Original scientific paper

Nonlinear modelling and adaptive fuzzy control of PEMFC

Wei Dong ; Institute of Fuel Cell, Department of Automation, Shanghai Jiao Tong University, Shanghai, PR CHINA
Guang-Yi Cao ; Institute of Fuel Cell, Department of Automation, Shanghai Jiao Tong University, Shanghai, PR CHINA
Xin-Jian Zhu ; Institute of Fuel Cell, Department of Automation, Shanghai Jiao Tong University, Shanghai, PR CHINA

Abstract

To improve the stability and performance of fuel cells, the operating temperature of proton exchange membrane fuel cells (PEMFC) should be controlled within a specified range. However, most existing mathematical models of PEMFC are too complex to be applied effectively in the control process. In this paper, adaptive fuzzy identification and control models of PEMFC are developed based on input-output sampled data and experts' experience. The parameters of the identifier and controller are regulated by an adaptive learning algorithm, the network structure and the rule database are modified by adjusting the parameters. In the end, the simulation results of the online control model are presented and show the effectiveness.

Keywords

proton exchange membrane fuel cell (PEMFC), adaptive neural-networks fuzzy infer system (ANFIS), adaptive neural-networks learning algorithm (ANA), adaptive neural-networks fuzzy controller

Hrčak ID:

316008

URI

https://hrcak.srce.hr/316008

Publication date:

30.6.2003.

Visits: 345 *