Modeling of DIR-SOFC Based on Particle Swarm Optimization-Wavelet Network

Jun Li; Nan Gao; Guang Yi Cao; Xin Jian Zhu

doi:10.4028/www.scientific.net/AMR.557-559.2202

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 557-559Modeling of DIR-SOFC Based on Particle Swarm...

Modeling of DIR-SOFC Based on Particle Swarm Optimization-Wavelet Network

Abstract:

Direct internal reforming solid oxide fuel cell (DIR-SOFC) is directly fueled with hydrocarbons and converts the chemical energy of the fuel directly into electrical energy. Particle swarm optimization (PSO) with adaptive inertia weights has global search ability and faster convergence rate. Wavelet network (WN) combines the advantage of multi-resolution approximation (MRA) of the wavelet decomposition and the capability of neural networks in learning from nonlinear process. The DIR-SOFC is considered a complicated nonlinear multi-input and multi-output (MIMO) system which contains coupling parameters. A method combines the WN with PSO algorithm is applied to establish the model of DIR-SOFC, avoiding the consideration of the complex process inside the cell. The simulation results show that the obtained dynamic model can accurately simulate the dynamics of the DIR-SOFC.

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Periodical:

Advanced Materials Research (Volumes 557-559)

Pages:

2202-2207

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.557-559.2202

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Online since:

July 2012

Authors:

Jun Li, Nan Gao, Guang Yi Cao, Xin Jian Zhu

Keywords:

Direct Internal Reforming, Particle Swarm Optimization Algorithm (PSO), Solid Oxide Fuel Cell (SOFC), Wavelet Network

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