Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/50561 |
| _version_ | 1811086026702061568 |
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| author | Ong, Chun Yang |
| author2 | Anuradha Annaswamy. |
| author_facet | Anuradha Annaswamy. Ong, Chun Yang |
| author_sort | Ong, Chun Yang |
| collection | MIT |
| description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009. |
| first_indexed | 2024-09-23T13:19:44Z |
| format | Thesis |
| id | mit-1721.1/50561 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T13:19:44Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/505612019-04-10T23:28:06Z Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models Ong, Chun Yang Anuradha Annaswamy. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Mechanical Engineering. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009. In title on title page, double underscored "x" appears as subscript and italic. Includes bibliographical references (leaf 125). 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. (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. by Chun Yang Ong. S.M. 2010-01-07T20:53:24Z 2010-01-07T20:53:24Z 2009 2009 Thesis http://hdl.handle.net/1721.1/50561 463629425 eng 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. http://dspace.mit.edu/handle/1721.1/7582 125 leaves application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Ong, Chun Yang Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models |
| title | Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models |
| title_full | Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models |
| title_fullStr | Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models |
| title_full_unstemmed | Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models |
| title_short | Adaptive PI control of NOx̳ emissions in a Urea Selective Catalytic Reduction System using system identification models |
| title_sort | adaptive pi control of nox emissions in a urea selective catalytic reduction system using system identification models |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/50561 |
| work_keys_str_mv | AT ongchunyang adaptivepicontrolofnoxemissionsinaureaselectivecatalyticreductionsystemusingsystemidentificationmodels |