Computational fluid dynamics (CFD) have become a valuable tool for the development and analysis of fuel cells. The most commonly used CFD methods are finite volume (FV) or finite element (FE) methods. In the framework of my PhD I develop a subroutine for the commercial finite volume solver fluent which allows simulating fuel cells. The purpose of this work is to investigate fuel cell designs on a macroscopic level as well as stack designs. The subroutine is capable of handling arbitrary geometries, the only requirement is that for each fuel cell there is one anodic fluid domain and one cathodic fluid domain which are separated by a solid electrolyte domain. The polarisations can be computed in different ways, depending on the user input.
In fuel cells the anode and cathode layers adjacent to the electrolyte are made of a porous material. The pore size can be as small as a couple of nanometres. When using a macroscopic model to simulate a fuel cell the heat and mass transfer processes as well as the reactions have to be approximated. For this reason a lot of input data is needed before a macroscopic fuel cell model can yield reliable results. Usually this data is provided by measurements and is often hard to obtain. To increase the predictive capabilities of fuel cell models it is desirable to be able to replace the measure d data with results of other simulations. In the case of the porous electrodes one possibility is to discretise the porous geometry and determine the macroscopic properties such as permeability or effective heat transfer coefficient. Traditional CFD methods like FV or FE are currently not suitable for the simulation of porous media since the complex geometry and the associated boundary conditions are hard to discretise. A promising method seems to be the Lattice Boltzmann Method (LBM) which allows a very simple implementation of boundary conditions. Until now a very basic LBM code has been written which is capable to simulate incompressible isothermal Newtonian fluids at very low Reynolds numbers. The aim is to be able to simulate multi-species, non isothermal environments.