Parameter analysis from the modeling of high temperature proton exchange membrane fuel cells

[Display omitted] •High temperature proton exchange membrane fuel cells (PEMFCs) are modeled.•4 critical membrane-electrode assembly (MEA) parameters are extracted.•Model validation is conducted with data from 22 polarization curves from 19 MEAs.•MEAs adopting other polymer membranes than polybenzimidazole are first modeled.•Optimum MEA performance is deduced using a combination of MEA parameters. High temperature proton exchange membrane fuel cells (PEMFCs) employing phosphoric acid (PA)-doped polymer membranes could be an alternative capable of overcoming the disadvantages of low temperature PEMFCs. Four critical membrane-electrode assembly (MEA) parameters (cathode exchange current density, cathode utilization, ohmic resistance, and cathode limiting current density) are selected and extracted from the modeling of twenty-two polarization curves measured from nineteen MEAs, which are fabricated and operated according to an experimental protocol that Samsung developed in the mid 2000s. MEA systems adopting three representative membranes (polybenzimidazole (PBI), poly(2,5-benzimidazole) (ABPBI), polybenzoxazine (PBOA)) are compared, and the effect of monomer ratio in two representative benzoxazine-benzimidazole copolymer membranes is analyzed. The evolution of the parameters during the break-in period of MEAs and the period of 2008 to 2018, when MEA performance was improved with the same specification of catalysts and membrane, is examined. Also, the impact of PA impregnation in the cathode is investigated when PA is additionally impregnated in the cathode in addition to a PA-doped membrane. Optimum values of the four parameters are combined to simulate the highest MEA performance, and the MEA performance is predicted in some cases where the parameters are varied. Overall, this approach expands the scope of previous literature on the modeling of high temperature PEMFCs, which have been mostly based on PBI membrane systems, by introducing new parameters such as the catalyst utilization and by applying the model to various membrane systems and phenomena.