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Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models

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dc.contributor.advisor Anuradha Annaswamy. en_US Ong, Chun Yang en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US 2010-01-07T20:53:24Z 2010-01-07T20:53:24Z 2009 en_US 2009 en_US
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009. en_US
dc.description In title on title page, double underscored "x" appears as subscript and italic. en_US
dc.description Includes bibliographical references (leaf 125). en_US
dc.description.abstract The Urea SCR System has shown great potential for implementation on diesel vehicles wanting to meet the upcoming emission regulations by the EPA. The objective of this thesis is to develop an adaptive controller that is capable of uniformly maintaining a high efficiency and a low ammonia slip in the presence of various uncertainties in the underlying mechanisms as well as the environment that significantly affect the SCR dynamics. Towards this end, the dynamics of the Urea SCR System was modeled using input-output data as a first order transfer function model.Using Stored NH3 as the output, and Excess NH3,in as input, a systems identification approach was adopted to estimate the values of k and T, the parameters for the transfer function. A family of -these parameter values was determined as the operating conditions of NH3,in and NOx,in were varied. Using a full chemistry model developed in the literature, the model was tested and verified to ensure that an acceptable level of accuracy was being achieved. A closed-loop PI controller was first designed and tested using the Stored NH3 as the system output. The closed-loop performance of the resulting system was evaluated using the full chemistry model, and was shown to result in an efficiency of 95% or higher, with a maximum NH3 slip of less than 20 ppm. An adaptive PI controller was then designed and tested, and was shown to lead to comparable performance even as the operating conditions varied. Since Stored NH3 is not measurable in an actual physical system, the next step was to use the combined state of NH3 Slip and NOx Slip as a system output. en_US
dc.description.abstract (cont.) A novel adaptive PI-controller with nonlinear components and projection maps was developed in order to account for the nonlinear relationship between Stored NH3 and the new system output. The same metrics of NO, reduction efficiency and peak ammonia slip were computed for the resulting system during a typical FTP cycle. It was observed the nonlinear adaptive controller was capable of delivering at least 90% NOx efficiency and a peak NH3 Slip of less than 20 ppm. In conclusion, the Non-Linear Adaptive PI Controller successfuly met the target requirements in the context of a full chemistry simulations. en_US
dc.description.statementofresponsibility by Chun Yang Ong. en_US
dc.format.extent 125 leaves en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri en_US
dc.subject Mechanical Engineering. en_US
dc.title Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models en_US
dc.type Thesis en_US S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US
dc.identifier.oclc 463629425 en_US

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