Roman Baena, V. J., Asouti V., Valtiner, M., & Vernes, A. (2024, July 28). Numerical Modelling and Optimisation of the Pressure-Dependent Electrical Contact Resistance (ECR) in Proton Exchange Membrane Fuel Cells (PEMFC) [Poster Presentation]. GRC Fuel Cells 2024, Rhode Island, United States of America (the).
Proton exchange membrane fuel cells (PEMFC) are one of the most promising alternatives in order to reduce CO 2 emissions in the transportation sector and this reason is why nowadays there is a considerable ongoing effort to enhance the efficiency of PEMFCs. It is well known that the contact resistance within fuel cells accounts for most of the electrical resistance leading to voltage loss. Specifically, the contact resistance between the Gas Diffusion Layer (GDL) and Bipolar Plate (BPP) is amongst all the biggest one. Towards reducing the Electrical Contact Resistance (ECR) at the GDL-BPP interface, the aim of this work is to develop a numerical scheme capable of realizing various configurations of GDL and BPP, and simulate the flow of electrons while maintaining optimum working conditions for the PEMFC. In order to achieve this, firstly a 3D stochastic reconstruction of the GDL will be realized and its properties studied through statistical analysis. Currently, modeling efforts regarding GDL have focused on either ordered systems such as carbon cloth or disordered carbon paper systems, characterizing the GDL mainly with its porosity. Once these GDL configurations are realized, they will be assembled with currently in-use BPPs and then the ECR will be estimated for all these interfaces by varying parameters such as porosity, degree of compression and anisotropy, while keeping unchanged the distribution density of fibers' direction. The findings will provide valuable guidance for optimizing GDL design and manufacturing processes to enhance fuel cell efficiency. This work is part of the BLESSED project funded by the European Union under Marie Sklodowska-Curie Actions and GA No. 101072578.
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Research Areas:
Surfaces and Interfaces: 25% Modeling and Simulation: 50% Computational Materials Science: 25%