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Abstract
For proton exchange membrane fuel cells (PEMFCs), the parameter extraction issue is among the most widely studied problems in the field of energy storage systems, since the precise identification of such parameters plays an important role in increasing the PEMFC performance and life span. The optimization process is intended to adjust the performance of PEMFCs by appraising the optimal parameters that produce a good estimation of the current–voltage (I–V) curve. In order to build an accurate equivalent circuit model for PEMFCs, a reliable and effective parameter extraction algorithm, termed a supply–demand-based optimization (SDO) algorithm, is proposed in this paper. Nine parameters (ξ1, ξ2, ξ3, ξ4, Rc, β, λ, l, and Jmax) are evaluated, to minimize the sum squared deviation (SSE) between the experimental and simulated I–V curves. To validate the feasibility and effectiveness of the SDO algorithm, four sets of experimental data with diverse characteristics and two well-known PEMFC stacks (BSC500W and 500W Horizon) are employed. Comparison of the simulated and experimental results clearly demonstrates the superiority/competitiveness of the SDO algorithm over five well-established parameter extraction algorithms, i.e., the whale optimization algorithm (WOA), grey wolf optimization (GWO), Harris hawks optimization (HHO), and genetic algorithm (GA). Several evaluation criteria, including best SSE, worst SSE, mean SSE, and standard deviation, show that the SDO algorithm has merits in terms of PEMFC modeling.
Highlights
The exponential demand for electricity and the impact of fossil fuel use, e.g., global warming, have led to an increase in the utilization of renewable energy resources (RERs).Appropriate techniques for energy storage help to deal with the lower availability of RERs, such as wind and solar energy, and contribute to the de-carbonization of multiple applications, e.g., automotive, grid-connection, maritime, and residential applications [1].Among the storage system techniques, fuel cell (FC) devices have received much attention as energy storage media [2,3]
Mathematical modeling is important to simulate the performance of a Proton exchange membrane fuel cells (PEMFCs) at different operating conditions in real work
Economic principles dictate that the quantity and cost of a commodity are determined by its current cost and quantity in the market, respectively
Summary
The exponential demand for electricity and the impact of fossil fuel use, e.g., global warming, have led to an increase in the utilization of renewable energy resources (RERs). Among the storage system techniques, fuel cell (FC) devices have received much attention as energy storage media [2,3]. PEMFCs have several outstanding characteristics, such as high energy efficiency; high energy density; low overall cost; low working noise; low operating temperature; zero emissions of nitrogen oxides, sulfur oxides, and CO2 ; short startup time; use of solid electrolytes; zero corrosion; and long life [4]. Mathematical modeling is important to simulate the performance of a PEMFC at different operating conditions in real work
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