Korean Journal of Chemical Engineering, Vol.34, No.7, 1952-1960, July, 2017
A comparative study of models for molten carbonate fuel cell (MCFC) processes
The necessity of this work arose from the need for identification of a comprehensive plant model that can be used in the model-based control of the MCFC plant. Various models for molten carbonate fuel cell (MCFC) processes are presented and evaluated in this paper. Both a rigorous model based on mass and energy balances and implicit models based on operation data were investigated and analyzed. In particular, auto regressive moving average (ARMA) model, least-squares support vector machine (LSSVM) model, artificial neural network (ANN) model and partial least squares (PLS) model for a MCFC system were developed based on input output operating data. Among these models, the ARMA model showed the best agreement with plant operation data.
Keywords:Molten Carbonate Fuel Cell;ARMA Modeling;Partial Least Squares;Artificial Neural Network;Leastsquares Support Vector Machine
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