Abstract--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 ...Abstract--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. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.展开更多
By means of the Second Law of Thermodynamics,thispaper gives out the entropy analysis method for vapor-comperession refrigeration system.The thermal irrevers-ibility of the system charged with R12 and its hopeful al-t...By means of the Second Law of Thermodynamics,thispaper gives out the entropy analysis method for vapor-comperession refrigeration system.The thermal irrevers-ibility of the system charged with R12 and its hopeful al-ternative refrlgerant R134a have been studied respective-ly.On the basis of all the research results of this paper,the measure used to save energy for vapor-compressionrefrigeration system has been put out.展开更多
The airborne high power electrical equipments have been widely used in modern aircrafts , which consequently causes the dramatic increase of heating load up to dozens of kilowatts.Accordingly , vapor-compression refri...The airborne high power electrical equipments have been widely used in modern aircrafts , which consequently causes the dramatic increase of heating load up to dozens of kilowatts.Accordingly , vapor-compression refrigeration system ( VCRS ) with lower engine bleed air and larger refrigeration capacity has been paid much attention in recent years.Therefore , based on the analysis of the characteristics of VCRS , an experiment system of VCRS using R134ais set up to simulate operation performances.The influences of different parameters including evaporation pressure , condensing pressure , refrigerant mass flow rate and compressor rotation speed are also investigated.The impacts of different parameters on the system performance are various.This work can help to establish the specific control law under different work conditions.展开更多
High power dissipating artificial intelligence (AI) chips require significant cooling to operate at maximum performance. Current trends regarding the integration of AI, as well as the power/cooling demands of high-per...High power dissipating artificial intelligence (AI) chips require significant cooling to operate at maximum performance. Current trends regarding the integration of AI, as well as the power/cooling demands of high-performing server systems pose an immense thermal challenge for cooling. The use of refrigerants as a direct-to-chip cooling method is investigated as a potential cooling solution for cooling AI chips. Using a vapor compression refrigeration system (VCRS), the coolant temperature will be sub-ambient thereby increasing the total cooling capacity. Coupled with the implementation of a direct-to-chip boiler, using refrigerants to cool AI server systems can materialize as a potential solution for current AI server cooling demands. In this study, a comparison of 8 different refrigerants: R-134a, R-153a, R-717, R-508B, R-22, R-12, R-410a, and R-1234yf is analyzed for optimal performance. A control theoretical VCRS model is created to assess variable refrigerants under the same operational conditions. From this model, the coefficient of performance (COP), required mass flow rate of refrigerant, work required by the compressor, and overall heat transfer coefficient is determined for all 8 refrigerants. Lastly, a comprehensive analysis is provided to determine the most optimal refrigerants for cooling applications. R-717, commonly known as Ammonia, was found to have the highest COP value thus proving to be the optimal refrigerant for cooling AI chips and high-performing server applications.展开更多
A novel power and cooling system combined system which coupled organic Rankine cycle(ORC) with vapor compression refrigeration cycle(VCRC) was proposed. R245 fa and butane were selected as the working fluid for the po...A novel power and cooling system combined system which coupled organic Rankine cycle(ORC) with vapor compression refrigeration cycle(VCRC) was proposed. R245 fa and butane were selected as the working fluid for the power and refrigeration cycle, respectively. A performance comparison and analysis for the combined system was presented. The results show that dual-pressure ORC-VCRC system can achieve an increase of 7.1% in thermal efficiency and 6.7% in exergy efficiency than that of basic ORC-VCRC. Intermediate pressure is a key parameter to both net power and exergy efficiency of dual-pressure ORC-VCRC system. Combined system can produce maximum net power and exergy efficiency at 0.85 MPa for intermediate pressure and 2.4 MPa for high pressure, respectively. However, superheated temperature at expander inlet has little impact on the two indicators. It can achieve higher overall COP, net power and exergy efficiency at smaller difference between condensation temperature and evaporation temperature of VCRC.展开更多
A model predictive controller based on a novel structure selection criterion for the vapor compression cycle （VCC） of refrigeration process is proposed in this paper. Firstly, those system variables are analyzed whi...A model predictive controller based on a novel structure selection criterion for the vapor compression cycle （VCC） of refrigeration process is proposed in this paper. Firstly, those system variables are analyzed which exert significant influences on the system performance. Then the structure selection criterion, a trade-off between computation complexity and model performance, is applied to different model structures, and the results are utilized to determine the optimized model structure for controller design. The controller based on multivariable model predictive control （MPC） strategy is designed, and the optimization problem for the reduced order models is formulated as a constrained minimization problem. The effectiveness of the proposed MPC controller is verified on the experimental rig.展开更多
基金supported by the National Natural Science Foundation of China(61233004,61221003,61374109,61473184,61703223,61703238)the National Basic Research Program of China(973 Program)(2013CB035500)+1 种基金Shandong Provincial Natural Science Foundation of China(ZR2017BF014,ZR2017MF017)the National Research Foundation of Singapore(NRF-2011,NRF-CRP001-090)
文摘Abstract--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. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.
