Kevin L. Davies
Georgia Institute of Technology, Woodruff School of Mechanical Engineering, Atlanta, Georgia USA
Robert M. Moore
Hawaii Natural Energy Institute, Honolulu, Hawaii USA
Guido Bender
Hawaii Natural Energy Institute, Honolulu, Hawaii USA
Ladda ner artikelhttp://dx.doi.org/10.3384/ecp09430107Ingår i: Proceedings of the 7th International Modelica Conference; Como; Italy; 20-22 September 2009
Linköping Electronic Conference Proceedings 43:7, s. 56-65
Publicerad: 2009-12-29
ISBN: 978-91-7393-513-5
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
The trade-offs among dynamic response; efficiency; and robustness to external factors are fundamental to the optimization of hardware and controls for fuel cell systems. No previously published model of polymer electrolyte membrane fuel cells (PEMFCs) has the capability to simultaneously provide dynamic modeling capabilities; a clear representation of physical configurations; adjustable fidelity; and flexible interfaces. This paper presents the first such library; explains key aspects of the library’s architecture; and demonstrates simulations under representative scenarios. The models; implemented in the acausal Modelica modeling language; are quasi-three-dimensional
(quasi-3D); discretizing the fuel cell and its layers along the directions from the anode to the cathode and down the channel length.
[1] D. M. Bernardi and M. W. Verbrugge. A mathematical model of the solid-polymer-electrolyte fuel cell. Journal of The Electrochemical Society; 13(9):2477-91; 1992. doi: 10.1149/1.2221251
[2] F. E. Cellier and E. Kofman. Continuous System Simulation. Springer; New York; NY; 2006.
[3] K. Davies and R. Moore. Object-oriented fuel cell model library. ECS Transactions; 11(1):797; 2007. doi: 10.1149/1.2780993
[4] K. Davies and R. Moore. PEMFCSim: A fuel cell model library in Modelica. In Fuel Cell Seminar; Austin; TX; 2007.
[5] Dynasim AB. Dymola: Dynamic modeling laboratory; 2007. v6.2.
[6] K. Forsberg and H. Mooz. System engineering for faster; cheaper; better. The Center for Systems Management; Reprinted by SF Bay Area Chapter of INCOSE; http://www.incose.org/sfbac/; 1998.
[7] Modelica Association. Modelica: A Unified Object-Oriented Language for Physical Systems Modeling: Tutorial. Linköping; Sweden; ver. 1.4 edition; December 2000.
[8] Modelica Association. Modelica: A unified object-oriented language for physical systems modeling; February 2 2005.
[9] M. A. Rubio; A. Urquia; L. González; D. Guinea; and S. Dormido. FuelCellLib: A modelica library for modeling of fuel cells. In 4th International Modelica Conference; Hamburg-Harburg; Germany; March 2005. Modelica Association.
[10] T. E. Springer; M. S. Wilson; and S. Gottesfeld. Modeling and experimental diagnostics in polymer electrolyte fuel cells. Journal of The Electrochemical Society; 140(12):3513–3526; 1993. doi: 10.1149/1.2221120
[11] T. E. Springer; T. A. Zawodzinski; and S. Gottesfeld. Polymer electrolyte fuel cell model. Journal of The Electrochemical Society; 138(8):2334–2342; 1991. doi: 10.1149/1.2085971
[12] J. Ungethüm. Fuel cell system modeling for real-time simulation. In 4th International Modelica Conference; Hamburg-Harburg; Germany; March 2005. Modelica Association.
[13] A. Z. Weber and J. Newman. Transport in polymer-electrolyte membranes III: Model validation in a simple fuel-cell model. Journal of The Electrochemical Society ; 151(2):326–339; 2004. doi: 10.1149/1.1639158
[14] F. Zenith; F. Seland; O. E. Kongstein; B. Borresen; R. Tunold; and S. Skogestad. Control-oriented modelling and experimental study of the transient response of a high-temperature polymer fuel cell. Journal of Power Sources; 162(1):215–227; 2006. doi: 10.1016/j.jpowsour.2006.06.022