- -

Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

Mostrar el registro completo del ítem

Ariza-Chacón, HE.; Correcher Salvador, A.; Sánchez-Diaz, C.; Pérez-Navarro, Á.; García Moreno, E. (2018). Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm. Energies. 11(8):1-15. https://doi.org/10.3390/en11082099

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/151154

Ficheros en el ítem

Metadatos del ítem

Título: Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm
Autor: Ariza-Chacón, Helbert Eduardo Correcher Salvador, Antonio Sánchez-Diaz, Carlos Pérez-Navarro, Ángel García Moreno, Emilio
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica
Universitat Politècnica de València. Instituto de Ingeniería Energética - Institut d'Enginyeria Energètica
Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica
Fecha difusión:
Resumen:
[EN] Proton Exchange Membrane Fuel Cell (PEMFC) fuel cells is a technology successfully used in the production of energy from hydrogen, allowing the use of hydrogen as an energy vector. It is scalable for stationary and ...[+]
Palabras clave: PEM fuel cell , Identification , Genetic algorithm , Model , LabVIEW
Derechos de uso: Reconocimiento (by)
Fuente:
Energies. (eissn: 1996-1073 )
DOI: 10.3390/en11082099
Editorial:
MDPI AG
Versión del editor: https://doi.org/10.3390/en11082099
Código del Proyecto:
info:eu-repo/grantAgreement/COLCIENCIAS//COLDOC 586/
Agradecimientos:
This research was funded by COLCIENCIAS (Administrative department of science, technology and innovation of Colombia) scholarship program PDBCEx, COLDOC 586, and the support provided by the Corporacion Universitaria ...[+]
Tipo: Artículo

References

Mehta, V., & Cooper, J. S. (2003). Review and analysis of PEM fuel cell design and manufacturing. Journal of Power Sources, 114(1), 32-53. doi:10.1016/s0378-7753(02)00542-6

Wang, Y., Chen, K. S., Mishler, J., Cho, S. C., & Adroher, X. C. (2011). A review of polymer electrolyte membrane fuel cells: Technology, applications, and needs on fundamental research. Applied Energy, 88(4), 981-1007. doi:10.1016/j.apenergy.2010.09.030

Amphlett, J. C., Baumert, R. M., Mann, R. F., Peppley, B. A., Roberge, P. R., & Harris, T. J. (1995). Performance Modeling of the Ballard Mark IV Solid Polymer Electrolyte Fuel Cell: I . Mechanistic Model Development. Journal of The Electrochemical Society, 142(1), 1-8. doi:10.1149/1.2043866 [+]
Mehta, V., & Cooper, J. S. (2003). Review and analysis of PEM fuel cell design and manufacturing. Journal of Power Sources, 114(1), 32-53. doi:10.1016/s0378-7753(02)00542-6

Wang, Y., Chen, K. S., Mishler, J., Cho, S. C., & Adroher, X. C. (2011). A review of polymer electrolyte membrane fuel cells: Technology, applications, and needs on fundamental research. Applied Energy, 88(4), 981-1007. doi:10.1016/j.apenergy.2010.09.030

Amphlett, J. C., Baumert, R. M., Mann, R. F., Peppley, B. A., Roberge, P. R., & Harris, T. J. (1995). Performance Modeling of the Ballard Mark IV Solid Polymer Electrolyte Fuel Cell: I . Mechanistic Model Development. Journal of The Electrochemical Society, 142(1), 1-8. doi:10.1149/1.2043866

Tao, S., Si-jia, Y., Guang-yi, C., & Xin-jian, Z. (2005). Modelling and control PEMFC using fuzzy neural networks. Journal of Zhejiang University-SCIENCE A, 6(10), 1084-1089. doi:10.1631/jzus.2005.a1084

Amphlett, J. C., Mann, R. F., Peppley, B. A., Roberge, P. R., & Rodrigues, A. (1996). A model predicting transient responses of proton exchange membrane fuel cells. Journal of Power Sources, 61(1-2), 183-188. doi:10.1016/s0378-7753(96)02360-9

Mo, Z.-J., Zhu, X.-J., Wei, L.-Y., & Cao, G.-Y. (2006). Parameter optimization for a PEMFC model with a hybrid genetic algorithm. International Journal of Energy Research, 30(8), 585-597. doi:10.1002/er.1170

YE, M., WANG, X., & XU, Y. (2009). Parameter identification for proton exchange membrane fuel cell model using particle swarm optimization. International Journal of Hydrogen Energy, 34(2), 981-989. doi:10.1016/j.ijhydene.2008.11.026

Askarzadeh, A., & Rezazadeh, A. (2011). A grouping-based global harmony search algorithm for modeling of proton exchange membrane fuel cell. International Journal of Hydrogen Energy, 36(8), 5047-5053. doi:10.1016/j.ijhydene.2011.01.070

El-Fergany, A. A. (2018). Electrical characterisation of proton exchange membrane fuel cells stack using grasshopper optimiser. IET Renewable Power Generation, 12(1), 9-17. doi:10.1049/iet-rpg.2017.0232

