Vapour-compression refrigeration and cooling systems represent a significant share of global electricity consumption, being estimated to account for approximately 10% to 20% of the worldwide electricity demand, which highlights their critical impact on energy efficiency and sustainability. In this context, improving the thermodynamic and exergoeconomic performance of refrigeration cycles, as well as the appropriate selection of the refrigerant, has become a key research priority. Therefore, this work aims to comparatively evaluate the energy, exergy, exergy cost, and exergoeconomic performance of three vapour-compression refrigeration cycle configurations: a simple cycle, a two-stage cycle with a flash tank, and a two-stage cycle with a flash tank and a mixing chamber. Six refrigerants (R134a, R600a, R290, R1234yf, R1234ze (E), and R717) were analysed under evaporation temperatures of 228–238 K and condensation temperatures of 298–308 K. The performance evaluation was carried out using the Fuel–Product–Residue (FPR) methodology, considering the coefficient of performance (COP), exergy efficiency, system irreversibilities, and exergy and exergoeconomic costs. The results indicate that the incorporation of the mixing chamber increases the COP by up to 7% and the exergy efficiency by up to 6% compared to the simple cycle, while reducing exergoeconomic costs by up to 10% for the most favourable refrigerants. Among the working fluids analysed, R600a exhibits the best overall performance (COP up to 4.3 and an exergy efficiency of 33%), followed by R290 and R717, whereas R1234yf shows the lowest efficiencies (COP ≈ 3.7 and exergy efficiency ≈ 28%) and the highest exergoeconomic costs. These findings demonstrate that the design of vapour-compression refrigeration systems should involve the joint selection of the cycle configuration and the refrigerant based on integrated energy, exergy, and exergoeconomic criteria. Overall, the results highlight that both the refrigerant and the cycle configuration must be selected simultaneously, considering energy, exergy, and exergoeconomic criteria, to achieve more efficient and sustainable industrial applications.

Gustavo Alberto Nuñez-Alvarez, Arturo Aguilar Pérez, Armando Gonzalez-Sanchez, Federico Mendez, and Wenceslao Bonilla-Blancas. International Journal of Fuzzy Logic and Intelligent Systems 2025;25:351-63. https://doi.org/10.5391/IJFIS.2025.25.3.351