Hajimolana, S.A. and Hussain, Mohd Azlan and Daud, Wan Mohd Ashri Wan and Chakrabarti, M.H. (2012) Neural network predictive control of a SOFC fuelled with ammonia. International Journal of Electrochemical Science, 7 (4). pp. 3737-3749. ISSN 1452-3981,
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Abstract
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 predictive controller (NNPC) 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 |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | 947FF Times Cited:0 Cited References Count:33 |
| Uncontrolled Keywords: | Ammonia fuel; Neural network predictive control; Sofc; Cell-tube temperature; Proton conducting electrolyte; Finite-volume; Cell; Model; Performance; Sensitivity; Dynamics; System |
| 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 01:05 |
| Last Modified: | 20 Jan 2021 07:41 |
| URI: | http://eprints.um.edu.my/id/eprint/7007 |
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