Non-linear optimization of passive direct methanol fuel cell (DMFC)

The cost associated with a direct methanol fuel cell (DMFC) is the main drawback of its commercialization. To address this issue, the main objective of this study is to minimize the cost of micro DMFCs for portable applications. The model was coupled with a non-linear constrained optimization to determine an optimum design of the DMFC with respect to the design and geometrical parameters of the anode and cathode, including methanol concentration, power density, catalyst loading, etc. Optimization was performed using Matlab to minimize the difference between the power input required and the power optimum via Non-Linear Programming (NLP). The optimum characteristics of DMFC were solved by using an NLP simulation. The outputs were verified by both experimental and modeling results. These dynamic optimization results provided an optimum design parameters for the physical properties of DMFC required to generate the portable application. Lastly, a cost analysis was also considered in this study.