Application based multi-objective performance optimization of a proton exchange membrane fuel cell

An application-based multi-objective optimization approach is presented to acquire the best operation condition for a proton-exchange membrane fuel cell. The optimization is done for propulsion, power station, and portable applications, in which the recommended range for decision variables and importance level of the objective functions are taken into consideration for optimization to obtain more accurate and practical results. In the multi-objective optimization, from each important aspect of the performance, i.e., technical, economic, dimensional, and environmental aspects, one objective is selected. The effect of the maximum allowable (threshold) current density on both optimum decision variables and objective functions are also investigated to find the best value for that. The results reveal that increasing the maximum allowable current density leads to improvements in optimized values of all the objective functions. Moreover, the conducted sensitivity analyses determine that the best value for threshold current density for the propulsion and power station applications is 1.3 A cm−2 and for the portable application is 1.5 A cm−2. Furthermore, comparison of the results to the base case condition shows that values of the temperature, pressure, and voltage in power station are not affected by optimization, whereas substantial decrease in both propulsion and portable applications brings more level of safety. Similarly, objective functions, i.e., efficiency, levelized cost, size, and greenhouse emission are averagely improved by 9.93, 16.95, 37.13, and 7.77%, respectively. The proposed procedure helps to design and manufacture the high-performance proton-exchange membrane fuel cells based on the employed application and users’ preference. [Display omitted] •The best allowable current density for portable application is 1.5 A cm−2.•Allowable current density of 1.3 A cm−2 is the best for other applications.•Employing the approach leads to a higher level of safety.•On average, efficiency and levelized cost are enhanced 9.93 and 16.95%.•Size and greenhouse emissions are averagely improved 37.13 and 7.77%.