Fuel cell performance modeling, 389

The analysis of the conditions within a gas channel can also be assumed to be onedimensional given that the changes in properties in the direction transverse to the streamwise direction are relatively small in comparison to the changes in the stream-wise direction. In this section, we examine the transport in a fixed cross-sectional area gas channel. The principle conserved quantities needed in fuel cell performance modeling are energy and mass. A dynamic equation for the conservation of momentum is not often of interest given the relatively low pressure drops seen in fuel cell operation, and the relatively slow fluid dynamics employed. Hence, momentum, if of interest, is normally given by a quasi-steady model,... 

Improvements in the fuel cell performance modeling developed and validation studies in progress. 

Andreadis G, Tsiakaras P (2006) Ethanol crossover and direct ethanol PEM fuel cell performance modeling and experimental validation. Chem Eng Sci 61 7497-7508... 

Chapters 4 and 5 are devoted to various aspects of electrode and fuel cell performance modeling. The type of modeling discussed in these chapters deals with the question of how to improve/Me/ cell performance. 

There is a great variety of approaches to fuel cell performance modeling. The simplest approach used in system simulations deals with the semiempirical polarization curves of the cell or stack under investigation. Such curves are obtained by fitting a simple analytical model equation to measured data. This philosophy is very useful in the optimization of FC systems with numerous peripheral components (blowers. 

A model of MCFC performance has been developed based on the dominating losses in the system, ohmic resistance, and anode and cathode kinetic losses. The fuel cell performance model from ref. [32] is given in Eqs. (7.5)-(7.8) ... 

From the above experimental results, it can be seen that the both PtSn catalysts have a similar particle size leading to the same physical surface area. However, the ESAs of these catalysts are significantly different, as indicated by the CV curves. The large difference between ESA values for the two catalysts could only be explained by differences in detailed nanostructure as a consequence of differences in the preparation of the respective catalyst. On the basis of the preparation process and the CV measurement results, a model has been developed for the structures of these PtSn catalysts as shown in Fig. 15.10. The PtSn-1 catalyst is believed to have a Sn core/Pt shell nanostructure while PtSn-2 is believed to have a Pt core/Sn shell structure. Both electrochemical results and fuel cell performance indicate that PtSn-1 catalyst significantly enhances ethanol electrooxidation. Our previous research found that an important difference between PtRu and PtSn catalysts is that the addition of Ru reduces the lattice parameter of Pt, while Sn dilates the lattice parameter. The reduced Pt lattice parameter resulting from Ru addition seems to be unfavorable for ethanol adsorption and degrades the DEFC performance. In this new work on PtSn catalysts with more... 

Fuel Cell Energy presented a computer model for predicting carbonate fuel cell performance at different operating conditions. The model was described in detail at the Fourth International Symposium on Carbonate Fuel Cell Technology, Montreal, Canada, 1997 (93). The model equations are listed as follows ... 

Wang, Mukherjee, and Wang [124] investigated the effects of catalyst layer electrolyte and void phase fractions on fuel cell performance using a random microstructure. The model predicted volume fractions of 0.4 and 0.26 for void and electrolyte phases, respectively, as the optimal CL compositions. 

As discussed previously, a number of different materials have been considered as potential candidates to be used as diffusion layers in PEMFCs and direct liquid fuel cells (DLFCs). The two materials used the most so far in fuel cell research and products are carbon fiber papers and carbon cloths, also known as carbon woven fabrics. Both materials are made from carbon fibers. Although these materials have been quite popular for fuel cells, they have a number of drawbacks—particularly with respect to their design and model complexity—that have led to the study of other possible materials. The following sections discuss in detail the main materials that have been used as diffusion layers, providing an insight into how these materials are fabricated and how they affect fuel cell performance. 

Prasarma et al. [185] were also able to observe an optimum thickness of DLs for fuel cells experimentally. They demonstrated that the thicker DLs experience severe flooding at intermediate current densities (i.e., ohmic region) due to low gas permeation and to possible condensation of water in the pores as the thickness of the DL increases. On the other hand, as the thickness of the DL decreases, the mass transport losses, contact resistance, and mechanical weakness increase significantly [113,185]. Through the use of mathematical modeling, different research groups have reported similar conclusions regarding the effect of DL thickness on fuel cell performance [186-189]. 

