Volume 14, Issue 3 (September 2018)                   IJEEE 2018, 14(3): 259-269 | Back to browse issues page

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Jabbari A. Analytical Modeling of Magnetic Field Distribution in Inner Rotor Brushless Magnet Segmented Surface Inset Permanent Magnet Machines. IJEEE 2018; 14 (3) :259-269
URL: http://ijeee.iust.ac.ir/article-1-1186-en.html
Analytical Modeling of Magnetic Field Distribution in Inner Rotor Brushless Magnet Segmented Surface Inset Permanent Magnet Machines
A. Jabbari
Abstract:   (4465 Views)
Brushless permanent magnet surface inset machines are interested in industrial applications due to their high efficiency and power density. Magnet segmentation is a common technique in order to mitigate cogging torque and electromagnetic torque components in these machines. An accurate computation of magnetic vector potential is necessary in order to compute cogging torque, electromagnetic torque, back electromotive force and self/mutual inductance. A 2D analytical method for magnetic vector potential calculation in inner rotor brushless segmented surface inset permanent magnet machines is proposed in this paper. The analytical method is based on the resolution of Laplace and Poisson equations as well as Maxwell equation in a quasi- Cartesian polar coordinate by using sub-domain method. One of the main contributions of the paper is to derive an expression for the magnetic vector potential in the segmented PM region by using hyperbolic functions. The developed method is applied on the performance computation of two prototype surface inset magnet segmented motors with open circuit and on load conditions. The results of these models are validated through FEM method.
Keywords: 2D Analytical Modeling , Segmented Permanent Magnet , Surface Inset DC Machine , Sub-Domain Method , Hyperbolic Functions
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Type of Study: Research Paper | Subject: Special Electric Machines
Received: 2017/11/06 | Revised: 2018/10/19 | Accepted: 2018/02/08
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.