Transient analysis of a solid oxide fuel cell unit with reforming and water-shift reaction and the building of neural network model for rapid prediction in electrical and thermal performance

被引:10
|
作者
Yuan, Ping [1 ]
Liu, Syu-Fang [1 ]
机构
[1] Lee Ming Inst Technol, Dept Mech Engn, Taipei, Taiwan
关键词
Transient; Solid oxide fuel cell; Reforming; Water-shift; Neural network model; GAS SHIFT; NUMERICAL-ANALYSIS; DYNAMIC-MODEL; SOFC; PLANAR; ANODE; METHANE; TEMPERATURE; KINETICS; SINGLE;
D O I
10.1016/j.ijhydene.2019.10.165
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
This study investigates the effect of reforming reaction, water-shift reaction, and operating parameters on the transient performance of a solid oxide fuel cell unit, because the transient analysis is necessary and helpful for the applications of a SOFC with cross-flow configuration. The primary results show that all properties approach the steady state at similar time except the cell temperature. The reforming and water-shift reaction obviously promote the average current density by 5%, and lower the maximum cell temperature by 20 K. The molar flow rate variation deduces about 15 K difference of maximum cell temperature. The effect of inlet temperature and operating voltage on the average current density and maximum cell temperature is more obvious than the molar flow rate effect. Moreover, this study builds a neural network model to predict the steady average current density and maximum cell temperature rapidly and correctly, which is helpful for the control of a SOFC. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:924 / 936
页数:13
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