Energy-efficiency-oriented Analysis And Control For Vapor Compression Refrigeration Cycle Systems

With the improvement of the global sustainable development strategy and the strengthening of energy conservation and environmental protection consciousness of people,there exists increasing demand on cooling quality and energy saving in modern society.The vapor compression refrigeration cycle(VCC)system is a strong nonlinear system with much interference,thermodynamic coupling characteristics,and wide operating condition.Therefore,the traditional modelling and control approaches may not be suitable to control the VCC system efficiently.Taking the VCC system as the object,the analysis of energy efficiency and controller design are systemically studied in this dissertation.It includes:1)A dynamic model of the VCC system is developed.For the analysis of system energy efficiency,the relationship and influence between the system variables need to be understood first.Therefore,the dissertation firstly models the VCC system.According to the energy conservation,mass balance theroy,and thermodynamic basic properties,with reasonable and effective simplified condition,the major components of the system are modeled respectively: dynamic models are set up for hear exchangers,such as condenser and evaporator;while static models are developed for compressor and expansion valve.Then according to the relationship among them,the whole system model is established.This dynamic model can overcome high order feature which is the traditional shortcoming for modeling of VCC system,reserve the original dynamic behavior of the system,and ensure the accuracy of the model.It also provides the basis for subsequent energy analysis and controller design.2)A novel enhanced-efficiency selection of operating variables for the VCC system is proposed.The influence of different sets of operating variables for the operation stability and system efficiency of the VCC system are analyzed in this dissertation.According to the self-optimizing control(SOC)method,an objective function is proposed to maximize the energy efficiency of the VCC system while meeting with the demand of indoor thermal comfort.Two self-optimizing control methods are applied to determine the optimal individual controlled variables(CVs)and measurement combinations as CVs.the proposed selection of self-optimizing CVs can not only provide the energy efficient control configuration for the VCC system,but also ensure the near-optimal stable operation for all disturbance scenarios.3)A model predictive control based control strategy for the VCC system is proposed to improve the energy efficiency of system.In the proposed control strategy,the compressor speed,opening of expansion valve,and the air mass flow rate of the evaporator are chosen as the system inputs,while the condensing pressure,evaporating pressure,and the superheat degree of evaporator are selected as the system outputs.Based on the system coefficient of performance(COP),the performance index is developed to improve the system efficiency,and the control target of system is achieved by using the rolling optimization technique.Simulation and experimental results show that the proposed control strategy has the advantages of tracking performance and disturbance resistance capability.4)A novel energy-efficiency-oriented cascade control strategy for the VCC system based on model predictive control method is proposed.The architecture is consisted by inner loop and outer loop.Thereinto,the outer loop consists of a nonlinear model which describes the relationship between cooling load and superheat of evaporator and a PI controller to provide the optimal setting values for inner loop depending on the corresponding cooling loads.The inner loop is composed of a simple vapor compression refrigeration cycle system model and MPC controller to to track the setting value of pressure difference and the superheat of the evaporator determined by the outer loop so that minimum energy consumption of VCC system.Experimental results of different cascade control schemes confirm that the proposed control strategy can improve the energy efficiency while meeting changing demands for cooling capacity.