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In order to determine the working conditions for direct methanol fuel cell and to gain higher performances, two one-dimensional, steady-state numerical models have been presented to evaluate the performance of direct methanol fuel cells (DMFCs) using Matlab. Genetic algorithm and direct Monte Carlo algorithm have been employed to determine the optimization operation conditions of the DMFC. The cell maximal power density has been predicted via the genetic algo- rithm. ComparinG with the direct Monte Carlo algorithm, the genetic algorithm has been found to be more efficient and useful.

One Dimensional Simulation of DMFC Performance Using Direct Monte Carlo Algorithm and Genetic Algorithm