Experimental and numerical analysis of a carbon dioxide chiller

The increasing demand for environmentally friendly refrigeration systems has led to the adoption of natural refrigerants such as carbon dioxide (CO₂) due to their low global warming potential (GWP) and favourable thermophysical properties. This thesis aims to support the development of a small air-to-water chiller for light applications, operating under transcritical conditions with CO₂ as the working fluid. The analysed system is a transcritical CO₂ refrigeration cycle consisting of a hermetic rotary compressor (Toshiba DY67L1F-10FU), a finned-tube gas cooler, a SWEP B18 brazed-plate evaporator, a Frigomac receiver, a SWEP B18 regenerator (reduced plates), and an electronic back-pressure valve. The objective is to evaluate the performance and refrigerant charge distribution of the system by combining MATLAB-Simulink modelling with experimental validation. Laboratory tests were conducted at Hiref S.p.A. under fixed conditions (compressor input 1.4 kW, High pressure approximately 75 bar, water inlet 19.9 °C at 1350 L/h, and air inlet 20 °C). The simulation model incorporated thermodynamic property calls from REFPROP and detailed component sub-models. Validation showed strong agreement between simulation and experiment: the deviation was below 1.2% for gas cooler outlet pressure, below 3% for evaporation pressure, and within 5% for cooling capacity. The total calculated charge (3.644 kg) aligns well with the estimated experimental filling value of about 4 kg. The main findings are that the developed MATLAB-Simulink framework can accurately reproduce both the thermodynamic behaviour and refrigerant inventory of a transcritical CO₂ chiller. The charge analysis revealed that the gas cooler and evaporator dominate the refrigerant distribution, while the regenerator and receiver have minor contributions. These results confirm the feasibility of small CO₂ chillers for light applications, providing both a validated modelling tool and design insights for future system optimization.