Title :
IRNN-Based Modeling and Simulation of Electrical Characteristics of Proton Exchange Membrane Fuel Cells
Author_Institution :
Automotive Eng. Dept., Shanghai Dian Ji Univ., Shanghai, China
Abstract :
The proton exchange membrane fuel cell (PEMFC) is a rising research field, and PEMFC modeling is a key of PEMFC research and development. However, PEMFC mechanism models were too complicated to be suitable for PEMFC practical system control at present. To aim at the problem, the PEMFC mechanism was analyzed, and then PEMFC modeling applied artificial neural networks was advanced. The structure, algorithm, training and simulation of PEMFC modeling based on internal recurrent neural networks (IRNN) were presented in detail. The computer simulation and conducted experiment verified that this model was fast and accurate, and could be as a suitable operational model of PEMFC real-time control.
Keywords :
power system control; proton exchange membrane fuel cells; recurrent neural nets; IRNN; PEMFC electrical characteristics; PEMFC practical system control; PEMFC real-time control; artificial neural networks; internal recurrent neural networks; proton exchange membrane fuel cells mechanism model; Artificial neural networks; Biomembranes; Computational modeling; Computer simulation; Control system synthesis; Electric variables; Fuel cells; Protons; Recurrent neural networks; Research and development; Proton exchange membrane fuel cells; artificial neural networks; modeling; simulation;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.445
