A comparative study of models for molten carbonate fuel cell (MCFC) processes

Tae Young Kim; Beom Seok Kim; Tae Chang Park; Yeong Koo Yeo

Korean Journal of Chemical Engineering, Vol.34, No.7, 1952-1960, July, 2017

DOI10.1007/s11814-017-0117-y Export Citation

A comparative study of models for molten carbonate fuel cell (MCFC) processes

Tae Young Kim, Beom Seok Kim, Tae Chang Park, and Yeong Koo Yeo^†

Department of Chemical Engineering, Hanyang University, Seoul 04763, Korea

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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

[References]

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Shen C, Cao GY, Zhu XJ, Sun XJ, J. Process Control, 12(8), 831 (2002)
Ahmed F, Cho HJ, Kim JK, Seong NU, Yeo YK, Korean J. Chem. Eng., 32(6), 1029 (2015)
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Tian YD, Zhu XJ, Cao GY, J. University of Science and Technology Beijing, 12, 72 (2005)
Haaland DM, Thomas EV, Anal. Chem., 60(11), 1193 (1988)

[Referenced By]

[1] He W, J. Power Sources, 52, 179 (1994)

[2] He W, J. Power Sources, 55, 25 (1995)

[3] Ernest JB, Ghezel-Ayagh H, Kush AK, Proceedings of the 1996 fuel cell seminar, Orlando, FL, U.S.A., 75 (1996).

[4] Lukas MD, Lee KY, Ghezel-Ayagh H, IEEE Trans. Energy Conver., 14(4), 1651 (1999)

[5] Li Z, Zhong W, Liu Y, Luo N, Qian F, Korean J. Chem. Eng., 32(4), 597 (2015)

[6] Sheng M, Mangold M, Kienle A, J. Power Sources, 162(2), 1213 (2006)

[7] Shen C, Cao GY, Zhu XJ, Simulation Modeling Practice and Theory, 10, 109 (2002)

[8] Shen C, Cao GY, Zhu XJ, Sun XJ, J. Process Control, 12(8), 831 (2002)

[9] Ahmed F, Cho HJ, Kim JK, Seong NU, Yeo YK, Korean J. Chem. Eng., 32(6), 1029 (2015)

[10] Farooque M, Maru HC, Baker B, Proceedings of the 28th intersociety energy conversion engineering conference, Atlanta, GA, U.S.A., 181 (1993).

[11] Lukas MD, Lee KY, Mand H. Ghezel-Ayagh, Control Engineering Practice, 197 (2002).

[12] Lukas MD, Lee KY, Ghezel-Ayagh H, Proceedings of the 2000 IEEE power engineering society summer meeting, Seattle, WA, U.S.A., 1793 (2000).

[13] M.D. Lukas and K.Y. Lee, Fuel Cells, 5(1), 115 (2005)

[14] Murshed AKMM, Huang B, Nandakumar K, J. Power Sources, 163(2), 830 (2007)

[15] Hirschenhofer JH, Stauffer DB, Engleman RR, Klett MG, Fuel cell handbook, US, Department of Energy (1998).

[16] Said SE, David D, Dickey A, Biometrika, 71(3), 599 (1984)

[17] Suykens JAK, Proceeding of IEEE Instrumentation and measurement technology, Budapest, 287 (2001).

[18] Samui P, Scientific Research, 431 (2011).

[19] Wang H, Hu D, IEEE, 279 (2005).

[20] Hagan MT, Demuth HB, Beale MH, Boston, MA: PWS Publishing Company (1996).

[21] Tian YD, Zhu XJ, Cao GY, J. University of Science and Technology Beijing, 12, 72 (2005)

[22] Haaland DM, Thomas EV, Anal. Chem., 60(11), 1193 (1988)