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首页> 外文期刊>Applied Soft Computing >Multi-objective optimization on multi-layer configuration of cathode electrode for polymer electrolyte fuel cells via computational-intelligence-aided design and engineering framework
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Multi-objective optimization on multi-layer configuration of cathode electrode for polymer electrolyte fuel cells via computational-intelligence-aided design and engineering framework

机译:基于计算智能设计与工程框架的高分子电解质燃料电池阴极多层结构多目标优化

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摘要

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 eta 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. (C) 2016 Elsevier B.V. All rights reserved.
机译:由于对可再生能源的需求不断增加,聚合物电解质燃料电池(PEFC)在研究界引起了相当大的兴趣。在PEFC的许多组件中,阴极在电池操作中起主要作用。在此,提出了一种具有潜在跨学科应用程序的计算智能辅助设计与工程(CIAD / CIAE)框架,以最大程度地减小过电位差eta并提高PEFC的整体效率。将新开发的群海豚算法嵌入到计算智能集成的求解器中,以优化三层阴极电极模型。仿真结果证明了所建议的CIAD / CIAE框架在PEFC的设计自动化和优化中的潜在应用。 (C)2016 Elsevier B.V.保留所有权利。

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