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A PEMFC model optimization using the enhanced bald eagle algorithm
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DOI：10.1016/j.asej.2022.101749.png)
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摘要
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In this article, a novel optimization algorithm is implemented to estimate the design variables of proton exchange membrane fuel cells. The main objective is to get the minimum of the sum of squared errors (SSE), which is defined as the difference between the measured and the calculated data. The newly devel-oped optimization algorithm is known as the Enhanced Bald Eagle Search (EBES) Optimization Algorithm. To verify the proposed algorithm, three tested cases are introduced: BCS 500 W, 250 W, and Horizon H-12 stacks. To study the impact of pressure and temperature variation on the proposed algorithm, the studied cases are repeated under various pressure and temperature conditions. One obstacle to be solved is a nonlinear complex problem that requires an efficient optimization algorithm. A comparison with the existing optimization algorithms is conducted which confirms the effectiveness of the newly developed EBES algorithm. (c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keyword:
Bald eagle search
Experimental results
Optimization algorithms
PEMFCs parameters estimation
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5.9
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3.4K
被引数:
1.2W
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Equilibrium optimizer for parameter extraction of a fuel cell dynamic model.png)
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