Experimental Analysis of Different Refrigerants’ Thermal Behavior and Predicting Their Performance Parameters

Abstract

This study experimentally compares thermodynamic performance of R290 and R404A refrigerants in a refrigeration system. In the first part of the paper, energy analysis of the refrigeration system was performed at various evaporator and condenser temperatures. Results revealed that R404A refrigerant caused an 18.6% increase in compressor power consumption. The highest coefficient of performance values in the system for R290 and R404A were 3.99 and 3.21, respectively. The second part of the paper includes artificial intelligence prediction studies. The pace and elastic net regression models were used to predict performance parameters. A single equation that can predict the cooling capacity and compressor power consumption of R290 and R404A simultaneously was derived. For the cooling capacity, pace regression showed mean absolute error of 0.0252 and root-mean-squared error of 0.0334, while elastic net regression indicated mean absolute error of 0.1103 and root-mean-squared error of 0.1262. It was concluded that R290 had better thermodynamic performance than R404A and the equations obtained with artificial intelligence were applicable to predict the experimental findings, regardless of which refrigerant gas was used.