Energy Efficient Predictive Control for Vapor Compression Refrigeration Cycle Systems

被引:0
|
作者
Xiaohong Yin [1 ]
Shaoyuan Li [2 ]
机构
[1] the School of Automation and Electronic Engineering,Qingdao University of Science and Technology
[2] the Department of Automation, Shanghai Jiao Tong University, and the Key Laboratory of System Control and Information Processing, Ministry of Education of China
基金
新加坡国家研究基金会; 中国国家自然科学基金;
关键词
Cooling load; model predictive control(MPC); superheat; vapor compression refrigeration cycle(VCC);
D O I
暂无
中图分类号
TB614 [];
学科分类号
摘要
Vapor compression refrigeration cycle(VCC) system is a high dimensional coupling thermodynamic system for which the controller design is a great challenge. In this paper, a model predictive control based energy efficient control strategy which aims at maximizing the system efficiency is proposed. Firstly,according to the mass and energy conservation law, an analysis on the nonlinear relationship between superheat and cooling load is carried out, which can produce the maximal effect on the system performance. Then a model predictive control(MPC)based controller is developed for tracking the calculated setting curve of superheat degree and pressure difference based on model identified from data which can be obtained from an experimental rig. The proposed control strategy maximizes the coefficient of performance(COP) which depends on operating conditions, in the meantime, it meets the changing demands of cooling capacity.The effectiveness of the control performance is validated on the experimental rig.
引用
收藏
页码:953 / 960
页数:8
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