Critical Parameter Identification of Fuel-Cell Models Using Sensitivity Analysis

Numerical modeling has been a vital tool in proton-exchange-membrane fuel-cell (PEMFC) analysis; however, the predictive capabilities of these models depend on input physical parameters, several which are either not experimentally measured or have large scatter values. This article presents an uncertainty propagation-based sensitivity analysis to identify model parameters that impact predictions most. A comprehensive 2-D membrane electrode assembly (MEA) is used perform local at multiple operating conditions, encompass range environments and conditions cell can encounter. While lower humidities, cathode kinetics membrane-ohmic-loss related crucial, gas transport porous-media saturation behavior more important humidified conditions. Several findings different from previous studies presented literature. Identifying crucial helps focus future material optimization as well experimental quantify with higher accuracy.