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
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;
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
DOI :
10.1109/ICEMI.2009.5274591
