Performance Characteristics of Direct Methanol Fuel Cell with Methanol Concentration

메탄올 농도에 따른 직접 메탄올 연료전지의 성능 해석

  • Published : 2008.03.10

Abstract

DMFC(Direct Methanol Fuel Cell) is one of promising candidates for power sources of small mobile IT devices like notebook, cell phone, and so on. Efficient operation of fuel cell system is very important for long-sustained power supply because of limited fuel tank size. It is necessary to investigate operation characteristics of fuel cell stack for optimal control of DMFC system. The generated voltage was modeled according to various operating condition; methanol concentration, stack temperature, and load current. It is inevitable for methanol solution at anode to cross over to cathode through MEA(membrane electrode assembly), which reduces the system efficiency and increases fuel consumption. In this study, optimal operation conditions are proposed by analyzing stack performance model, cross-over phenomenon, and system efficiency.

Keywords

References

  1. Gurau, B. and Smotkin, E. S., 2002, Methanol crossover in direct methanol fuel cells:a link between power and energy density, Journal of Power Sources, Vol. 112, pp. 339-352 https://doi.org/10.1016/S0378-7753(02)00445-7
  2. Liu, W. and Wang, C. Y., 2006, Modeling water transport in liquid feed direct methanol fuel cells, Journal of Power Sources, Vol. 164, pp. 189-195 https://doi.org/10.1016/j.jpowsour.2006.10.047
  3. O'Hayre, R., Cha, S. W., Clella, W. and Prinz, F. B., 2006, Fuel cell fundamentals, John Willy & Sons, INC., pp. 56-173
  4. Kulikovsky, A. A., 2003, A method for analysis of DMFC performance curves, Electrochemistry Communication, Vol. 5, pp. 1030-1036 https://doi.org/10.1016/j.elecom.2003.10.002
  5. Sundmacher, K., Schultz, T., Zhou, S., Scott, K., Ginkel, M. and Gilles, E. D., 2001, Dynamics of the direct methanol fuel cell (DMFC): Experiments and model-based analysis, Chemical Engineers, Vol. 56, pp. 333-341 https://doi.org/10.1016/S0009-2509(00)00233-5
  6. VanderNoot, T. J. and Abrahams, I., 1998, The use of genetic algorithms in the nonlinear regression of immittance data, Journal of Electroanalytical Chemistry, Vol. 448, pp. 17-23 https://doi.org/10.1016/S0022-0728(97)00593-7