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• To evaluate the technical and economic suitability of fuel cells in applications. Models can be used to determine whether a fuel cell’s unique characteristics will match the requirements of a given application and evaluate its cost-effectiveness. Each of these applications for fuel cell models has a specific requirement with respect to the level of detail and rigor in the model and its predictive capability. In many higher level applications, the predictive requirements are modest. In some cases, the operational characteristics of the fuel cell are not even a degree a freedom. In such cases, relatively simple models are satisfactory and appropriate. It is possible to encapsulate the mass and energy balances and performance equations for a fuel cell within a spreadsheet application. Such spreadsheet models are often useful for quick trade-off considerations. On the other end of the spectrum, models intended to improve understanding of complex physical and chemical phenomena or to optimize cell geometries and flow patterns are necessarily very sophisticated, and usually have intensive computational requirements. As expected, given this wide range of potential uses and the variety of fuel cell types, an equally wide variety of fuel cell models has been developed. While fundamentally the constitutive equations such as those described earlier in this chapter underlie all models, their level of detail, level of aggregation, and numerical implementation method vary widely. A useful categorization of fuel cell models is made by level of aggregation, as shown in Figure 2-9. As implied in the figure, the outputs of the more detailed fundamental models can be used in lower-order models. This flow of information is, in fact, a critical application for high fidelity models. Recently, much work has been done in the development of algorithms to integrate or embed high-fidelity models into system analysis simulation tools. Despite the availability of quite sophisticated fuel cell models with well-written code and convenient user interfaces, the fuel cell developer or engineer must be a critical user. As mentioned above, obtaining experimental data on the behavior of fuel cells (especially internally and at the micro-level) can be difficult, time-consuming, and expensive. Unfortunately this has lead to a dearth of accurate and detailed data of sufficient quality and quantity to allow thorough validation of the mathematical models. Much of the data on fuel cell performance reported in the literature is, while phenomenologically often interesting, insufficiently accurate and accompanied by far too little detail on the test conditions to be usable for model validation. In particular, with much of the cell and stack taken at modest utilization, it is almost impossible to infer kinetic data without spatially resolved data on current density, temperature and species concentrations. As a consequence, the validity of fuel cell models must be critically considered for each use. The user of the model must be thoroughly familiar with the assumptions and limitations embedded in the models. 2-25PDF Image | Fuel Cell Handbook (Seventh Edition)
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