In this review, we have examined the different models for polymer-electrolyte fuel cells operating with hydrogen. The major focus has been on transport of the various species within the fuel cell. The different regions of the fuel cell were examined, and their modeling methodologies and equations were elucidated. In particular, the 1-D fuel-cell sandwich was discussed thoroughly because it is the most important part of the fuel-cell assembly. Models that included other effects such as temperature gradients and transport in other directions besides through the fuel-cell sandwich were also discussed. Models were not directly compared to each other; instead they were broken down into their constitutive parts. The reason for this is that validation of the models is usually accomplished by comparison of simulation to experimental polarization data (e.g., Figure 3). However, other data can also be used such as the net flux of water through the membrane. In fitting these data, the models vary not only in their complexity and treatments but also in their number and kind of fitting parameters. This is one reason it is hard to justify one approach over another by just looking at the modeling results. In general, it seems reasonable that the more complex models, which are based on physical arguments and do not contain many fitting parameters, are perhaps closest to reality. Of course, this assumes that they fit the experimental data and observations. This last point has been overlooked in the validation of many models. For example, a model may fit the data very well for certain operating conditions, but if it does not at least predict the correct trend when one of those conditions is changed, then the model is shown to be valid only within a certain operating range. 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.

Modeling transport in polymer-electrolyte fuel cells.

Development of direct methanol alkaline fuel cells using anion exchange membranes

Mass transport phenomena in direct methanol fuel cells

Mathematical modeling of a passive-feed DMFC with heat transfer effect

Methanol-tolerant oxygen reduction catalysts based on transition metal sulfides and their application to the study of methanol permeation

http://www.panosargyropoulos.gr/pdf/Limiting%20current%20behavior%20of%20the%20direct%20methanol%20fuel%20cell.pdf

Limiting current behaviour of the direct methanol fuel cell

http://www.panosargyropoulos.gr/pdf/Dynamic%20modelling%20of%20the%20voltage%20response%20of%20direct%20methanol%20fuel%20cells%20and%20stacks%20Part%20I%20Model%20development%20and%20validation.pdf

Dynamic modelling of the voltage response of direct methanol fuel cells and stacks Part I: Model development and validation

http://www.panosargyropoulos.gr/pdf/Dynamic%20modelling%20of%20the%20voltage%20response%20of%20direct%20methanol%20fuel%20cells%20and%20stacks%20Part%20II%20Feasibility%20study%20of%20model-based%20scale-up%20and%20scale-down.pdf

W.M. Taama

Papers

Limiting current behaviour of the direct methanol fuel cell

Dynamic modelling of the voltage response of direct methanol fuel cells and stacks Part I: Model development and validation

Dynamic modelling of the voltage response of direct methanol fuel cells and stacks Part II: Feasibility study of model-based scale-up and scale-down