A Streamlined Polynomial Regression-Based Modeling of Speed-Driven Hermetic-Reciprocating Compressors

Abstract

This study presents a streamlined and accurate approach for modeling the performance of hermetic reciprocating compressors under variable-speed conditions. Traditional compressor models often neglect the influence of motor frequency, leading to considerable deviations at low-speed operation. To address these limitations, a frequency-dependent numerical framework was developed using one-dimensional (1-D) and two-dimensional (2-D) polynomial regressions to represent volumetric efficiency (ηv) and isentropic efficiency (ηisentr) as functions of compression ratio (r) and motor speed frequency (f). The proposed model integrates manufacturer data and thermodynamic property databases to predict compressor behavior across a wide range of operating conditions. Validation using the Bitzer 4HTE-20K CO2 compressor demonstrated strong agreement with experimental data, maintaining prediction errors within ±10% for both power input and discharge temperature. Moreover, the model enhanced accuracy by up to 19.4% in the low-frequency range below 40 Hz, where conventional models typically fail. The proposed method provides a practical and computationally efficient tool for accurately simulating the performance of hermetic reciprocating compressors that support improved design, optimization, and control of refrigeration and heat pump systems.