机构:
Aston Univ, Sch Engn & Appl Sci, Mech Engn & Design, Aston Triangle, Birmingham B4 7ET, W Midlands, England
Univ Sharjah, Dept Sustainable & Renewable Energy Engn, POB 27272, Sharjah, U Arab EmiratesAston Univ, Sch Engn & Appl Sci, Mech Engn & Design, Aston Triangle, Birmingham B4 7ET, W Midlands, England
Olabi, Abdul Ghani
[1
,4
]
机构:
[1] Aston Univ, Sch Engn & Appl Sci, Mech Engn & Design, Aston Triangle, Birmingham B4 7ET, W Midlands, England
[2] Univ West Scotland, Inst Engn & Energy Technol, Glasgow G72 0LH, Lanark, Scotland
bipolar plate material;
fuel consumption;
machine learning;
fuel cell;
WATER MANAGEMENT;
FLOW CHANNEL;
METAL FOAMS;
HUMIDIFICATION;
ALGORITHMS;
SIMULATION;
GASES;
D O I:
10.3390/en15051886
中图分类号:
TE [石油、天然气工业];
TK [能源与动力工程];
学科分类号:
0807 ;
0820 ;
摘要:
Commercialization of proton exchange membrane fuel cells can only materials provided its performance is closely related to existing technologies useful in commercial application. Other critical parameters like the utilization of cheaper materials should be taken into account during the manufacturing of the cell. A key component in the cell that has direct correlation to the cell performance is the flow plate. The weight coupled with cost of the cell revolves around the flow plate used in the manufacturing of the cell. This study explores materials ideal for the manufacturing of fuel cells in order to improve the overall cell performance. The investigation highlights the critical impact of varying materials used in the manufacturing of flow plates for PEM fuel cells. Stainless steel (SS), aluminium (Al) and copper (Cu) were the materials considered. The flow plate designs considered were serpentine and open pore cellular foam channel. Machine learning using python for the validation of the results with Linear regression, Ridge regression and Polynomial regression algorithm was carried out. The performance of both flow field channels was compared using different bipolar plate materials. The results show that metal foam flow channels overall performance was better than serpentine flow channels with all the various bipolar plate material used and Al material outperformed Cu and SS material. There is a direct correlation in terms of the outcome of the study and literature based on the data generated experimentally. It can however be concluded that molecules of hydrogen are stable on aluminium plates compared to copper and stainless steel.
机构:
Univ Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USAUniv Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USA
Awin, Yussef
;
Dukhan, Nihad
论文数: 0引用数: 0
h-index: 0
机构:
Univ Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USAUniv Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USA
机构:
Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
Univ Penn, Perelman Sch Med, Dept Psychiat, Philadelphia, PA 19104 USABeijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
Cui, Zaixu
;
Gong, Gaolang
论文数: 0引用数: 0
h-index: 0
机构:
Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
Beijing Normal Univ, Beijing Key Lab Brain Imaging & Connect, Beijing 100875, Peoples R ChinaBeijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
机构:
Univ Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USAUniv Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USA
Awin, Yussef
;
Dukhan, Nihad
论文数: 0引用数: 0
h-index: 0
机构:
Univ Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USAUniv Detroit Mercy, Dept Mech Engn, 4001 W McNichols Rd, Detroit, MI 48221 USA
机构:
Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
Univ Penn, Perelman Sch Med, Dept Psychiat, Philadelphia, PA 19104 USABeijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
Cui, Zaixu
;
Gong, Gaolang
论文数: 0引用数: 0
h-index: 0
机构:
Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
Beijing Normal Univ, Beijing Key Lab Brain Imaging & Connect, Beijing 100875, Peoples R ChinaBeijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China