Development of a Typical Distribution Function of Relaxation Times Model for Polymer Electrolyte Membrane Fuel Cells and Quantifying the Resistance to Proton Conduction within the Catalyst Layer

In recent decades, polymer electrolyte membrane fuel cell (PEMFC) technologies have attracted research attention as promising candidates for next-generation energy conversion systems. This work deals with the effect of operating conditions and the construction of a typical model for PEMFCs, using electrochemical impedance spectroscopy (EIS) and distribution of relaxation times analysis. In operando EIS measurements were carried out on PEMFCs under different operating conditions. The measurements were analyzed using a genetic algorithm to obtain the distribution function of relaxation times (DFRT) models as analytical functions. The obtained model consists of four peak functions that fit the four main physical processes known to occur within the fuel cell during operation: proton conduction within the membrane, proton conduction within the catalyst layer (CL), oxygen reduction reaction's charge transfer, and oxygen mass transfer within the CL and the gas diffusion layer. In addition, this method enabled examining each physical process's response to operating conditions (such as temperature, humidity, and output current) and quantifying each process's effective resistance. In particular, we were able to quantify the resistance to proton conduction within the CL, a process known to have a low contribution to the overall impedance, hence many times eclipsed by other processes. The resulting model can be further used in, for example, PEMFC degradation research, owing again to the fact that the model's analytical form is stable while its parameters change as the cell degrades.

Automated summary

This study utilized electrochemical impedance spectroscopy and distribution of relaxation times analysis, along with a genetic algorithm, to investigate PEMFC under different operating conditions and establish a typical model. The model consists of four peak functions representing the main physical processes in a fuel cell, and it is stable even as parameters change with cell degradation, making it suitable for further research on PEMFC degradation and performance.