
url http://eprints.um.edu.my/46884/
https://doi.org/10.1038/s41598-024-64915-7
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score 13.244413

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