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Improved fish migration optimization method to identify PEMFC parameters
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DOI：10.1016/j.ijhydene.2023.02.071.png)
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Abstract
En 中文
In a worldwide environment context where the emergency need to decrease pollutant emissions is an important issue, the research for solutions is increasing. Fuel cell technology is anticipated to become a practicable approach for solving the problem of pollution due to its environmentally friendly characteristics. In this work, a novel problem formulation is sug-gested for the efficient recognition of PEMFC parameters which the solving is by using the Improved Fish Migration Optimizer (IFMO) technique. After coding the steps of the algorithm in MATLAB, the objective function is resolved for the fuel cell. Comprehensive simulations evaluate the formulation performance with the suggested and traditional objective functions; then, the outcomes are compared. To confirm the suggested formulation ascendancy compared to the traditional curve-fitting method, a complete assessment based on conver-gence rate, the value of the objective function, and the value of absolute voltage error are performed. The achieved value of the objective function, absolute voltage error, and average time of computation is 0.005, 0.4, and 1.63, respectively. Environmentally, the combustion of hydrogen and its use in PEMFC produce no carbon dioxide. & COPY; 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Keywords:
PEMFC
Modeling of the fuel cell
Environmental consideration
Improved fish migration optimizer
Extraction of fuel cell parameter
Journal
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8.3
Papers:
5.5W
Citations:
23.1W
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