Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/3689
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dc.contributor.authorAbunike, Emmanuel C.en_US
dc.contributor.authorOkoro, Ogbonnaya I.en_US
dc.contributor.authorDavidson, Innocent E.en_US
dc.date.accessioned2021-11-10T05:06:51Z-
dc.date.available2021-11-10T05:06:51Z-
dc.date.issued2021-09-13-
dc.identifier.citationAbunike, E.C.; Okoro, O.I. and Davidson, I.E. 2021. Finite element design and multi-objective optimization of four pole reluctance motor based on NSGA-II intelligent algorithm. 2021 IEEE AFRICON. Presented at: 2021 IEEE AFRICON. doi:10.1109/africon51333.2021.9570964en_US
dc.identifier.urihttps://hdl.handle.net/10321/3689-
dc.description.abstractThe design of a four-pole reluctance motor with multiple objectives is discussed in this paper using a finite element design methodology based on multi-objective genetic algorithm. Non-dominated genetic algorithm (NSGA-II) is used because of its high performance and intensification in optimization problems. The global sensitivity chart revealed that the motor’s stator pole embrace and yoke thickness are key parameters for the optimization objectives, while the rotor’s pole embrace should be restrained and closely associated with these two key parameters. According to the optimization and sensitivity analysis results, a final design which is superior to the base design was achieved. There were 15 % and 13.2 % improvement in the optimized model in terms of the average torque and efficiency respectively. Also, the optimized model recorded a reduction in the average torque ripple and total loss by 1.55 % and 30.1 % respectively. This demonstrates the NSGA-II intelligent optimization program is a suitable framework to optimize specified objective functions.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2021 IEEE AFRICONen_US
dc.subjectAverage torqueen_US
dc.subjectMulti-objective functionsen_US
dc.subjectPole embraceen_US
dc.subjectReluctance motoren_US
dc.subjectSensitivityen_US
dc.titleFinite element design and multi-objective optimization of four pole reluctance motor based on NSGA-II intelligent algorithmen_US
dc.typeConferenceen_US
dc.date.updated2021-10-31T14:18:10Z-
dc.identifier.doi10.1109/africon51333.2021.9570964-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeConference-
item.languageiso639-1en-
Appears in Collections:Research Publications (Engineering and Built Environment)
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