Geometry optimization and pressure analysis of a proton exchange membrane fuel cell stack

被引:0
|
作者
Chen, Wei-Hsin [1 ,2 ,3 ]
Tsai, Zong-Lin [1 ,4 ]
Chang, Min-Hsing [5 ]
You, Siming [6 ]
Kuo, Pei-Chi [7 ]
机构
[1] Natl Cheng Kung Univ, Dept Aeronaut & Astronaut, Tainan 701, Taiwan
[2] Tunghai Univ, Res Ctr Smart Sustainable Circular Econ, Taichung 407, Taiwan
[3] Natl Chin Yi Univ Technol, Dept Mech Engn, Taichung 411, Taiwan
[4] Natl Cheng Kung Univ, Int Master Degree Program Energy Engn, Tainan 701, Taiwan
[5] Tatung Univ, Dept Mech Engn, Taipei 104, Taiwan
[6] Univ Glasgow, James Watt Sch Engn, Glasgow G12 8QQ, Lanark, Scotland
[7] Ind Technol Res Inst, Green Energy & Environm Res Labs, Tainan 711, Taiwan
关键词
Fuel cell stack; Pressure uniformity; Taguchi method; Analysis of variance (ANOVA); Neural network (NN); Multivariate adaptive regression; splines (MARS); ADAPTIVE REGRESSION SPLINES; ARTIFICIAL NEURAL-NETWORKS; TAGUCHI METHOD; PERFORMANCE; FLOW; PEMFC; TEMPERATURE; DESIGN; MODEL; PARAMETERS;
D O I
10.1016/j.ijhydene.2021.01.222
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
For proton exchange membrane fuel cells (PEMFCs), the distribution of reactant streams in the reactor is critical to their efficiency. This study aims to investigate the optimal design of the inlet/outlet flow channel in the fuel cell stack with different geometric dimensions of the tube and intermediate zones (IZ). The tube-to-IZ length ratio, the IZ width, and the tube diameter are adjusted to optimize the geometric dimensions for the highest pressure uniformity. Four different methods, including the Taguchi method, analysis of variance (ANOVA), neural network (NN), and multiple adaptive regression splines (MARS), are used in the analyses. The results indicate the tube diameter is the most impactive one among the three factors to improve the pressure uniformity. The analysis suggests that the optimal geometric design is the tube-to-IZ length ratio of 9, the IZ width of 14 mm, and the tube diameter of 9 mm with the pressure uniformity of 0.529. The relative errors of the predicted pressure uniformity values by NN and MARS under the optimal design are 1.62% and 3.89%, respectively. This reveals that NN and MARS can accurately predict the pressure uniformity, and are promising tools for the design of PEMFCs. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:16717 / 16733
页数:17
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