Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/231939
Title: Parameter Estimation of Three Phase Induction Motor
Researcher: Singh, Mayank Pratap
Guide(s): Chaturvedi, D.K. and Man Mohan
Keywords: Engineering and Technology,Engineering,Engineering Electrical and Electronic
University: Dayalbagh Educational Institute
Completed Date: 2016
Abstract: Three-phase induction motors (TPIMs) are used in all types of industries. The performance of TPIM is chiefly dependent on its parameters. Hence, there is great importance to improve the reliability of TPIM under different operating conditions by its observing parameters. The TPIM parameter estimation is the art and science of building mathematical models of dynamic systems from practical input-output data. It can be seen as the interface between the real world of applications and the mathematical world of control theory. The model abstractions largely depend upon the system parameters. The knowledge of all the machine parameters is very important to tune the controllers of a high performance motor drive system. newlineThe details of three phase induction motor modeling e.g., d-q transformation model, approximated equivalent (AE) circuit analysis and basic machine nonlinearities along with an exhaustive literature survey where the thrust is given on the problems on on-line/off-line estimation of TPIM parameters, the results of soft computing parameters estimation have been compared with actual parameters obtained from experiments such as stator and rotor resistances and reactances at different loading conditions. newlineThe d-q model is used for the mathematical modeling of TPIM and encoded in MATLAB with the help of Simulink. The different performance curves of TPIM are calculated such as speed-torque curve, Stator current curves, Rotor current curves, Stator and rotor voltage curves under different operating conditions after short circuiting the stator phase winding by 10%, 20% and 30% turns of coil of phase a, phases a and b and phases a, b and c . The soft computing techniques have been used for parameters estimation of TPIM such as ANA, GNA and QGNA are used for this purpose. For validation of results obtained by above techniques, an experimental setup is developed in Electrical Power Research Lab, Dayalbagh Educational Institute (Deemed Univ.), Dayalbagh, Agra using microcontroller-ATMEGA16, various sensors and data acquisition system (DAS) for acquiring the data experimentally. The parameters are estimated using ANA, GNA and Q-GNA and results are compared with experimentally calculated machine parameters. newline newline
Pagination: 
URI: http://hdl.handle.net/10603/231939
Appears in Departments:Department of Electrical Engineering

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01_title.pdfAttached File6.4 kBAdobe PDFView/Open
02_certificate.pdf329.25 kBAdobe PDFView/Open
03_declaration.pdf167.42 kBAdobe PDFView/Open
05_acknowledgement.pdf147.88 kBAdobe PDFView/Open
06_contents.pdf267.39 kBAdobe PDFView/Open
07_list_of_tables.pdf249.07 kBAdobe PDFView/Open
08_list_of_figures.pdf282.5 kBAdobe PDFView/Open
09_abbreviations.pdf384.01 kBAdobe PDFView/Open
10_chapter 1.pdf409.97 kBAdobe PDFView/Open
11_chapter 2.pdf376.2 kBAdobe PDFView/Open
12_chapter 3.pdf1.58 MBAdobe PDFView/Open
13_chapter 4.pdf1.35 MBAdobe PDFView/Open
14_chapter 5.pdf2.21 MBAdobe PDFView/Open
15_conclusion.pdf154.64 kBAdobe PDFView/Open
16_references.pdf441.04 kBAdobe PDFView/Open
17_appendix.pdf2.74 MBAdobe PDFView/Open
18_summary.pdf129.87 kBAdobe PDFView/Open


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