(496b) Combined Modeling and Experimental Analysis of Microscale Fuel Cells
AIChE Annual Meeting
2015
2015 AIChE Annual Meeting Proceedings
Transport and Energy Processes
Recent Advances in Fuel Cell and Battery Technologies
Wednesday, November 11, 2015 - 8:45am to 9:00am
Combined Modeling and Experimental Analysis of Microscale Fuel Cells
Adam S. Hollinger, Daniel G. Doleiden
Department of Mechanical Engineering
Penn State Erie, The Behrend College, 5101 Jordan Road, Erie, PA 16563, USA
Section: Transport and Energy Processes (07)
Session: 07000 Recent Advances in Fuel Cell and Battery Technologies
With the rapid advancement of consumer mobile technology, an accompanying demand for energy-dense portable power sources has given rise to increased development of alternatives to traditional rechargeable battery technologies (i.e., lithium-ion) [1]. Microscale direct methanol fuel cells (DMFCs) demonstrate potential as such an alternative, enabling instantaneous recharging via fuel solution cartridges and higher energy density than lithium-ion rechargeable batteries [1].
When optimizing the design of DMFCs for portable power applications, laboratory testing involving the production of fuel solutions and iterative fabrication of various components is typically required [2]. Here, we present a UNIX-based mathematical model of flow and diffusion through the flow chamber of a DMFC as a means of predicting the effects of various parameters on cell performance. This model will aid design optimization by reducing the amount of time and materials required for experimental benchmarking.
After input parameters are defined, the model provides expeditious 2D and 3D graphical simulation of current density, fuel molarity, and hydrodynamic flow as functions of position in the flow chamber. In addition, polarization curves can be generated from model output for comparison to experimental data. Such comparisons enable internal modifications of the model for increased accuracy.
A positive correlation between model predictions and experimental data for catalyst deposition width studies at low to medium power density has already been observed; evaluation of the model’s ability to predict the effects of varying fuel molarity, electrolyte molarity, flow chamber geometry, and fuel flow rate are ongoing.
[1] E. Kjeang, N. Djilali, D. Sinton, Journal of Power Sources, 186 (2009) 353-369.
[2] A.S. Hollinger, P.J.A. Kenis, Journal of Power Sources, 240 (2013) 486-493.