Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor
An efficient adaptive modeling criterion for the polymer electrolyte membrane fuel cell (PEMFC) is proposed in this paper, which can facilitate its precise simulation, design, analysis and control. In this work, a number of state-of-the-art algorithms have been adapted to optimize the complex electr...
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MDPI AG
2025-04-01
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| Series: | Fuels |
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| Online Access: | https://www.mdpi.com/2673-3994/6/2/30 |
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| author | Mohamed Ahmed Ali Mohey Eldin Mandour Mohammed Elsayed Lotfy |
| author_facet | Mohamed Ahmed Ali Mohey Eldin Mandour Mohammed Elsayed Lotfy |
| author_sort | Mohamed Ahmed Ali |
| collection | DOAJ |
| description | An efficient adaptive modeling criterion for the polymer electrolyte membrane fuel cell (PEMFC) is proposed in this paper, which can facilitate its precise simulation, design, analysis and control. In this work, a number of state-of-the-art algorithms have been adapted to optimize the complex electrochemical PEMFC model. Investigations are carried out not only from the conventional perspective of modeling accuracy but also from a new perspective represented by the impact of process computational time. Here, a novel technique of PEMFC modeling is proposed based on a meta-heuristic optimization algorithm called the wild horse optimizer (WHO). The proposed technique is concerned with the impact of the computational time on dynamic PEMFC modeling. A comprehensive statistical analysis was performed on the results of competing meta-heuristic optimizers that were adapted to a common PEMFC modeling problem. Among them, the proposed WHO approach’s results showed a promising performance in terms of its accuracy and minimum computational time over the other state-of-the-art approaches. For further evaluation of the WHO approach, it was used to optimize additional commercial PEMFC stack models. The results of the WHO approach highlighted its superior performance from the point of view of a high accuracy with a low computational burden, which supports its suitability for online applications. |
| format | Article |
| id | doaj-art-8d20b6c4bd0e48ec8a3c334937215056 |
| institution | Kabale University |
| issn | 2673-3994 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Fuels |
| spelling | doaj-art-8d20b6c4bd0e48ec8a3c3349372150562025-08-20T03:27:07ZengMDPI AGFuels2673-39942025-04-01623010.3390/fuels6020030Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging FactorMohamed Ahmed Ali0Mohey Eldin Mandour1Mohammed Elsayed Lotfy2Egyptian National Railways (ENR), Cairo 11794, EgyptElectrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig 44519, EgyptElectrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig 44519, EgyptAn efficient adaptive modeling criterion for the polymer electrolyte membrane fuel cell (PEMFC) is proposed in this paper, which can facilitate its precise simulation, design, analysis and control. In this work, a number of state-of-the-art algorithms have been adapted to optimize the complex electrochemical PEMFC model. Investigations are carried out not only from the conventional perspective of modeling accuracy but also from a new perspective represented by the impact of process computational time. Here, a novel technique of PEMFC modeling is proposed based on a meta-heuristic optimization algorithm called the wild horse optimizer (WHO). The proposed technique is concerned with the impact of the computational time on dynamic PEMFC modeling. A comprehensive statistical analysis was performed on the results of competing meta-heuristic optimizers that were adapted to a common PEMFC modeling problem. Among them, the proposed WHO approach’s results showed a promising performance in terms of its accuracy and minimum computational time over the other state-of-the-art approaches. For further evaluation of the WHO approach, it was used to optimize additional commercial PEMFC stack models. The results of the WHO approach highlighted its superior performance from the point of view of a high accuracy with a low computational burden, which supports its suitability for online applications.https://www.mdpi.com/2673-3994/6/2/30PEMFC adaptive modelless computational burdencontrol-targeted modelingmodel parameter optimizationwild horse optimization algorithmnumerical statistical analysis |
| spellingShingle | Mohamed Ahmed Ali Mohey Eldin Mandour Mohammed Elsayed Lotfy Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor Fuels PEMFC adaptive model less computational burden control-targeted modeling model parameter optimization wild horse optimization algorithm numerical statistical analysis |
| title | Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor |
| title_full | Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor |
| title_fullStr | Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor |
| title_full_unstemmed | Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor |
| title_short | Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor |
| title_sort | optimal adaptive modeling of hydrogen polymer electrolyte membrane fuel cells based on meta heuristic algorithms considering the membrane aging factor |
| topic | PEMFC adaptive model less computational burden control-targeted modeling model parameter optimization wild horse optimization algorithm numerical statistical analysis |
| url | https://www.mdpi.com/2673-3994/6/2/30 |
| work_keys_str_mv | AT mohamedahmedali optimaladaptivemodelingofhydrogenpolymerelectrolytemembranefuelcellsbasedonmetaheuristicalgorithmsconsideringthemembraneagingfactor AT moheyeldinmandour optimaladaptivemodelingofhydrogenpolymerelectrolytemembranefuelcellsbasedonmetaheuristicalgorithmsconsideringthemembraneagingfactor AT mohammedelsayedlotfy optimaladaptivemodelingofhydrogenpolymerelectrolytemembranefuelcellsbasedonmetaheuristicalgorithmsconsideringthemembraneagingfactor |