COUPLED 2023

Continuous Galerkin Formulation For The Simulation Of Multiphysics Processes In Planar Solid-oxide Fuel Cells (SOFC)

  • Costa-Solé, Albert (Barcelona Supercomputing Center (BSC))
  • Gargallo-Peiró, Abel (Barcelona Supercomputing Center (BSC))
  • Mira, Daniel (Barcelona Supercomputing Center (BSC))
  • Torrell, Marc (Institut de Recerca en Energia de Catalunya)
  • Tarancón, Albert (Institut de Recerca en Energia de Catalunya)

Please login to view abstract download link

Solid oxide cell (SOC) technology is a promising alternative to fossil fuels, providing sustainable energy and mitigating global warming. Specifically, solid-oxide fuel cells (SOFC) are electrochemical devices that convert chemical energy into electrical energy without producing pollutants under high-temperature conditions ranging from 700-900 ºC (Kakac et al., 2007, Chroneos et al. 2011). Although SOFC technology has matured in the last few years, there are still some issues with its commercial deployment. Specifically, cell degradation changes the microstructural parameters during the operation regimes affecting cell efficiency. Numerical simulations can provide insights into these microstructure's effects, the geometrical design, and the operation parameters on SOFC efficiency. At the same time, these simulations can optimize the geometries and operation regimes (Kakac et al., 2007). Moreover, the obtained numerical data can later be used for reduced-order modeling. This work presents a Continuous Galerkin (CG) formulation to simulate the multiphysics processes in SOFC during steady operation. We use Ohm's law to define the electric and ionic potentials and the Dusty Gas Model (DGM) to determine the species diffusion, assuming that the temperature and the total pressure are uniform and constants (Brus et al., 2020). Moreover, we use the Bulter-Volmer equations to describe the charge-transfer rates. Finally, we will show several examples to assess the capabilities of the proposed methodology and validate the obtained results with experimental data.