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Parameter Estimation of Dynamic Air-conditioning Component Models Using Limited Sensor Data

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dc.contributor.advisor Rasmussen, Bryan en_US
dc.creator Hariharan, Natarajkumar en_US
dc.date.accessioned 2011-08-08T22:48:20Z en_US
dc.date.accessioned 2011-08-09T01:28:06Z
dc.date.available 2011-08-08T22:48:20Z en_US
dc.date.available 2011-08-09T01:28:06Z
dc.date.created 2010-05 en_US
dc.date.issued 2011-08-08 en_US
dc.date.submitted May 2010 en_US
dc.identifier.uri http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-8032 en_US
dc.description.abstract This thesis presents an approach for identifying critical model parameters in dynamic air-conditioning systems using limited sensor information. The expansion valve model and the compressor model parameters play a crucial role in the system model's accuracy. In the past, these parameters have been estimated using a mass flow meter; however, this is an expensive devise and at times, impractical. In response to these constraints, a novel method to estimate the unknown parameters of the expansion valve model and the compressor model is developed. A gray box model obtained by augmenting the expansion valve model, the evaporator model, and the compressor model is used. Two numerical search algorithms, nonlinear least squares and Simplex search, are used to estimate the parameters of the expansion valve model and the compressor model. This parameter estimation is done by minimizing the error between the model output and the experimental systems output. Results demonstrate that the nonlinear least squares algorithm was more robust for this estimation problem than the Simplex search algorithm. In this thesis, two types of expansion valves, the Electronic Expansion Valve and the Thermostatic Expansion Valve, are considered. The Electronic Expansion Valve model is a static model due to its dynamics being much faster than the systems dynamics; the Thermostatic expansion valve model, however, is a dynamic one. The parameter estimation algorithm developed is validated on two different experimental systems to confirm the practicality of its approach. Knowing the model parameters accurately can lead to a better model for control and fault detection applications. In addition to parameter estimation, this thesis also provides and validates a simple usable mathematical model for the Thermostatic expansion valve. en_US
dc.format.mimetype application/pdf en_US
dc.language.iso en_US en_US
dc.subject Thermostatic Expansion Valve en_US
dc.subject Parameter estimation en_US
dc.subject Simplex search en_US
dc.subject Air-conditioner modeling en_US
dc.title Parameter Estimation of Dynamic Air-conditioning Component Models Using Limited Sensor Data en_US
dc.type Thesis en
thesis.degree.department Mechanical Engineering en_US
thesis.degree.discipline Mechanical Engineering en_US
thesis.degree.grantor Texas A&M University en_US
thesis.degree.name Master of Science en_US
thesis.degree.level Masters en_US
dc.contributor.committeeMember Palazzolo, Alan en_US
dc.contributor.committeeMember Alvarado, Jorge en_US
dc.type.genre thesis en_US
dc.type.material text en_US


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