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Coupled Field Analysis Needs in the Design of Submersible Electric Motors

Authors: Shehab Ahmed; Hamid A. Toliyat;

Coupled Field Analysis Needs in the Design of Submersible Electric Motors

Abstract

The design optimization of permanent magnet synchronous motors has long been a topic of major interest due to the widespread industrial use of such machines. Although there are a number of commercially available design tools to aid in such a task, the application specific nature of submersible motors has prompted the current interest. A new design consideration, the air gap viscous drag loss, will be shown to have a significant impact on the fluid immersed motor's losses. The conflicting nature of this loss component with the machine's electromagnetic design was presented. Finite element (FE) analysis using computational fluid dynamics software will aid in the understanding of the concept. An electric motor design procedure that takes this loss component into consideration illustrates the need for coupled field analysis in the design of submersible motors. Experimental results were used to corroborate the presented theory and illustrate the initial motivation for this study.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Average
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