Fuzzy-based multi-objective optimization of DMFC system efficiencies

To improve the fuel efficiency and total exergetic efficiency of a non-isothermal direct methanol fuel cell (DMFC) system, the multi-objective optimization problem is addressed in this article. Under incommensurable multiple goals, the fuzzy inference with two-phase procedures is applied for finding the locally Pareto-optimal solution. Through an iterative optimization programming, a piecewise optimal control action is effectively generated at each time period. Finally, the optimal operating manner by manipulating anode inlet temperature is successfully demonstrated by the dynamic simulation.