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Simulation Study Of Two-stage Compression Refrigeration System

Posted on:2017-04-29Degree:MasterType:Thesis
Country:ChinaCandidate:S B ZhangFull Text:PDF
GTID:2272330485483587Subject:Refrigeration and Cryogenic Engineering
Abstract/Summary:PDF Full Text Request
Energy saving and environmental protection have gradually become an important theme with modern social progress and economic development. Energy saving and environmental protection of air-conditioning have been a hot topic related to academics, the rapid development of simulation techniques for the study of the refrigeration system provides an opportunity to greatly shorten the development cycle of refrigeration equipment.Combining refrigeration principle with the various components of two-stage compressor refrigeration system for analysis and research, based on some necessary assumptions, adding cooling, heat transfer, thermodynamics and other engineering disciplines of knowledge, and using relevant empirical formula, this paper establishes mathematical models of compressor of high and low temperature, condenser, thermostatic expansion valve, calorimeter, intercooler, charge amount of refrigerant and other parts of the physical parameters. At the same time, using platform of simulink software, the paper sets up simulation model of compressor of high and low temperature, condenser, cooler, thermal expansion valve, calorimeter and others, combines with the organic relationship among them to make up the simulation platform of the two-stage compressor refrigeration system. In order to compare results of simulation with experiment, we build a experimental platform of two-stage compressor refrigeration system to achieve experimental analysis of the system under different conditions, providing the basis for the design of two-stage compressor refrigeration system.Using the method of simulation and experimental validation, the mass flow, input power, exhaust temperature, cooling capacity, COP and other simulation results are compared to get error analysis, and the causes of such errors from a theoretical perspective are discussed. Finally, system simulation platform has been optimized by using of BP neural network, so that the error of simulation results are reduced to about 5%.
Keywords/Search Tags:simulation, two-stage compression, BP neural network, Simulink
PDF Full Text Request
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