Abstract
Recently, much attention was paid to the application of renewable energy in environmental issues. Meanwhile, the fuel cell industry, which is considered an environmentally friendly industry, is one of the important components of this project. They are in fact devices for the direct conversion of chemical energy into electrical energy by an electrochemical reaction without the need for any mechanical parts. In this study, it is attempted to model one of their important types, called proton exchange membrane fuel cells, so that it can be used in predicting the behavior of the fuel cell and examining various parameters affecting the performance of the cell. The main idea is to optimal parameters estimation for the proton exchange membrane fuel cells by minimizing the total Squared Error value between the empirical output voltage and the approximated output voltage. For giving better results in terms of accuracy and reliability, a new design of a metaheuristic called the balanced Water Strider Algorithm is utilized. The results of the suggested method are finally validated by comparison with several latest optimizers applied on a practical test case. After running all of the optimizers 30 times independently, the proposed method with minimum absolute error equals 3.4831e−4 shows the best results toward the others.
Highlights
Fuel cells are a new technology for generating energy that produces high-efficiency electricity from a direct combination of fuel and oxidant without causing environmental or noise pollution
Proton exchange membrane fuel cells can be replaced by internal combustion engines for transport applications which is because they have outstanding characteristics such as high efficiency, solid electrolyte, production of electrical energy without making pollution, diversity, no noise, and short start-up time
– Design an optimal model for the Proton exchange membrane fuel cells (PEMFCs) – Minimize the total Squared Error between the empirical and the estimated output voltage. – A new balanced Water Strider Algorithm is used for minimization. – The results are validated by comparison with several latest optimizers and a practical test case
Summary
Fuel cells are a new technology for generating energy that produces high-efficiency electricity from a direct combination of fuel and oxidant without causing environmental or noise pollution. Proton exchange membrane fuel cells can be replaced by internal combustion engines for transport applications which is because they have outstanding characteristics such as high efficiency, solid electrolyte, production of electrical energy without making pollution, diversity, no noise, and short start-up time. The technique was relied on using the Developed Sunflower Optimizer (DSFO) as a tool for minimizing the error between the observed and the produced voltage outputs of the PEMFCs. To verify the technique, it was applied to two practical models and a comparison of its results with some various methods was carried out (Fei et al, 2019). Xu et al (2020) suggested another method for optimal variables recognition for high-temperature proton exchange membrane fuel cells (HT-PEMFCs). – Design an optimal model for the PEMFCs – Minimize the total Squared Error between the empirical and the estimated output voltage. – Design an optimal model for the PEMFCs – Minimize the total Squared Error between the empirical and the estimated output voltage. – A new balanced Water Strider Algorithm (bWSA) is used for minimization. – The results are validated by comparison with several latest optimizers and a practical test case
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