Critical Parameter Identification of Fuel-Cell Models Using Sensitivity Analysis

被引:7
作者
Pant, Lalit M. [1 ]
Stewart, Sarah [2 ]
Craig, Nathan [2 ]
Weber, Adam Z. [1 ]
机构
[1] Lawrence Berkeley Natl Lab, Energy Technol Area, Energy Convers Grp, Berkeley, CA 94720 USA
[2] Robert Bosch LLC, Sunnyvale, CA 94085 USA
关键词
Fuel Cells; PEM; parameter sensitivity; numerical modeling; CATALYST-LAYER; TRANSPORT; PERFORMANCE; UNCERTAINTY; CATHODE; SIMULATION; 2-PHASE; VALIDATION;
D O I
10.1149/1945-7111/ac0d68
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
Numerical modeling has been a vital tool in proton-exchange-membrane fuel-cell (PEMFC) analysis; however, the predictive capabilities of these models depend on the input physical parameters, several of which are either not experimentally measured or have large scatter in measured values. This article presents an uncertainty propagation-based sensitivity analysis to identify the model parameters that impact the model predictions most. A comprehensive 2-D membrane electrode assembly (MEA) model is used to perform local sensitivity analysis at multiple operating conditions, which encompass the range of environments and operating conditions a cell can encounter. While at lower humidities, cathode kinetics and membrane-ohmic-loss related parameters are crucial, gas transport and porous-media saturation behavior are more important at humidified conditions. Several of these findings are different from previous studies presented in literature. Identifying the crucial parameters helps focus future material and cell optimization studies as well as experimental studies to quantify these parameters with higher accuracy.
引用
收藏
页数:11
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