A solid oxide fuel cell (SOFC) is a clean and high-efficiency energy conversion device, which undergoes improvement of performance continuously. The transport of gas species and charges proceed in the porous electrodes. The porous electrodes are also responsible for the removal of exhaust gases. In this paper, a fully coupled 3D single-channel multiphysics computational fluid dynamics (CFD) model was developed based on the finite element method (FEM). The governing equations for momentum, species, charges, and heat transport were solved by a segregated solver. The impact of decreased ionic, electronic, and pore phase tortuosity on the SOFC performance such as fuel utilization, current density, activation overpotential and temperature distribution are analyzed and compared with the base case. In addition to the tortuosity investigation, the volume fraction of the electronic phase in the active layer and the support layer is also investigated using a parametric sweep study. Of all the decreased tortuosity cases, there is an increase in ionic current density and temperature compared with the base case. Except for a decreased pore tortuosity, all other cases led to an increase of electronic current density compared with the base case. The consumption of hydrogen increased for all cases compared with the base case. The activation overpotential increased with decreased electronic phase and pore phase tortuosity, while a decrease of ionic phase tortuosity caused a decrease. Finally, when decreasing all phase tortuosity, both current density, temperature, activation overpotential, and hydrogen consumption increased. For the parametric sweep, there is an optimum electronic phase volume fraction value. This work allows for a better understanding of the relationship between the microstructure and performance of SOFCs. Meanwhile, it provides theoretical guidance for a better porous electrode design.
Bibliografisk informationFunding Information:
Great appreciation to the Chinese Scholarship Council (grant number: 201906070189) and ?Forsk Foundation (grant number: 17-331) for fully support this work.
Great appreciation to the Chinese Scholarship Council (grant number: 201906070189 ) and ÅForsk Foundation (grant number: 17-331 ) for fully support this work.
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