Mads Bang

Modeling of CO Influence in PBI Electrolyte PEM Fuel Cells

In most PEM fuel cell MEA’s Nafion is used as electrolyte material due to its excellent proton conductivity at low temperatures. However, Nafion needs to be fully hydrated in order to conduct protons. This means that the cell temperature cannot surpass the boiling temperature of water and further this poses great challenges regarding water management in the cells. When operating fuel cell stacks on reformate gas, carbon monoxide (CO) content in the gas is unavoidable. The highest tolerable amount of CO is between 50–100 ppm with CO-tolerant catalysts. To achieve such low CO-concentration, extensive gas purification is necessary; typically shift reactors and preferential oxidation. The surface adsorption and desorption is strongly dependent upon the cell temperature. Higher temperature operation favors the CO-desorption and increases cell performance due to faster kinetics. High temperature polymer electrolyte fuel cells with PBI polymer electrolytes rather than Nafion can be operated at temperatures between 120–200°C. At such conditions, several percent CO in the gas is tolerable depending on the cell temperature. System complexity in the case of reformate operation is greatly reduced increasing the overall system performance since shift reactors and preferential oxidation can be left out. PBI-based MEA’s have proven long durability. The manufacturer PEMEAS have verified lifetimes above 25,000 hours. They are thus serious contenders to Nafion based fuel cell MEA’s. This paper provides a novel experimentally verified model of the CO sorption processes in PEM fuel cells with PBI membranes. The model uses a mechanistic approach to characterize the CO adsorption and desorption kinetics. A simplified model, describing cathode overpotential, was included to model the overall cell potential. Experimental tests were performed with CO-levels ranging from 0.1% to 10% and temperatures from 160–200°C. Both pure hydrogen as well as a reformate gas models were derived and the modeling results are in excellent agreement with the experiments.© 2006 ASME

Flow and Pressure Distribution in Fuel Cell Manifolds

The manifold is an essential part of the fuel cell stack. Evidently evenly distributed reactants are a prerequisite for an efficient fuel cell stack In this study, the cathode manifold ability to distribute air to the cells of a 70 cell stack is investigated experimentally. By means of 20 differential pressure gauges, the flow distribution is mapped for several geometrical and operating conditions. Special attention is given to the inlet conditions of the manifold. Here, a diffuser design was constructed in order to replace the conventional circular inlet design. The diffuser design showed significant improvements to the flow distribution in comparison to the circular design. Moreover, the best flow distribution was found using a U-shaped configuration.

Particle Image Velocimetry and Computational Fluid Dynamics Analysis of Fuel Cell Manifold

The inlet effect on the manifold flow in a fuel cell stack was investigated by means ofnumerical methods (computational fluid dynamics) and experimental methods (particleimage velocimetry). At a simulated high current density situation the flow field wasmapped on a 70 cell simulated cathode manifold. Three different inlet configurationswere tested: plug flow, circular inlet, and a diffuser inlet. A very distinct jet was formedin the manifold, when using the circular inlet configuration, which was confirmed bothexperimentally and numerically. This jet was found to be an asymmetric confined jet,known as the symmetry-breaking bifurcation phenomenon, and it is believed to cause asignificant maldistribution of the stack flow distribution. The investigated diffuser designproved to generate a much smoother transition from the pipe flow to the manifold flowwith a subsequent better flow distribution. A method was found in the literature to probeif there is a risk of jet asymmetry; it is however recommended by the author to implementa diffuser design, as this will generate better stack flow distribution and less head loss.Generally, the numerical and experimental results were found in to be good agreement,however, a detailed investigation revealed some difference in the results.

Fitting a Three Dimensional PEM Fuel Cell Model to Measurements by Tuning the Porosity and Conductivity of the Catalyst Layer

A three-dimensional, computational fluid dynamics (CFD) model of a PEM fuel cell is presented. The model consists of straight channels, porous gas diffusion layers, porous catalyst layers and a membrane. In this computational domain, most of the transport phenomena which govern the performance of the PEM fuel cell are dealt with in detail. The model solves the convective and diffusive transport of the gaseous phase in the fuel cell and allows prediction of the concentration of the species present. A special feature of the model is a method that allows detailed modelling and prediction of electrode kinetics. The transport of electrons in the gas diffusion layer and catalyst layer is accounted for, as well as the transport of protons in the membrane and catalyst layer. This provides the possibility of predicting the three-dimensional distribution of the activation overpotential in the catalyst layer. The current density dependency on the gas concentration and activation overpotential can thereby be addressed. The proposed model makes it possible to predict the effect of geometrical and material properties on the fuel cell’s performance. It is shown how the ionic conductivity and porosity of the catalyst layer affects the distribution of current density and further how this affects the polarization curve. The porosity and conductivity of the catalyst layer are some of the most difficult parameters to measure, estimate and especially control. Yet the proposed model shows how these two parameters can have significant influence on the performance of the fuel cell. The two parameters are shown to be key elements in adjusting the three-dimensional model to fit measured polarization curves. Results from the proposed model are compared to single cell measurements on a test MEA from IRD Fuel Cells.© 2004 ASME