A novel approach to improve the mathematical modelling of the internal reforming process for solid oxide fuel cells using the orthogonal least squares method

被引：22

作者：

Sciazko, Anna ^{[1
,2
]}

Komatsu, Yosuke ^{[2
]}

Brias, Grzegorz ^{[1
]}

Kimijima, Shinji ^{[3
]}

Szmyd, Janusz S. ^{[1
]}

机构：

[1] AGH Univ Sci & Technol, Fac Energy & Fuels, Dept Fundamental Res Energy Engn, PL-30059 Krakow, Poland

[2] Shibaura Inst Technol, Grad Sch Engn & Sci, Div Reg Environm Syst, Minuma Ku, Saitama 3378570, Japan

[3] Shibaura Inst Technol, Coll Syst Engn & Sci, Dept Machinery & Control Syst, Minuma Ku, Saitama 3378570, Japan

来源：

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2014年 / 39卷 / 29期

关键词：

Methane/steam reforming; Generalized least squares method; Uncertainty analysis; Reaction kinetics; Solid oxide fuel cells; MASS-TRANSFER PROCESSES; NUMERICAL-ANALYSIS; HEAT-TRANSFER; METHANE; KINETICS; NI/YSZ; ANODE; GAS; SOFC; CH4;

D O I：

10.1016/j.ijhydene.2014.07.130

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 paper presents a novel approach to experimental and numerical investigations of the methane/steam reforming reaction process over a nickel/yttria-stabilized zirconia fine powder catalyst. Methane/steam reforming is primarily considered as a hydrogen production process for Solid Oxide Fuel Cells, and therefore its reaction kinetic was investigated experimentally and numerically. The present paper describes the innovative implementation of an orthogonal least squares (generalized least squares: GLS) algorithm for the calculation of the reaction kinetics involving precise information and the uncertainties of the obtained results. The GLS method was applied to evaluate the reaction rate and therefore fractional conversion of methane. An analysis of the mathematical model points out that the experimental inaccuracy could be reduced and allowed for the calculation of the most probable values of kinetic parameters and their uncertainties. The GLS method secures a higher accuracy of measured data and estimates the most probable value of all model parameters. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

引用

页码：16372 / 16389

页数：18