Enhancing acoustic performance of refrigerator compressors through muffler modeling and optimizing via discharge pressure

Abstract

To enhance the acoustic performance of refrigerator compressors, it is essential to minimize undesirable vibrations and noise emissions. A crucial factor in this endeavor is the optimization of the compressor's gas flow path, focusing on noise generation. This article investigates the enhancement of acoustic performance in compressors through the optimization of muffler designs within the gas flow path. 1D Transfer Matrix Method (TMM) was used to model Transmission Loss (TL) of suction and discharge mufflers, with results validated against Finite Element Method (FEM) simulations. Pressure pulsation data from the discharge line were analyzed using Welch method, which informed the optimization of a two-chamber discharge muffler through custom optimization algorithms: Genetic Algorithm (GA) and Interior Point Method (IPM). These methodologies targeted specific frequencies, while adhering to predefined design constraints. Furthermore, the results of this study provide insights into the interplay between pressure pulsation dynamics and noise emissions, contributing to compressor acoustics-efficient muffler designs. This article evaluates TMM for modelling complex geometries, specifically suction mufflers at low to mid-range frequencies. TMM accurately predicted discharge muffler performance, even at higher frequencies. Optimizations led to significant improvements in acoustic performance, with GA outperforming IPM in both accuracy and efficiency. Experimental validation conducted in a full anechoic room (FAR) confirmed that the optimized muffler design achieved a reduction in overall Sound Power Level (SWL). These optimized designs not only led to a significant decrease in noise but also reinforced the established correlation between pressure pulsations and corresponding acoustic emissions, highlighting advanced modelling and optimization.