Full Text:
<2963>
CLC number: TP29
On-line Access:
Received: 2005-10-21
Revision Accepted: 2006-07-06
Crosschecked: 0000-00-00
Cited: 0
Clicked: 5886
Simulation and analysis of energy optimization for PEMFC hybrid system
| |||||||||||||
LIU Cheng-ze, ZHU Xin-jian. Simulation and analysis of energy optimization for PEMFC hybrid system[J]. Journal of Zhejiang University Science A, 2006, 7(11): 1878-1885.
@article{title="Simulation and analysis of energy optimization for PEMFC hybrid system",
author="LIU Cheng-ze, ZHU Xin-jian",
journal="Journal of Zhejiang University Science A",
volume="7",
number="11",
pages="1878-1885",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1878"
}
%0 Journal Article
%T Simulation and analysis of energy optimization for PEMFC hybrid system
%A LIU Cheng-ze
%A ZHU Xin-jian
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 11
%P 1878-1885
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A1878
TY - JOUR
T1 - Simulation and analysis of energy optimization for PEMFC hybrid system
A1 - LIU Cheng-ze
A1 - ZHU Xin-jian
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 11
SP - 1878
EP - 1885
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A1878
Abstract: The control objective and several key parameters of PEMFC hybrid system are analyzed. Control strategy design and energy optimization simulation are made individually for given cycle case and realtime operating case. For the given cycle case, genetic algorithm is adopted to solve the multi-constraint combinatorial optimization problem. Simulation result showed the algorithm’s feasibility. As far as the realtime operation is concerned, based on the original fuzzy control strategy, the fuel cell voltage and voltage variance parameters are introduced to apply two-level modification on the fuzzy control output. The result reveals that the improved fuzzy control strategy can enhance the fuel cell efficiency and reduce the power fluctuations.
[1] Barili, A., Cersea, M., Parisi, C., 1995. Energy-saving Motion Control for an Autonomous Mobile Robot. Proceedings of the IEEE International Symposium, Pavia, Italy, 2:674-676.
[2] Gao, Y., Ehsani, M., 2001. Systematic Design of Fuel Cell Powered Hybrid Vehicle Drive Train. Electric Machines and Drives Conference, IEMDC 2001, Cambridge, America, p.604-611.
[3] Haugen, L.B., Ayers, P.D., 2003. Vehicle movement patterns and vegetative impacts during military training exercises. Journal of Terramechanics, 40(2):83-95.
[4] Iqbal, M.T., 2003. Modelling and control of a wind fuel cell hybrid energy system. Renewable Energy, 28(2):223-237.
[5] Lee, H.S., Jeong, K.S., Oh, B.S., 2003. An experimental study of controlling strategies and drive forces for hydrogen fuel cell hybrid vehicles. International Journal of Hydrogen Energy, 28(2):215-222.
[6] Markel, T., Brooker, A., Hendricks, T., Johnson, V., Kelly, K., Kramer, B., O’Keefe, M., Sprik, S., Wipke, K., 2002. ADVISOR: a systems analysis tool for advanced vehicle modelling. Journal of Power Sources, 110(2):255-266.
[7] Nasiri, A., Rimmalapudi, V.S., 2004. Active Control of a Hybrid Fuel Cell-battery System. Power Electronics and Motion Control Conference, IPEMC 2004, Xi’an, China, 2:491-496.
[8] van Mierlo, J., van den Bossche, P., Maggetto, G., 2004. Models of energy sources for EV and HEV: fuel cells, batteries, ultracapacitors, flywheels and engine-generators. Journal of Power Sources, 128(1):76-89.
[9] Wipke, K., Markel, T., Nelson, D., 2001. Optimizing Energy Management Strategy and Degree of Hybridization for a Hydrogen Fuel Cell SUV. Http://www.ctts.nrel.gov/analysis/.
Open peer comments: Debate/Discuss/Question/Opinion
<1>