High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
<p dir="ltr">Development and modeling of proton exchange membrane fuel cells (PEMFCs) need accurate identification of unknown factors affecting mathematical models. The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, mak...
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2025
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| _version_ | 1864513524419526656 |
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| author | Badreddine Kanouni (23073244) |
| author2 | Abdelbaset Laib (16904688) Salah Necaibia (23073247) Abdelbasset Krama (16870008) Ilyas Bennia (23073250) Sertac Bayhan (16388511) |
| author2_role | author author author author author |
| author_facet | Badreddine Kanouni (23073244) Abdelbaset Laib (16904688) Salah Necaibia (23073247) Abdelbasset Krama (16870008) Ilyas Bennia (23073250) Sertac Bayhan (16388511) |
| author_role | author |
| dc.creator.none.fl_str_mv | Badreddine Kanouni (23073244) Abdelbaset Laib (16904688) Salah Necaibia (23073247) Abdelbasset Krama (16870008) Ilyas Bennia (23073250) Sertac Bayhan (16388511) |
| dc.date.none.fl_str_mv | 2025-10-03T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2025.3614048 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/High-Accurate_Parameter_Identification_of_PEMFC_Using_Advanced_Multi-Trial_Vector-Based_Sine_Cosine_Meta-Heuristic_Algorithm/31168486 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Chemical engineering Electrical engineering Multi-trial vector-based sine cosine algorithm (MTV-SCA) hydrogen energy parameters extraction proton exchange membrane fuel cell sustainable energy |
| dc.title.none.fl_str_mv | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Development and modeling of proton exchange membrane fuel cells (PEMFCs) need accurate identification of unknown factors affecting mathematical models. The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. This paper introduces a novel multi-trial vector-based sine cosine algorithm (MTV-SCA) for the identification of seven unknown parameters of PEMFCs. The proposed MTV-SCA incorporates MTV methodology utilizing three control parameters to achieve the desired optimization targets. A key contribution of this work is the development of four distinct search strategies, to mitigating early convergence issues. These strategies leverage various sinusoidal and cosinusoidal factors to improve the algorithm. The optimization goal is to minimize sum square error (SSE) between measured and simulated stack voltages. Five PEMFC stack mode:250W, BCS 500W, SR-12, H-12, and Temasek 1 kW, validate the MTV-SCA algorithm’s efficacy and robustness Compared to previously established optimization approaches, MTV-SCA extracts optimum PEMFC parameters more accurately and reliably. Statistical testing further demonstrates the method’s durability and consistency. Analyzing PEMFC performance at different pressures and temperatures helps verify the adjusted parameters. Simulations show that the MTV-SCA solves difficult PEMFC parameter identification issues better than SCA and other approaches.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3614048" target="_blank">https://dx.doi.org/10.1109/access.2025.3614048</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_6c5d73bc65e638106cba5d83d27234f7 |
| identifier_str_mv | 10.1109/access.2025.3614048 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/31168486 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic AlgorithmBadreddine Kanouni (23073244)Abdelbaset Laib (16904688)Salah Necaibia (23073247)Abdelbasset Krama (16870008)Ilyas Bennia (23073250)Sertac Bayhan (16388511)EngineeringChemical engineeringElectrical engineeringMulti-trial vector-based sine cosine algorithm (MTV-SCA)hydrogen energyparameters extractionproton exchange membrane fuel cellsustainable energy<p dir="ltr">Development and modeling of proton exchange membrane fuel cells (PEMFCs) need accurate identification of unknown factors affecting mathematical models. The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. This paper introduces a novel multi-trial vector-based sine cosine algorithm (MTV-SCA) for the identification of seven unknown parameters of PEMFCs. The proposed MTV-SCA incorporates MTV methodology utilizing three control parameters to achieve the desired optimization targets. A key contribution of this work is the development of four distinct search strategies, to mitigating early convergence issues. These strategies leverage various sinusoidal and cosinusoidal factors to improve the algorithm. The optimization goal is to minimize sum square error (SSE) between measured and simulated stack voltages. Five PEMFC stack mode:250W, BCS 500W, SR-12, H-12, and Temasek 1 kW, validate the MTV-SCA algorithm’s efficacy and robustness Compared to previously established optimization approaches, MTV-SCA extracts optimum PEMFC parameters more accurately and reliably. Statistical testing further demonstrates the method’s durability and consistency. Analyzing PEMFC performance at different pressures and temperatures helps verify the adjusted parameters. Simulations show that the MTV-SCA solves difficult PEMFC parameter identification issues better than SCA and other approaches.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3614048" target="_blank">https://dx.doi.org/10.1109/access.2025.3614048</a></p>2025-10-03T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2025.3614048https://figshare.com/articles/journal_contribution/High-Accurate_Parameter_Identification_of_PEMFC_Using_Advanced_Multi-Trial_Vector-Based_Sine_Cosine_Meta-Heuristic_Algorithm/31168486CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/311684862025-10-03T09:00:00Z |
| spellingShingle | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm Badreddine Kanouni (23073244) Engineering Chemical engineering Electrical engineering Multi-trial vector-based sine cosine algorithm (MTV-SCA) hydrogen energy parameters extraction proton exchange membrane fuel cell sustainable energy |
| status_str | publishedVersion |
| title | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm |
| title_full | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm |
| title_fullStr | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm |
| title_full_unstemmed | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm |
| title_short | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm |
| title_sort | High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm |
| topic | Engineering Chemical engineering Electrical engineering Multi-trial vector-based sine cosine algorithm (MTV-SCA) hydrogen energy parameters extraction proton exchange membrane fuel cell sustainable energy |