Most of the models show that fuel-cell performance is a balance among the various losses shown in Figure 3, in particular, ohmic losses and mass-transport limitations, which both increase with current. The reason for this is that the kinetic losses are hard to mitigate without significantly changing op-... 

As shown in Figure 16b, the 2-D rib models deal with how the existence of a solid rib affects fuel-cell performance. They do not examine the along-the-channel effects discussed above. Instead, the relevant dimensions deal with the physical reality that the gas channeFdiffusion media interfaces are not continuous. Instead, the ribs of the flow-channel plates break them. These 2-D models focus on the cathode side of the fuel-cell sandwich because oxygen and water transport there have a much more significant impact on performance. This is in contrast to the along-the-channel models that show that the underhumidification of and water transport to the anode are more important than those for the cathode. 

Finally, there are some miscellaneous polymer-electrolyte fuel cell models that should be mentioned. The models of Okada and co-workers - have examined how impurities in the water affect fuel-cell performance. They have focused mainly on ionic species such as chlorine and sodium and show that even a small concentration, especially next to the membrane at the cathode, impacts the overall fuelcell performance significantly. There are also some models that examine having free convection for gas transfer into the fuel cell. These models are also for very miniaturized fuel cells, so that free convection can provide enough oxygen. The models are basically the same as the ones above, but because the cell area is much smaller, the results and effects can be different. For example, free convection is used for both heat transfer and mass transfer, and the small... 

Recent kinetic studies indicate that carbon corrosion can be significant under normal transient operation.56,57,60-62 The rate of voltage change, common in the automotive application, enhances cathode carbon-support corrosion.16 Hence, further model improvement shall be focused on finding the carbon corrosion kinetics associated with voltage cycling. Currently, the relationship between fuel cell performance decay and accumulated carbon-support loss is only empirical.22 More effort has to be made to incorporate mechanisms that can accurately quantify voltage decay with carbon-support loss.31,32... 

Finally, a key highlight of this investigation is that the systematic estimation of the effective transport parameters for the porous CL and GDL from the mesoscopic modeling can quantitatively predict the fuel cell performance from the macroscopic fuel cell models. 

Bearing in mind that phenomena occurring in nature are too complex to be completely described by mathematical equations, the required details to be described by the model must be goal-driven, i.e. the complexity of the model, and the related results, must be strictly connected to the main goal of the analysis itself. When, for example, the main purpose of the model is to provide the fuel cell performance, in order to analyze the whole system in which it is embedded, the spatial variation in the physical and chemical variables (such as gas concentration, temperature, pressure and current density, for example) are not relevant however the performances, in terms of efficiency, electrical and thermal power and input requirements are important [1-4],... 

The so-called micromodels are models of a particular component, or of a part of a cell component, conducted at molecular or atomistic level. Due to the high level of detail related to the material properties and characteristics, the information provided by such models is usually limited to the specific phenomenon analyzed, and provides only limited indications on the resulting fuel cell performance and operating conditions. However, the results of such models play a fundamental role in understanding, analyzing and designing improved solutions for SOFC. Moreover, the results of such analyses may be used as an input for macro-models, i.e. models conducted at fuel cell level. 

Aguiar P., Adjiman C.S., Brandon N.P. (2005) Anode-supported intermediate-temperature direct internal reforming solid oxide fuel cell II Model-based dynamic performance and control. Journal of Power Sources 147, 136-147. 

Fuel cell performance is affected by MEA composition, including catalyst loading, PTFE content in the gas diffusion layer, and Nafion content in the catalyst layer and membrane, each of which affects the performance in different ways, yielding distinct characteristics in the electrochemical impedance spectra. Even different fabrication methods may influence a cell s performance and electrochemical impedance spectra. With the help of the model described above, impedance spectra can provide us with a useful tool to probe structure-performance relationships and thereby optimize MEA structure and fabrication methods. 

Evidently, modeling of fuel cells is a delicate task, which comprises a multitude of functions, ranging from posing problems for research programs in fundamental science to laying out routes toward optimization of fuel cell performance. Relevant areas of fundamental... 

There are different approaches that incorporate the water balance in the membrane into models of fuel cell performance. They rest on different concepts of membrane microstructure. As a common feature they use local values of transport parameters which are functions of the local water content, w (volume fraction of water relative to the total membrane volume). 

---