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Summary: This article shows the teaching processes of artificial neural networks that are used to model the molten carbonate fuel cell (MCFC). Researchers model MCFCs to address a variety of issues across a range of complexities, from simply gauging the effect of temperature through to a complete model with 14 input parameters. The architecture of the model is a triple layer network with one hidden layer containing three neurons. The activation function used for the hidden layer was a hyperbolic tangent, with the last layer being based on linear function. We produced various network configurations, mostly networks containing one hidden layer. Models map the work of a real fuel cell with an average error in the range of 2.4% to 4.6%. The model we created guided the optimization of the thermal‐flow and construction parameters of the MCFC. Commercially available software was used to build the model and optimize the operating parameters. The selected objective functions were the efficiency of electricity production and the power density obtained from the cell's surface. The results obtained serve as pointers for possible changes in fuel cell operation and could lead to some structural changes being made. [ABSTRACT FROM AUTHOR]

This paper sets out the results of mathematical modeling and numerical simulations of the off-design (part-load) operation of the solid oxide fuel cell hybrid system (SOFC-HS). The governing equations of SOFC-HS modeling are given. An adequate simulator of the SOFC stack was made and described. The performance of the SOFC-HS with part-and over-load operation is shown, and adequate maps are given and described. The ranges of possible system operation conditions are determined. [Copyright &y& Elsevier]

Abstract: Based on mathematical modelling and numerical simulations, the control strategy for a molten carbonate fuel cell hybrid system (MCFC-HS) is presented. Adequate maps of performances with three independent parameters are shown. The independent parameters are as follows: stack current, fuel mass flow and compressor outlet pressure. Those parameters can be controlled by external load, fuel valve and turbine–compressor shaft speed, respectively. The control system is purposed to meet many constraints: e.g. stack temperature, steam-to-carbon ratio, compressor surge limitation, etc. The aim is to achieve maximum efficiency of power generated within those constraints. Governing equations of MCFC-HS modelling are given. An adequate simulator for the MCFC module was produced and described. Based on this simulator, the control strategy was obtained. The performance of this MCFC-HS is shown in various working environments. [Copyright &y& Elsevier]