Performance optimization of new generation R290 and R1234yf refrigerants: A response surface methodology approach

Abstract

This study aims to perform the parametric optimization of the R290 and R1234yf refrigerants in vapor compression refrigeration systems by employing the Response surface methodology (RSM) approach to obtain the best operating conditions. The input factors, including evaporator and condenser temperatures, are first determined, ranging from -12 to -4 degrees C and 30 to 40 degrees C, respectively. The objective functions are also identified, including compressor discharge temperature (Tdis), refrigerant mass flow rate (mref), compressor power consumption (Pcomp), and coefficient of performance (COP). Then, the central composite design (CCD) was performed to set out the experimental investigations. Response surface methodology and analysis of variance were utilized to detect the optimal levels and analyze the individual and combined interaction between each pair of input factors. The novelty of this study is in applying the RSM technique to develop second-order regression models and utilizing the desirability function approach for optimizing the refrigeration system. The deviations between the predicted and experimental values for the compressor discharge temperature, refrigerant mass flow rate, compressor power consumption, and COP are 0.256 %, 0.292 %, 0.724 %, and 0.169 %, respectively, representing that this method efficiently optimizes the performance of the R290 refrigerant. Similarly, the deviations between the predicted and experimental values for R1234yf are as follows: 0.272 %, 0.526 %, 0.980 %, and 1.069 %. From our knowledge, there have been very few optimization studies on the thermodynamic performance of refrigerants using the RSM tool, which reduces experimental costs and saves time.