Neural network predictive control of a tubular solid oxide fuel cell

Hajimolana, S.A. and Hussain, Mohd Azlan and Natesan, J. and Tonekaboni Moghaddam, S.M. (2012) Neural network predictive control of a tubular solid oxide fuel cell. Computer Aided Chemical Engineering, 31. pp. 390-394. ISSN 15707946 , DOI

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The dynamic behavior and control of a tubular solid oxide fuel cell will be studied in this paper. The effect of fuel/air temperature and pressure will be investigated. Controlling the average stack temperature is the final objective of this study due to a high operating temperature of the system. In this case, temperature fluctuation induces thermal stress in the electrodes and electrolyte ceramics; therefore, the cell temperature distribution should be kept as constant as possible. A mathematical modeling based on first principles is developed. The fuel cell is divided into five subsystems and the factors such as mass/energy/momentum transfer, diffusion through porous media, electrochemical reactions, and polarization losses inside the subsystems are presented. Dynamic fuel-cell-tube temperature responses of the cell to step changes in conditions of the feed streams will be presented. A neural network model predictive controller (NNMPC) is then implemented to control the cell-tube temperature through manipulation of the temperature of the inlet air stream. The results show that the control system can successfully reject unmeasured step changes (disturbances) in the load resistance.

Item Type: Article
Additional Information: Export Date: 5 March 2013 Source: Scopus doi: 10.1016/B978-0-444-59507-2.50070-6 Language of Original Document: English Correspondence Address: Hajimolana, S.A.; Chemical Engineering Department, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia References: Ni, M., Leung, M.K.H., Mathematical modelling of ammonia-fed solid oxide fuel cells with different electrolytes (2008) Int. J. of Hydrogen Energy, 88 (33), pp. 5765-5772; Jurado, F., Predictive control of solid oxide fuel cells using fuzzy Hammerstein models (2006) J. Pow. Sour, 11 (158), pp. 245-253; Hajimolana, S.A., Soroush, M., Dynamics and Control of a Tubular Solid-Oxide Fuel Cell (2009) Ind. Eng. Chem, 23 (48), pp. 6112-6125; Hajimolana, S.A., Hussain, M.A., Wan Daud, W.A., Soroush, M., Shamiri, A., Mathematical modelling of solid oxide fuel cells: A review (2011) Renew. and Sustain. Ener. Rev., 121 (15), pp. 1893-1917; Meng, G., Comparative study on the performance of a SDC-based SOFC fueled by ammonia and hydrogen (2007) J. Pow. Sour, 32 (173), pp. 189-193; Singhal, S.C., Advances in solid oxide fuel cell technology (2003) Sol. St. Ion, 23 (135), pp. 305-313; Ota, T., Object-based modeling of SOFC system: dynamic behavior of micro-tube SOFC (2003) J. Pow. Sour, 118 (125), pp. 430-439
Uncontrolled Keywords: Cell-tube temperature, Neural network predictive control, SOFC.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 10 Jul 2013 01:03
Last Modified: 10 Feb 2021 03:51

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