Intelligent Modeling Method of Proton Exchange Membrane Fuel Cell Based on Grey Theory

Abstract

Numerical modeling is an important supplementary means for the study on fuel cell power system. Therefore, the research on modeling method has been a hot topic in academia from Lumped parameter modeling to three-dimensional modeling. But above modeling approaches share the common feature that the accuracy of the model is highly dependent on the key parameters' data veracity in the cell (e.g., conductivity, exchange current density, electrode area, etc.). However, these parameters are often difficult to determine for research work on commercial fuel cell applications and require extensive experimentation or even disassembly of the fuel cell for internal measurements. This paper proposes an intelligent modeling method for proton exchange membrane fuel cell (PEMFC) based on Grey Theory, and filter the optimal model by analyzing and comparing the simulation accuracy of several sub-models. The results show that the proposed intelligent modeling method can build a fuel cell model using limited experimental data and ensure the simulation accuracy, which can simplify the modeling of proton exchange membrane fuel cell work.