Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYin, Xiaohongen
dc.contributor.authorLi, Shaoyuanen
dc.contributor.authorCai, Wenjianen
dc.identifier.citationYin, X., Li, S., & Cai, W. (2015). Enhanced-efficiency operating variables selection for vapor compression refrigeration cycle system. Computers and Chemical Engineering, 80, 1-14.en
dc.description.abstractIn this paper, a novel enhanced-efficiency selection of operating variables based on self-optimizing control (SOC) method for the vapor compression refrigeration cycle (VCC) system is proposed. An objective function is proposed to maximize the energy efficiency of the VCC system while meeting with the demand of indoor thermal comfort. With the detailed analysis of operating variables, three unconstrained degrees of freedom are selected among all the candidate operating variables. Then two SOC methods are applied to determine the optimal individual controlled variables (CVs) and measurement combinations as CVs. The model predictive control (MPC) method based controllers and PID controllers are designed for different sets of CVs, and the experimental results indicate that the proposed selection of CVs can achieve a good trade-off between optimal (or near optimal) stable operation and enhanced-efficiency of the synthesized control structure.en
dc.format.extent44 p.en
dc.relation.ispartofseriesComputers and chemical engineeringen
dc.rights© 2015 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Computers and Chemical Engineering, Elsevier Ltd. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [].en
dc.subjectDRNTU::Engineering::Computer science and engineeringen
dc.titleEnhanced-efficiency operating variables selection for vapor compression refrigeration cycle systemen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.description.versionAccepted versionen
item.fulltextWith Fulltext-
Appears in Collections:EEE Journal Articles

Citations 20

Updated on Jul 18, 2024

Web of ScienceTM
Citations 20

Updated on Oct 27, 2023

Page view(s) 50

Updated on Jul 20, 2024

Download(s) 20

Updated on Jul 20, 2024

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.