Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/13685
DC Field | Value | |
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dc.title | Geometry-dependent torque optimization for small spindle motors based on reduced basis finite element formulation | |
dc.contributor.author | AZMI BIN AZEMAN | |
dc.date.accessioned | 2010-04-08T10:35:29Z | |
dc.date.available | 2010-04-08T10:35:29Z | |
dc.date.issued | 2004-03-24 | |
dc.identifier.citation | AZMI BIN AZEMAN (2004-03-24). Geometry-dependent torque optimization for small spindle motors based on reduced basis finite element formulation. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/13685 | |
dc.description.abstract | This thesis looks at the novel technique of Reduced-Basis Method applied to the optimisation of electromagnetic problems. Iterative optimisation in a wide search space can be time consuming, regardless of whether statistical or deterministic methods are employed in the search. A fast method of computing the cost function, in this case the cogging torque, is developed which takes advantage of the accuracy of finite element method but with faster computation time. The method is applied to the problem of predicting the cogging torque in a brushless DC permanent magnet machine. Cogging torque is known to be highly geometry dependent and the variation of cogging torque with permanent magnet dimensions (radial thickness and arc angle) is investigated. Results are compared against that obtained using FLUX2D, a commercially available Electromagnetic Finite Element Package. | |
dc.language.iso | en | |
dc.subject | Optimization, Electromagnetics, Finite Element, Spindle Motors, Cogging, Linear Transformation | |
dc.type | Thesis | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.contributor.supervisor | JABBAR, MOHAMMED ABDUL | |
dc.description.degree | Master's | |
dc.description.degreeconferred | MASTER OF ENGINEERING | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Master's Theses (Open) |
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File | Description | Size | Format | Access Settings | Version | |
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thesis.pdf | 802.23 kB | Adobe PDF | OPEN | None | View/Download |
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