Nitrogen, oxygen and water crossover and their accumulation in the anode channels of low temperature Proton Exchange Membrane Fuel Cells present system level challenges for the design and operation of devices with high hydrogen utilization. The low flow rates enable operation under self-humidified anode conditions further reducing the system weight, cost, and complexity which is especially important for small portable applications. However, accumulated inert gasses and liquid water need to be purged before severe starvation conditions lead to carbon corrosion, inevitably wasting some Hydrogen. Frequent purging wastes fuel and dries the membrane leading to physical degradation and membrane delamination observed in post mortem Scanning Electron Microscopy images. Model based control methods provide an automated way to schedule the anode purges and study the tradeoff between degradation and fuel efficiency over the life of a fuel cell stack [1]. In addition the models can be used for design purposes such as optimizing the anode channel dimensions to balance the tradeoff between power density and interval between purges.

The transport of gas species in the anode and cathode channels can be predicted by partial differential equations, specifically the 1-D the multi-component Stefan-Maxwell equation along the length of the channel. The distribution of membrane hydration level and temperature must also be considered as they impact the crossover rate. The model accurately predict the nitrogen accumulation and resulting recoverable drop in terminal voltage over time between purges when operating with a Dead Ended Anode (DEA). The model has been validated by simultaneous Neutron Imaging (NI) and Gas Chromatography (GC) sampling from within the anode channel [4]. Neutron imaging provides a unique measurement of the liquid water distribution within the cell and can be performed on relevant materials and channel designs without the need for modified hardware with different thermal properties such as transparent plates for optical imaging. The two dimensional images provide information about both the membrane electrode assembly water content, and channel liquid water [5]. This allows us to validate model predictions of the two phase (liquid water) transition point along the length of the channels. Dead Ended Anode (DEA) operation represents the extreme case of operation with high hydrogen utilization. There are several practical advantages to studying this limiting behavior of the system. Foremost is the direct measurement of membrane permeation rates since the only sources of nitrogen and oxygen in the anode channel is crossover.

The introduction of oxygen into the anode gas stream from membrane crossover is the primary mechanism for cathode carbon corrosion. The oxygen present in a hydrogen depleted region creates a voltage reversal and hence large cathode potential in the adjacent region of the cell similar to the one observed during startup conditions when the air is pushed out of the channels by hydrogen.  A quaternary system for the anode channels using the Stefan-Maxwell framework was augmented with a model of carbon corrosion [3]. The resulting model of cathode active site loss predicts the slow non-recoverable voltage drop over 1000 hours of operation.  The modeled corrosion rate matched the decrease in cathode catalyst layer thickness observed in post mortem SEM images [2].

Finally the augmented model has been used to study the optimum purge scheduling considering both corrosion and fuel efficiency [1].  The physical channel dimensions provide a rough estimate of feasible target purge duration (volume) and interval between purges. The minimum purge duration pushes the nitrogen blanketed region to the end of the channel, fully recovering the terminal voltage, whereas the maximum duration completely clears the channel (anything beyond this needlessly wastes fuel). The analysis and methodologies presented herein can be used for the design and control of fuel cell systems operating with high hydrogen utilization to prolong stack life and achieve high efficiency.

[1]    J. Chen, J. Siegel, A. Stefanopoulou, and J. Waldecker, IJHE, 38, (2013).

[2]    T. Matsuura, J. Chen, J. Siegel, and A. Stefanopoulou, IJHE, 38 (2013).

[3]    J. Chen, J. B. Siegel, T. Matsuura, and A. G. Stefanopoulou, J. Electrochem. Soc., 158, 9, (2011).

[4]    J. B. Siegel, S. V. Bohac, A. G. Stefanopoulou, and S. Yesilyurt, J. Electrochem. Soc., 157, 7 (2010).

[5]    J. B. Siegel, D. A. McKay, A. G. Stefanopoulou, D. S. Hussey, and D. L. Jacobson, J. Electrochem. Soc. 155, 11 (2008).