Proton Exchange Membrane Fuel Cells: An Effective Neural Fuzzy System for Optimal Power Tracking
| Autor: | Assala Bouguerra, Abd Essalam Badoud, Saad Mekheilef |
|---|---|
| Jazyk: | English<br />French |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Revue des Énergies Renouvelables, Pp 151 – 164-151 – 164 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1112-2242 2716-8247 |
| DOI: | 10.54966/jreen.v1i3.1299 |
| Popis: | The revolutionary future of proton-exchanging membrane fuel cells (PEMFC) has recently garnered a great deal of excitement, as has their green energy source. Maximizing the production of electricity from PEMFC is crucial to maintaining effectiveness. This research article thoroughly analyzes a research study using a strategy known as MPPT, or maximum power point tracking that uses the neuro-fuzzy method for PEMFC operating under diverse temperatures, pressures, and joining constraints. The neuro-fuzzy controller cleverly regulates the point of maximal operation of a hydrogen fuel cell system, allowing exact adherence to the highest possible power scale. According to simulation results, the neuro-fuzzy MPPT technique improves PEMFC validity across a wide range of operating scenarios. |
| Databáze: | Directory of Open Access Journals |
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