Efficiency and Size Optimization of a General Solid Oxide Fuel Cell System
An irreversible model of high temperature solid oxide fuel cells( SOFCs) working at steady-state is developed,devoted to performing the optimization with regard to two objectives:minimization of the fuel cell size and maximization of the system efficiency. The performance characteristics of the syst...
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Published in | 东华大学学报(英文版) Vol. 32; no. 1; pp. 113 - 118 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China%College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
28.02.2015
State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry, Donghua University, Shanghai 201620, China |
Subjects | |
Online Access | Get full text |
ISSN | 1672-5220 |
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Abstract | An irreversible model of high temperature solid oxide fuel cells( SOFCs) working at steady-state is developed,devoted to performing the optimization with regard to two objectives:minimization of the fuel cell size and maximization of the system efficiency. The performance characteristics of the system are analyzed in details, illustrated by the curves of power density,efficiency and voltage. Genetic algorithm is used to perform the multi-objective optimization with four decision variables: the operating pressure, the fuel stoichiometric ratio, the air stoichiometric ratio and the current density. A Pareto set giving a quantative description of the trade-off between the two objectives is used to analyze the results. Optimization results prove the existence of optimal designs region for a 50 kW system with efficiency from 43% corresponding to a 14. 6 m2 electrolyte area to 48% corresponding to a 25.4 m2 electrolyte area. The SOFC model used is general and the optimization results could be applied to the practical SOFC design. |
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AbstractList | An irreversible model of high temperature solid oxide fuel cells( SOFCs) working at steady-state is developed,devoted to performing the optimization with regard to two objectives:minimization of the fuel cell size and maximization of the system efficiency. The performance characteristics of the system are analyzed in details, illustrated by the curves of power density,efficiency and voltage. Genetic algorithm is used to perform the multi-objective optimization with four decision variables: the operating pressure, the fuel stoichiometric ratio, the air stoichiometric ratio and the current density. A Pareto set giving a quantative description of the trade-off between the two objectives is used to analyze the results. Optimization results prove the existence of optimal designs region for a 50 kW system with efficiency from 43% corresponding to a 14. 6 m2 electrolyte area to 48% corresponding to a 25.4 m2 electrolyte area. The SOFC model used is general and the optimization results could be applied to the practical SOFC design. |
Author | 陈鹏 黄跃武 刘思煦 |
AuthorAffiliation | College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China State Environmental Protection Engineering Center.for Pollution Treatment and Control in Textile Industry, Donghua University,Shanghai 201620, China |
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Notes | 31-1920/N CHEN Peng , HUANG Yue-wu , LIU Si-xu ( 1 College of Environmental Science and Engineering, Donghzza UniversiO', Shanghai 201620, China 2 State Environmentol Protection Engineering Center.for Pollution Treatment and Control in Textile Industr3,, Donghua Unigersity, Shanghai 201620, China) solid oxide fuel cell(SOFC) multi-objective optimization efficiency size An irreversible model of high temperature solid oxide fuel cells( SOFCs) working at steady-state is developed,devoted to performing the optimization with regard to two objectives:minimization of the fuel cell size and maximization of the system efficiency. The performance characteristics of the system are analyzed in details, illustrated by the curves of power density,efficiency and voltage. Genetic algorithm is used to perform the multi-objective optimization with four decision variables: the operating pressure, the fuel stoichiometric ratio, the air stoichiometric ratio and the current density. A Pareto set giving a quantative description of the trade-off between the two objectives is used to analyze the results. Optimization results prove the existence of optimal designs region for a 50 kW system with efficiency from 43% corresponding to a 14. 6 m2 electrolyte area to 48% corresponding to a 25.4 m2 electrolyte area. The SOFC model used is general and the optimization results could be applied to the practical SOFC design. |
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Title | Efficiency and Size Optimization of a General Solid Oxide Fuel Cell System |
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