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The British University in Egypt
Proton exchange membrane fuel cells; Efficiency maximization; Energy saving; Dynamic model; Tuna swarm algorithm; Neuro-fuzzy.
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Full-Text Articles in Power and Energy
Synergy Of Neuro-Fuzzy Controller And Tuna Swarm Algorithm For Maximizing The Overall Efficiency Of Pem Fuel Cells Stack Including Dynamic Performance, Hossam Ashraf, Mahmoud M. Elkholy Prof, Sameh O. Abdellatif, Attia A. El-Fergany Prof
Synergy Of Neuro-Fuzzy Controller And Tuna Swarm Algorithm For Maximizing The Overall Efficiency Of Pem Fuel Cells Stack Including Dynamic Performance, Hossam Ashraf, Mahmoud M. Elkholy Prof, Sameh O. Abdellatif, Attia A. El-Fergany Prof
Electrical Engineering
Recently, world endeavors are focused on promoting energy savings by operating both sources and loads at their maximum efficiency points. Thus, this paper presents a novel attempt to optimally determine the operating parameters of an isolated system comprising the proton exchange membrane fuel cells (PEMFCs) stack serving a variable load. A fitness function is adapted to maximize the PEMFCs stack’s efficiency using tuna swarm algorithm (TSA), subjected to set of inequality constraints. A well-known commercial type of PEMFCs stack namely Nedstack PS6 6 kW, are carefully studied over two TSA-based optimization scenarios. The first scenario aims at optimizing five operating …