Li, Q., Chen, W., Wang, Y., Liu, S., & Jia, J. (2011). Parameter Identification for PEM Fuel-Cell Mechanism Model Based on Effective Informed Adaptive Particle Swarm Optimization. IEEE Transactions on Industrial Electronics, 58(6), 2410-2419. doi:10.1109/tie.2010.2060456

Ali, M., El-Hameed, M. A., & Farahat, M. A. (2017). Effective parameters’ identification for polymer electrolyte membrane fuel cell models using grey wolf optimizer. Renewable Energy, 111, 455-462. doi:10.1016/j.renene.2017.04.036

Sun, Z., Wang, N., Bi, Y., & Srinivasan, D. (2015). Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm. Energy, 90, 1334-1341. doi:10.1016/j.energy.2015.06.081

Gong, W., Yan, X., Liu, X., & Cai, Z. (2015). Parameter extraction of different fuel cell models with transferred adaptive differential evolution. Energy, 86, 139-151. doi:10.1016/j.energy.2015.03.117

Turgut, O. E., & Coban, M. T. (2016). Optimal proton exchange membrane fuel cell modelling based on hybrid Teaching Learning Based Optimization – Differential Evolution algorithm. Ain Shams Engineering Journal, 7(1), 347-360. doi:10.1016/j.asej.2015.05.003

Al-Othman, A. K., Ahmed, N. A., Al-Fares, F. S., & AlSharidah, M. E. (2015). Parameter Identification of PEM Fuel Cell Using Quantum-Based Optimization Method. Arabian Journal for Science and Engineering, 40(9), 2619-2628. doi:10.1007/s13369-015-1711-0

Methekar, R. N., Prasad, V., & Gudi, R. D. (2007). Dynamic analysis and linear control strategies for proton exchange membrane fuel cell using a distributed parameter model. Journal of Power Sources, 165(1), 152-170. doi:10.1016/j.jpowsour.2006.11.047

KUNUSCH, C., HUSAR, A., PULESTON, P., MAYOSKY, M., & MORE, J. (2008). Linear identification and model adjustment of a PEM fuel cell stack. International Journal of Hydrogen Energy, 33(13), 3581-3587. doi:10.1016/j.ijhydene.2008.04.052

Li, C.-H., Zhu, X.-J., Cao, G.-Y., Sui, S., & Hu, M.-R. (2008). Identification of the Hammerstein model of a PEMFC stack based on least squares support vector machines. Journal of Power Sources, 175(1), 303-316. doi:10.1016/j.jpowsour.2007.09.049

Fontes, G., Turpin, C., & Astier, S. (2010). A Large-Signal and Dynamic Circuit Model of a $\hbox{H}_{2}/\hbox{O}_{2}$ PEM Fuel Cell: Description, Parameter Identification, and Exploitation. IEEE Transactions on Industrial Electronics, 57(6), 1874-1881. doi:10.1109/tie.2010.2044731

Cheng, S.-J., & Liu, J.-J. (2015). Nonlinear modeling and identification of proton exchange membrane fuel cell (PEMFC). International Journal of Hydrogen Energy, 40(30), 9452-9461. doi:10.1016/j.ijhydene.2015.05.109

Buchholz, M., & Krebs, V. (2007). Dynamic Modelling of a Polymer Electrolyte Membrane Fuel Cell Stack by Nonlinear System Identification. Fuel Cells, 7(5), 392-401. doi:10.1002/fuce.200700013

Meiler, M., Schmid, O., Schudy, M., & Hofer, E. P. (2008). Dynamic fuel cell stack model for real-time simulation based on system identification. Journal of Power Sources, 176(2), 523-528. doi:10.1016/j.jpowsour.2007.08.051

Wang, C., Nehrir, M. H., & Shaw, S. R. (2005). Dynamic Models and Model Validation for PEM Fuel Cells Using Electrical Circuits. IEEE Transactions on Energy Conversion, 20(2), 442-451. doi:10.1109/tec.2004.842357

Restrepo, C., Konjedic, T., Garces, A., Calvente, J., & Giral, R. (2015). Identification of a Proton-Exchange Membrane Fuel Cell’s Model Parameters by Means of an Evolution Strategy. IEEE Transactions on Industrial Informatics, 11(2), 548-559. doi:10.1109/tii.2014.2317982

Salim, R., Nabag, M., Noura, H., & Fardoun, A. (2015). The parameter identification of the Nexa 1.2 kW PEMFC’s model using particle swarm optimization. Renewable Energy, 82, 26-34. doi:10.1016/j.renene.2014.10.012

Pérez-Navarro, A., Alfonso, D., Ariza, H. E., Cárcel, J., Correcher, A., Escrivá-Escrivá, G., … Vargas, C. (2016). Experimental verification of hybrid renewable systems as feasible energy sources. Renewable Energy, 86, 384-391. doi:10.1016/j.renene.2015.08.030

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem