NSF Award
0232266
This Small Business Innovation Research (SBIR) Phase I project focuses on the development of commercial software, based on computational fluid dynamic (CFD) techniques, to predict performance of liquid-feed direct methanol fuel cells (DMFC). While computational modeling of fuel cells has been widespread in the solid oxide fuel cell (SOFC) and hydrogen-air proton exchange membrane fuel cell (PEMFC) areas, it has been limited in the area of direct methanol fuel cell. This can be attributed, in part, to the fact that in DMFC, since the liquid fuel produces gaseous products, the modeling necessitates careful consideration of two-phase phenomena, which is numerically challenging. A comprehensive simulation tool for the prediction of performance of gas-feed PEMFC and SOFC have been developed and marketed. In order to capture the rapidly growing DMFC market, this project proposes to extend the simulation tool to address issues specific to liquid-feed DMFC modeling. The model will be validated against experimental data available from the literature. <br/><br/>Liquid-feed Direct Methanol Fuel Cells have become the center of attention, especially for portable power applications where optimal space utilization is critical. The proposed research will produce a commercial-quality predictive tool, which could be utilized extensively for design and optimization of DMFCs, in addition to providing better understanding of the transport and electrochemistry that occur in such systems.
