IRNN-Based Modeling and Simulation of Electrical Characteristics of Proton Exchange Membrane Fuel Cells

Author

Tian, Yudong

Author_Institution

Automotive Eng. Dept., Shanghai Dian Ji Univ., Shanghai, China

Volume

1

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

170

Lastpage

173

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/AICI.2009.445

Filename

5376070