Polymer electrolyte membranes model parameters

Based on this framework, a Binary Friction Membrane Model (BFM2) was developed to account for coupled transport of water and hydronium ions in polymer electrolyte membranes. The BFM2 was cast in a general form to allow for broad applicability to the PFSA family of membranes. As a tool to determine the model parameters, a simplified Binary Friction Conductivity Model (BFCM) was derived to represent conditions found in AC impedance conductivity measurements. 

In the scope of the thesis, a steady-state model of polymer electrolyte membrane fuel cell was made by Matlab. The model was based on simplified chemical and electrical equations. The most important performance related parameters, namely operation temperature and pressure, were parametrically investigated. Output voltage, electrical output power, heat generation, material inputs and outputs, and efficiencies according to first and second law of thermodynamics were plotted by the change of temperature and pressure against current density. 

A number of models describing supercapacitor resistor and capacitor behaviors used to mimic their performances in power systems have been reported and include classical equivalent, ladder circuit, and lumped or distributed parameter electrical and Debye polarization cell models [6]. An established design of a dynamic model of the often-used polymer electrolyte membrane fuel cell (PEMFC) is included in MATLAB and Simulink software to simulate performance under varying conditions specific to applications. 

This review has highlighted the important effects that should be modeled. These include two-phase flow of liquid water and gas in the fuel-cell sandwich, a robust membrane model that accounts for the different membrane transport modes, nonisothermal effects, especially in the directions perpendicular to the sandwich, and multidimensional effects such as changing gas composition along the channel, among others. For any model, a balance must be struck between the complexity required to describe the physical reality and the additional costs of such complexity. In other words, while more complex models more accurately describe the physics of the transport processes, they are more computationally costly and may have so many unknown parameters that their results are not as meaningful. Hopefully, this review has shown and broken down for the reader the vast complexities of transport within polymer-electrolyte fuel cells and the various ways they have been and can be modeled. 

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