Abstract
The present study introduces an economical–functional design for a polymer electrolyte membrane fuel cell system. To do so, after introducing the optimization problem and solving the problem based on the presented equations in the fuel cell, a cost model is presented. The final design is employed for minimizing the construction cost of a 50 kW fuel cell stack, along with the costs of accessories regarding the current density, stoichiometric coefficient of the hydrogen and air, and pressure of the system as well as the temperature of the system as optimization parameters. The functional–economic model is developed for the studied system in which all components of the system are modeled economically as well as electrochemically–mechanically. The objective function is solved by a newly improved metaheuristic technique, called converged collective animal behavior (CCAB) optimizer. The final results of the method are compared with the standard CAB optimizer and genetic algorithm as a popular technique. The results show that the best optimal cost with 0.1061 $/kWh is achieved by the CCAB. Finally, a sensitivity analysis is provided for analyzing the consistency of the method.
Highlights
Duan et al [13] proposed an optimal design for the PEM fuel cell stack by the satin bowerbird optimization algorithm (SBOA)
The achievements of applying the suggested collective animal behavior (CCAB) optimizer were put in comparison with several various meta-heuristic optimizers, the World Cup optimizer (WCO) [25], emperor penguin optimization (EPO) [47], gravitational search algorithm (GSA) [48], and typical collective animal behavior optimizer (CAB) algorithm [44], to declare its high efficiency
The model is developed with the objective function for minimizing the cost of fuel cell fabrication based on the proposed converged collective animal behavior (CCAB) algorithm and solving the optimal values for each of the main parameters
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The modeling of the fuel cell stacks is performed to obtain two significant purposes. The comparison of the proposed model with the empirical data confirmed the method efficiency for the analysis of the fuel cell. Duan et al [13] proposed an optimal design for the PEM fuel cell stack by the satin bowerbird optimization algorithm (SBOA). The achievements showed better accuracy of the proposed model than the PEM fuel cell design parameters. Optimizers have proper results for the PEM fuel cell model, which is thanks to the proper capability of them to avoid the local minima, compared to the classic approaches [25,26,27]. A new optimal design for a PEM fuel cell-based system is presented in this paper. The results are validated by empirical data to show the method’s precision
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