Numerical Simulations for in-Plane Distribution of Platinum Degradation in Dynamic Operating Conditions of Polymer Electrolyte Membrane Fuel Cells

Abstract

Predicting degradation of polymer electrolyte membrane fuel cells (PEMFCs) is an important issue from the viewpoint of durability and cost. In fact, in technical roadmaps regarding fuel cell of each country, high targets of durability and performance are set for transport applications especially for heavy duty vehicles. One of important degradation process takes place in catalyst layer. PEMFC catalysts are typically platinum or platinum alloys and consist of nanoparticles to increase the electrochemically active surface area (ECSA). However, these particles are not stable in dynamic operating conditions of the transport applications. A typical degradation mechanism of the catalyst is the electrochemical Ostwald ripening mechanism, and it is known that the platinum particle size distribution shifts to larger particle diameter, resulting in lower ECSA and lower performance. Therefore, predicting platinum catalyst degradation is important to enhance durability of the products.Various numerical models for catalyst degradation of PEMFC have been proposed and used to explore degradation mechanisms. Many of these are zero or one-dimensional models, but factors that affect catalyst degradation, such as temperature, potential, and humidity, have non-uniform distributions in the active area of large-size (several hundred cm2) cells. Furthermore, these factors change unsteadily due to the dynamic operating conditions. In order to predict the degradation of cells, it is necessary to analyze the dynamic behavior of large-area cells, but there are few spatially resolved catalyst degradation predictions [1].In this analysis, transient analysis of a large-area cell for a dynamic operating conditions is performed to predict in-plane distribution of catalyst degradation. Furthermore, we will analyze changes in the power generation performance of the cells when these degradations progress. A three-dimensional numerical simulation model based on our original methodology [2] was used as the performance prediction model for the PEMFC. Catalyst degradation considers the mechanisms of platinum dissolution, oxidation, and platinum oxide dissolution [3]. The in-plane distribution of platinum degradation is predicted from the time-series results of in-plane distributions of temperature, potential, humidity, etc., obtained by the performance prediction model. The performance of the PEMFC at the time of progressive degradation is analyzed by reflecting the effect of ECSA decrease due to platinum degradation in the performance prediction model. Although this method considers only a part of the catalyst degradation process, a path is presented to analyze the distribution of catalyst degradation under dynamic operating conditions in large-area cells.