Evaluation Criterion of Proton Exchange Membrane (ECPEM) fuel cells considering inserted porous media inside the gas flow channel. (25th February 2022)

• Record Type: Journal Article
• Authors: Pourrahmani, Hossein; Van herle, Jan
• Is Part Of: Applied thermal engineering. Volume 203(2022)
• Publication Date: 2022-02-25
• Subjects: Proton Exchange Membrane Fuel Cells (PEMFC) -- Evaluation Criterion of Proton Exchange Membrane (ECPEM) -- Artificial Neural Networks (ANN) -- Porous media -- Electrochemical performance -- Thermal management; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2021.117952
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: Electrochemical and heat transfer analyses of proton exchange membrane fuel cell. Introducing a new design using porous media inside the gas flow channel. Evaluating the power density, voltage, pressure drop and Nu as the outputs. Define a new parameter "Evaluation Criterion of Proton Exchange Membrane (ECPEM)". Training an ANN model to calculate the optimum value of ECPEM to be 78.88. Abstract: The focus of this study is to evaluate the effects of porous media inside the gas flow channel of Proton Exchange Membrane Fuel Cells (PEMFC) on four different output parameters of voltage, power density, pressure drop, and Nusselt number (Nu) considering the impacts of its thickness, viscous resistance, and current density. Although it is proved that the new design will improve the convective heat transfer, there have not been studies to evaluate the effects of this porous layer on the electrochemical performance and heat transfer simultaneously. The results showed that viscous resistance has by far the highest impact on the power densities in high current densities while thicker inserted porous layer improves the performance. Results also demonstrate that a parameter is needed to consider all these output parameters at the same time, hence the Evaluation Criterion of Proton Exchange Membrane (ECPEM) is defined using artificial neural network (ANN) modeling. Single-objective optimization of the ECPEM is developed using the ANN models to produce 250, 000 data. The optimum value of ECPEM was obtained 78.88 in the thickness of 500 μ m and the viscous resistance of 2, 111, 000 ( 1 m 2 ) while the current density is equal to 0.65 ( A / c m 2 ).