Multi-objective optimization on multi-layer configuration of cathode electrode for polymer electrolyte fuel cells via computational-intelligence-aided design and engineering framework

Yi Chen; Bei Peng

doi:10.1016/j.asoc.2016.02.045

Multi-objective optimization on multi-layer configuration of cathode electrode for polymer electrolyte fuel cells via computational-intelligence-aided design and engineering framework

Yi Chen, Bei Peng

Research output: Contribution to journal › Article

Abstract

Polymer electrolyte fuel cells (PEFCs) have attracted considerable interest within the research community due to the increasing demands for renewable energy. Within the PEFCs' many components, a cathode electrode plays a primary function in the operation of the cell. Here, a computational-intelligence-aided design and engineering (CIAD/CIAE) framework with potential cross-disciplinary applications is proposed to minimize the over-potential difference η and improve the overall efficiency of PEFCs. A newly developed swarm dolphin algorithm is embedded in a computational-intelligence-integrated solver to optimize a triple-layer cathode electrode model. The simulation results demonstrate the potential application of the proposed CIAD/CIAE framework in the design automation and optimization of PEFCs.

Original language	English
Pages (from-to)	357-371
Number of pages	15
Journal	Applied Soft Computing
Volume	43
Early online date	27 Feb 2016
DOIs	https://doi.org/10.1016/j.asoc.2016.02.045
Publication status	Published - Jun 2016

Keywords

CIAD
CIAE
polymer electrolyte fuel cells

Documents and Links

10.1016/j.asoc.2016.02.045

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Chen, Y., & Peng, B. (2016). Multi-objective optimization on multi-layer configuration of cathode electrode for polymer electrolyte fuel cells via computational-intelligence-aided design and engineering framework. Applied Soft Computing, 43, 357-371. https://doi.org/10.1016/j.asoc.2016.02.045

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abstract = "Polymer electrolyte fuel cells (PEFCs) have attracted considerable interest within the research community due to the increasing demands for renewable energy. Within the PEFCs' many components, a cathode electrode plays a primary function in the operation of the cell. Here, a computational-intelligence-aided design and engineering (CIAD/CIAE) framework with potential cross-disciplinary applications is proposed to minimize the over-potential difference η and improve the overall efficiency of PEFCs. A newly developed swarm dolphin algorithm is embedded in a computational-intelligence-integrated solver to optimize a triple-layer cathode electrode model. The simulation results demonstrate the potential application of the proposed CIAD/CIAE framework in the design automation and optimization of PEFCs.",

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AB - Polymer electrolyte fuel cells (PEFCs) have attracted considerable interest within the research community due to the increasing demands for renewable energy. Within the PEFCs' many components, a cathode electrode plays a primary function in the operation of the cell. Here, a computational-intelligence-aided design and engineering (CIAD/CIAE) framework with potential cross-disciplinary applications is proposed to minimize the over-potential difference η and improve the overall efficiency of PEFCs. A newly developed swarm dolphin algorithm is embedded in a computational-intelligence-integrated solver to optimize a triple-layer cathode electrode model. The simulation results demonstrate the potential application of the proposed CIAD/CIAE framework in the design automation and optimization of PEFCs.

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