Please use this identifier to cite or link to this item:
http://10.1.7.192:80/jspui/handle/123456789/8895
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vaghela, Meghavi Satishbhai | - |
dc.date.accessioned | 2019-09-27T09:02:33Z | - |
dc.date.available | 2019-09-27T09:02:33Z | - |
dc.date.issued | 2018-06-01 | - |
dc.identifier.uri | http://10.1.7.192:80/jspui/handle/123456789/8895 | - |
dc.description.abstract | The induction motor ratings are readily available or in most cases given by manufacturer of the motor but in order to implement vector control scheme on induction motor estimation of parameters with minimum error is highly desirable. There are several approaches proposed in literature for estimating parameters of motor in the online mode but these controllers as well as their control methods have always been very niche and propriety based leading to their limited usage. This project aims at proposing an offline method for estimating the parameters of the induction motor and optimizing the estimated parameters using various random search techniques for better drive control and performance. The proposed offline methods would also serve as an alternative method for the conventional parameter estimation tests like no-load test and blocked rotor test leading the better up-time and implementation time of the complete drive system. | en_US |
dc.publisher | Institute of Technology | en_US |
dc.relation.ispartofseries | 16MEEP09; | - |
dc.subject | Electrical 2016 | en_US |
dc.subject | Project Report 2016 | en_US |
dc.subject | Electrical Project Report | en_US |
dc.subject | Project Report | en_US |
dc.subject | EC (PEMD) | en_US |
dc.subject | Power Electronics, Machines & Drives | en_US |
dc.subject | 16MEE | en_US |
dc.subject | 16MEEP | en_US |
dc.subject | 16MEEP09 | en_US |
dc.subject | PEMD | en_US |
dc.subject | PEMD 2016 | en_US |
dc.title | Off-line Parameter Estimation of Three Phase Induction Motor using Advanced Computation Techniques | en_US |
dc.type | Dissertation | en_US |
Appears in Collections: | Dissertation, EE (PEMD) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
16MEEP09.pdf | 16MEEP09 | 5.33 MB | Adobe PDF | ![]() View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.