DocumentCode
3545119
Title
Air compressor flow forecast in fuel cell based on elman NN
Author
Deng, Jian ; Wei, Wuxing ; Gao, Xiang ; Quan, Shuhai
Author_Institution
Coll. of Autom., Wuhan Univ. of Technol., Wuhan, China
fYear
2009
fDate
16-19 Aug. 2009
Abstract
The air flow is an important parameter for the proton exchange membrane fuel cells (PEMFC) engine. Based on a modified Elman neural network, a model, which is used to forecast the air flow for fuel cell compressor, will be introduced. And the Elman neural network is used to learn and train simulation experiments of the network, and compared with simulation result of the BP neural network. Simulation result shows that the Elman neural network is precise and effective in air flow prediction.
Keywords
compressors; neural nets; power system measurement; proton exchange membrane fuel cells; BP neural network; Elman neural network; air compressor flow forecast; air flow prediction; fuel cell compressor; proton exchange membrane fuel cells; Atmospheric modeling; Biomembranes; Engines; Fasteners; Fuel cells; Inductors; Neural networks; Predictive models; Protons; Thermal management; compressor; elman algorithm; flow prediction; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-3863-1
Electronic_ISBN
978-1-4244-3864-8
Type
conf
DOI
10.1109/ICEMI.2009.5274591
Filename
5274591
Link To Document