2003 IEEE International Symposium on Industrial Electronics ( Cat. No.03TH8692)
DOI: 10.1109/isie.2003.1267924
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Obtaining the magnetic characteristics of an 8/6-switched reluctance machine: FEM analysis and experimental tests

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Cited by 32 publications
(38 citation statements)
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“…5-A, the magnetic saturation has a significant effect in this modular SFP topology. However, a steep saturation can also be seen in regular machines as presented in [11]. Two structurally different topologies (for instance, having different numbers of poles) can be compared, preserving certain dimensions of the magnetic circuit where the flux paths lie on.…”
Section: Design Study Results and Discussionmentioning
confidence: 99%
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“…5-A, the magnetic saturation has a significant effect in this modular SFP topology. However, a steep saturation can also be seen in regular machines as presented in [11]. Two structurally different topologies (for instance, having different numbers of poles) can be compared, preserving certain dimensions of the magnetic circuit where the flux paths lie on.…”
Section: Design Study Results and Discussionmentioning
confidence: 99%
“…The average power 〈 〉 is thus given by (9). Both current and phase inductance may be written as functions of rotor position, and maximum values and , respectively, by using (10) and (11). After multiplying these functions, the phase flux-linkage is expressed by (12).…”
Section: A Rated Power and Lossesmentioning
confidence: 99%
“…Fast and accurate acquisition of electromagnetic characteristics is very important for advanced control and performance assessment of SRM. The core of obtaining the electromagnetic characteristics of SRM is to accurately describe the relationship among the flux-linkage ψ, rotor position θ and current i [5,6]. However, it is difficult to depict the flux-linkage characteristic of the SRM accurately because of the double saliency structure and high nonlinearity of magnetic material [7].…”
Section: Introductionmentioning
confidence: 99%
“…Some of them, as [4][5][6][7] discussed analytical models based on motor geometry data, while others were dedicated to the SRM models which employ magnetic equivalent circuits [8,9]. Other models are based on finite element analysis (FEA) [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25].…”
Section: Introductionmentioning
confidence: 99%
“…Training fuzzy logic and ANN model requires more time and a large amount of initial data. A usual approach is based on the analytical fitting of the previously obtained magnetizing characteristics [16][17][18][19][20][21][22][23][24][25].…”
Section: Introductionmentioning
confidence: 99%