Proton Exchange Membrane Fuel Cell Steady State Modeling Using Marine Predator Algorithm Optimizer
In this paper, the problem concerned is to find the optimum values of the seven uncertain parameters ξ1, ξ2, ξ3, ξ4, λ, Rc, and β of the semi-empirical equation that defines the proton exchange membrane fuel cell (PEMFC) polarization (I/V) relationship using a recent optimization technique, the mari...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/ce079335e4754a369b0a139ddfa9a5ce |
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| Sumario: | In this paper, the problem concerned is to find the optimum values of the seven uncertain parameters ξ1, ξ2, ξ3, ξ4, λ, Rc, and β of the semi-empirical equation that defines the proton exchange membrane fuel cell (PEMFC) polarization (I/V) relationship using a recent optimization technique, the marine predator algorithm (MPA). The main target of this study is to obtain a very precise PEMFC steady state model. The MPA mimics the different random movements of marine predators when foraging and is believed to always converge to a stable value. Three popular stacks namely the Ballard Mark 5 kW, BCS stack 500 W, and Temasek 1 kW are investigated and efficiently modeled. Numerical results show the high accuracy of the MPA-based model when compared with other recently published optimization techniques. |
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