Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
Abstract 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) algori...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-06-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-64915-7 |
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| author | Assala Bouguerra Abd Essalam Badoud Saad Mekhilef Badreddine Kanouni Mohit Bajaj Ievgen Zaitsev |
| author_facet | Assala Bouguerra Abd Essalam Badoud Saad Mekhilef Badreddine Kanouni Mohit Bajaj Ievgen Zaitsev |
| author_sort | Assala Bouguerra |
| collection | DOAJ |
| description | Abstract 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 |
| id | doaj-art-6aa1eede0f0b44df839392fddce110f2 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-6aa1eede0f0b44df839392fddce110f22025-01-26T12:34:46ZengNature PortfolioScientific Reports2045-23222024-06-0114112810.1038/s41598-024-64915-7Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environmentsAssala Bouguerra0Abd Essalam Badoud1Saad Mekhilef2Badreddine Kanouni3Mohit Bajaj4Ievgen Zaitsev5Automatic Laboratory of Setif, Electrical Engineering Department, University Ferhat Abbas of Setif 1Automatic Laboratory of Setif, Electrical Engineering Department, University Ferhat Abbas of Setif 1School of Software and Electrical Engineering, Swinburne University of TechnologyAutomatic Laboratory of Setif, Electrical Engineering Department, University Ferhat Abbas of Setif 1Department of Electrical Engineering, Graphic Era (Deemed to Be University)Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of UkraineAbstract 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.https://doi.org/10.1038/s41598-024-64915-7Boost converter integrationCuckoo Search (CS)Dynamically operating environmentsFlying Squirrel Search Optimization (FSSO)Maximum power point tracking (MPPT)PEM fuel cell |
| spellingShingle | Assala Bouguerra Abd Essalam Badoud Saad Mekhilef Badreddine Kanouni Mohit Bajaj Ievgen Zaitsev Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments Scientific Reports Boost converter integration Cuckoo Search (CS) Dynamically operating environments Flying Squirrel Search Optimization (FSSO) Maximum power point tracking (MPPT) PEM fuel cell |
| title | 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_short | 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 |
| topic | Boost converter integration Cuckoo Search (CS) Dynamically operating environments Flying Squirrel Search Optimization (FSSO) Maximum power point tracking (MPPT) PEM fuel cell |
| url | https://doi.org/10.1038/s41598-024-64915-7 |
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