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

页码：357 / 371

页数：15

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