Parameter Estimation and Dynamic State Observer Design for Vapor Compression Systems

Abstract

Between cooling our house, our workplace, and keeping our food cold both in home and commercially (among other uses), the vapor compression cycle (VCC) is a common method for removing heat from various environments and it accounts for a significant amount of the energy used throughout the world. Therefore, with an evergrowing demand for more efficient processes and reduced energy consumption, improving the ability to accurately model, predict the performance of, and control VCC systems is beneficial to society as whole. While there is much information available regarding the performance for some of the components found in VCC systems, much of the challenge associated with modelling the VCC lies within the complex behavior of the heat exchangers found within the system. Over the years, lumped parameter models have been developed for the VCC. However, many of these rely on simplified geometry (mainly a bare tube assumption), and neglect to capture the effect of the fins found throughout those heat exchangers. This thesis builds upon approaches used in the past by identifying effective heat transfer coefficients that capture this effect. Using this approach, a 2-ton residential airconditioning unit was modelled, which was able to predict the heat removed by the VCC system within ±4% error when compared to published performance data from the manufacturer. Furthermore, these coefficients, along with the complete dynamic model, form the basis of a nonlinear state observer which can be used to further the ability to accurately predict and monitor system performance. vi TABLE OF CONTENTS