Performance analysis and multi-optimization of direct methanol fuel cell based on a novel numerical model considering mass transfer

In this paper, a novel numerical model of direct methanol fuel cells (DMFC) is proposed aiming to quantitatively analyze the effect of methanol, water, and oxygen mass transfer on the performance and to further improve power and reduce energy losses. The model was validated against experimental data. The model predicts the values of variation of reactant concentrations in each layer and the effect of parameters is analyzed. The results show that overall performance is better at low methanol concentration (1 - 2 mol/dm 3 ). A rise in a certain temperature (65 K) increases maximum power density by 13.6%, ECOP by 43.9%, voltage efficiency by 13.6%, thermal efficiency by 14.2% and real efficiency by 19.1%, while reducing entropy yield by 19.3%. Moreover, the average of optimization results based on multi-objective particle swarm algorithm (MOPSO) indicated that maximum power density and its corresponding ECOP , and thermal efficiency were increased by 13.47%, 0.03%, and 6.21%, respectively.