Exergy and exergoeconomic analyses of serial and bypass two-stage compression on the household refrigerator-freezer and replacement of R436A refrigerant

Abstract

In this research, the performance of serial two-stage compression (STC) cycle and bypass two-stage compression (BTC) cycle on the household refrigerator-freezers is tested in the laboratory. Then, based on the results of the experiments, exergy, exergoeconomic analyses, and cycle optimization are carried out. Considering that replacing refrigerants in household refrigerator-freezers is one of the approaches to increase the performance and environmental impact of these systems, R436A refrigerant (46% Isobutene and 54% Propane mixture) is used and analyzed to replace previous refrigerants. Finally, the multi-objective optimization of the mentioned cycles is performed with both refrigerants. For analyses, two models of refrigerator-freezers with different cycles are used (STC cycle with R134a refrigerant and BTC cycle with R-600a refrigerant). In both models, two evaporators for refrigerator-freezer compartments are used. International standards (IEC 62552) are used to test refrigerator-freezers. MATLAB and REFPROP 9.1 software are used to model the systems. According to the results of the analyses, the STC cycle with R436A refrigerant has more total exergy destruction rate (0.727 kW) compared to R134a refrigerant. In the BTC cycle, in which the fresh food compartment (FFC) and freezer compartment (FZC) operate, the total exergy destruction rate with R-600a refrigerant (0.422 kW) is less than with R436A refrigerant. In the case of the BTC cycle in which only the FZC operates, the total exergy destruction rate with R-600a refrigerant (0.455 kW) is less than with R436A refrigerant. The most exergoeconomic factor among cycle equipment is related to the compressor (about 98%). The highest COP value between cycles is related to the STC cycle with R134a refrigerant.

Keywords

Serial circuit bypass circuit household refrigerator-freezer exergy exergoeconomic multi-objective optimization

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