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ACRC Technical Report 244PDF

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Title:Dynamic Modeling and Advanced Control of Air Conditioning and Refrigeration Systems
Author(s):Rasmussen, Bryan P.; Alleyne, Andrew G.
Subject(s):vapor compressor systems
Abstract:Over 15 billion dollars is spent on energy for residential air-conditioning alone each year, and air conditioning remains the largest source of peak electrical demand. Improving the efficiency of these systems has the potential for significant economic and environmental impact, but requires not only refining individual component designs, but increasing overall system efficiency using advanced control strategies. Transient control of vapor compression cycles faces two significant challenges: 1) creating control-oriented models that balance simplicity with accuracy, and capture the complex heat and mass flow dynamics, and 2) developing control strategies that can achieve high performance over a wide range of operating conditions. This dissertation makes contributions on both fronts and can be divided into two distinct parts. The first portion of the dissertation presents the development, simulation, and experimental validation of a first principles modeling framework that captures the dynamics of a variety of vapor compression cycles in a form amenable to controller design. These models are highly nonlinear, and require a nonlinear control strategy to attain high performance over the entire operating envelope. To this end, a gain-scheduled control approach based on local models and local controllers is presented that uses endogenous scheduling variables. This comprises the second portion of the dissertation, where a theoretical framework for designing gain scheduled controllers, tools for analyzing the stability of the nonlinear closed loop system, and experimental evaluation of advanced control strategies for vapor compression systems is presented. These results demonstrate that while linear control techniques offer significant advantages versus traditional a/c control systems over small ranges, the gain-scheduled approach extends these advantages over the entire operating regime.
Issue Date:2006-06
Publisher:Air Conditioning and Refrigeration Center. College of Engineering. University of Illinois at Urbana-Champaign.
Series/Report:Air Conditioning and Refrigeration Center TR-244
Genre:Technical Report
Type:Text
Language:English
URI:http://hdl.handle.net/2142/12355
Sponsor:Air Conditioning and Refrigeration Project 163
Date Available in IDEALS:2009-06-22


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