Thermo-economical sensitivity analysis of a linear compressor. (October 2022)

• Record Type: Journal Article
• Authors: Mastrullo, R.; Mauro, A.W.; Napoli, G.; Strano, S.; Viscito, L.
• Is Part Of: International journal of refrigeration. Volume 142(2022)
• Page Start: 82
• Page End: 91
• Publication Date: 2022-10
• Subjects: Linear compressor -- Sensitivity analysis -- Geometrical optimization -- Thermo-economic modeling; Compresseur linéaire -- Analyse de sensibilité -- Optimisation géométrique -- Modélisation thermo-économique; Refrigeration and refrigerating machinery -- Periodicals; 621.56
• DOI: 10.1016/j.ijrefrig.2022.06.015
• Languages: English
• ISSNs: 0140-7007

Abstract

Highlights: Sensitivity analysis and optimization of a linear compressor for domestic use. Efficiency decreases with friction coefficient, stroke and spring eccentricity. Efficiency increases with piston and suction valve diameters. Linear compressor cost mainly affected by piston diameter and stroke. Possibility for lower cost and higher efficiency than conventional technologies. Abstract: The linear compressor is a new kind of reciprocating compressor in which the reciprocating motion is provided by means of a linear motor that replaces the crank mechanism, allowing a reduction in friction, oil-free operation and a continuous control of the cooling capacity without ON/OFF operations. A detailed compressor model has been implemented with the purpose to design a compressor for household refrigerators, using R600a as working fluid and having a cooling power of 200 W. Geometrical and design parameters have been identified, and a sensitivity analysis is carried out to quantify the influence of each parameter on the compressor global and volumetric efficiencies, and costs. All the simulated solutions have been then compared, in terms of global efficiency and costs, to the traditional reciprocating and the linear compressors currently available on the market. It is shown that this technology has generally a higher efficiency but also higher costs. However, a careful design of all the influencing parameters could lead to significant improvements for both objective functions.