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Effect of Current Density and Operating Parameters on the Dynamical Evolution of Liquid Water Distribution within the Gas Diffusion Layers of PEMFC Using a Multiscale Kinetic Monte Carlo Method

Sunday, 30 September 2018: 16:20
Star 1 (Sunrise Center)
A. Pournemat, F. Wilhelm, and J. Scholta (Zentrum für Sonnenenergie- und Wasserstoff-Forschung)
In this study, a kinetic Monte Carlo (KMC) model is employed to observe the variation of the liquid water distribution within the gas diffusion layers (GDL) of polymer electrolyte membrane fuel cells (PEMFCs) with time and current density. The application of the model yields deeper understanding on the dependence of the liquid water agglomerations quantity and dispersal on the surface characteristics, the thermodynamic boundary conditions and the current density. This work, which focuses on the evolution of the system with time, represents a mayor enhancement to the previous works on the Grand Canonical Monte Carlo (GCMC) model 1–3, in which the behavior of the system was investigated after a steady-state had been reached. Particularly, by direct integration of the current density into the simulations, in addition to the local temperature and relative humidity, another step forward towards a complete representation of the real operating conditions of a running fuel cell is reached.

In the simulations, the real GDL structure is mapped onto a 3D grid featuring an appropriate voxel size, which is chosen to adequately represent the structural details of the respective material. As an initial state at the time zero, either a certain amount of liquid water can be randomly distributed within the open pores, or the steady-state water distribution obtained from a previous simulation with the standard GCMC model in the same GDL structure can be used. In the KMC model, the dynamic of the system is characterized by subsequent transitions from one state to another. Escaping from a certain state can occur along a number of pathways. Each of these pathways has its own rate constant, which corresponds to the Metropolis rate. All the states which preceded the actual state of the system are not important. This is the defining property of Markov chains. After each movement, a time increment is computed, which is a statistical estimation of the time needed for this event to take place in reality. Having obtained the time step, the amount of water produced as the result of the current density can be calculated. The water is added from the CL side and is removed from the opposite side, when it reaches the boundary region of the simulation box.

The KMC simulation results show how different current densities and boundary conditions effect the amount of liquid water in the structure, and how water distributes and moves in the GDL depending on the structural and wetting properties. Figure 1 shows an example of the simulation results at four different times after starting from a random water distribution: t = 4.6×10-8 s, t = 0.29 s, t = 0.75 s and t = 1.26 s, respectively. The initial water content corresponds to 20% occupation of the available pore space. In this simulation the current density was set to a constant value of 0.9 A cm-2 and the voxel size had a value of 4.348 μm. The local temperature and relative humidity within the structure were obtained from a previous CFD study. The surface contact angle of the GDL to water is considered to have a value of 94°. The results show the change in size, amount and distribution of water agglomerations with time. As expected for a hydrophobic surface, the water tends to fill the bigger pores within the structure.

References

1. K. Seidenberger, F. Wilhelm, T. Schmitt, W. Lehnert, and J. Scholta, J. Power Sources, 196, 5317–5324 (2011).

2. K. Seidenberger et al., J. Power Sources, 239, 628–641 (2013).

3. A. Pournemat et al., in ECS Transactions,, vol. 75 (2016).

Figures

Figure 1. Water distribution in the PEMFC GDL as the result of a Kinetic Monte Carlo simulation with a voxel size of 4.348 µm and current density of 0.9 A cm-2, water enters the GDL from z = 0.