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

被引：13
|
作者：
Chen, Yi [1 ,2 ]
Peng, Bei [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Mechatron Engn, Chengdu 611731, Peoples R China
[2] Glasgow Caledonian Univ, Sch Engn & Built Environm, Glasgow G4 0BA, Lanark, Scotland
来源：
APPLIED SOFT COMPUTING | 2016年 / 43卷
基金：
中国国家自然科学基金;
关键词：
Fuel cell; Cathode electrode; CIAD; CIAE; Swarm dolphin algorithm; PARAMETER SENSITIVITY EXAMINATION; CATALYST LAYER; PERFORMANCE; VALIDATION; SIMULATION; MODEL; PREDICTION;
D O I：
10.1016/j.asoc.2016.02.045
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码：357 / 371
页数：15
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