文摘By means of the Second Law of Thermodynamics,thispaper gives out the entropy analysis method for vapor-comperession refrigeration system.The thermal irrevers-ibility of the system charged with R12 and its hopeful al-ternative refrlgerant R134a have been studied respective-ly.On the basis of all the research results of this paper,the measure used to save energy for vapor-compressionrefrigeration system has been put out.
文摘The airborne high power electrical equipments have been widely used in modern aircrafts , which consequently causes the dramatic increase of heating load up to dozens of kilowatts.Accordingly , vapor-compression refrigeration system ( VCRS ) with lower engine bleed air and larger refrigeration capacity has been paid much attention in recent years.Therefore , based on the analysis of the characteristics of VCRS , an experiment system of VCRS using R134ais set up to simulate operation performances.The influences of different parameters including evaporation pressure , condensing pressure , refrigerant mass flow rate and compressor rotation speed are also investigated.The impacts of different parameters on the system performance are various.This work can help to establish the specific control law under different work conditions.
文摘High power dissipating artificial intelligence (AI) chips require significant cooling to operate at maximum performance. Current trends regarding the integration of AI, as well as the power/cooling demands of high-performing server systems pose an immense thermal challenge for cooling. The use of refrigerants as a direct-to-chip cooling method is investigated as a potential cooling solution for cooling AI chips. Using a vapor compression refrigeration system (VCRS), the coolant temperature will be sub-ambient thereby increasing the total cooling capacity. Coupled with the implementation of a direct-to-chip boiler, using refrigerants to cool AI server systems can materialize as a potential solution for current AI server cooling demands. In this study, a comparison of 8 different refrigerants: R-134a, R-153a, R-717, R-508B, R-22, R-12, R-410a, and R-1234yf is analyzed for optimal performance. A control theoretical VCRS model is created to assess variable refrigerants under the same operational conditions. From this model, the coefficient of performance (COP), required mass flow rate of refrigerant, work required by the compressor, and overall heat transfer coefficient is determined for all 8 refrigerants. Lastly, a comprehensive analysis is provided to determine the most optimal refrigerants for cooling applications. R-717, commonly known as Ammonia, was found to have the highest COP value thus proving to be the optimal refrigerant for cooling AI chips and high-performing server applications.
基金Project(12C0379)supported by the Scientific Research Fund of Hunan Province,ChinaProject(13QDZ04)supported by the Scientific Research Foundation for Doctors of Xiangtan University,China
文摘A novel power and cooling system combined system which coupled organic Rankine cycle(ORC) with vapor compression refrigeration cycle(VCRC) was proposed. R245 fa and butane were selected as the working fluid for the power and refrigeration cycle, respectively. A performance comparison and analysis for the combined system was presented. The results show that dual-pressure ORC-VCRC system can achieve an increase of 7.1% in thermal efficiency and 6.7% in exergy efficiency than that of basic ORC-VCRC. Intermediate pressure is a key parameter to both net power and exergy efficiency of dual-pressure ORC-VCRC system. Combined system can produce maximum net power and exergy efficiency at 0.85 MPa for intermediate pressure and 2.4 MPa for high pressure, respectively. However, superheated temperature at expander inlet has little impact on the two indicators. It can achieve higher overall COP, net power and exergy efficiency at smaller difference between condensation temperature and evaporation temperature of VCRC.
基金supported by National Natural Science Foundation of China (Nos. 61233004, 61221003, 61374109 and 61473184)National Basic Research Program of China (973 Program)(No. 2013CB035500)+1 种基金partly sponsored by the Higher Education Research Fund for the Doctoral Program of China (No. 20120073130006)National Research Foundation of Singapore (No. NRF2011 NRF-CRP001-090)
文摘A model predictive controller based on a novel structure selection criterion for the vapor compression cycle （VCC） of refrigeration process is proposed in this paper. Firstly, those system variables are analyzed which exert significant influences on the system performance. Then the structure selection criterion, a trade-off between computation complexity and model performance, is applied to different model structures, and the results are utilized to determine the optimized model structure for controller design. The controller based on multivariable model predictive control （MPC） strategy is designed, and the optimization problem for the reduced order models is formulated as a constrained minimization problem. The effectiveness of the proposed MPC controller is verified on the experimental rig.
