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Title: Nonlinear varying-network magnetic circuit analysis of consequent-pole permanent-magnet motor for electric vehicles
Authors: Wang, Hui
Chau, Kwok Tong
Lee, Christopher Ho Tin
Chan, C. C.
Yang, Tengbo
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Wang, H., Chau, K. T., Lee, C. H. T., Chan, C. C. & Yang, T. (2021). Nonlinear varying-network magnetic circuit analysis of consequent-pole permanent-magnet motor for electric vehicles. World Electric Vehicle Journal, 12(4), 254-.
Journal: World Electric Vehicle Journal
Abstract: To conserve rare earth resources, consequent-pole permanent-magnet (CPPM) machine has been studied, which employs iron-pole to replace half PM poles. Meanwhile, to increase flux-weakening ability, hybrid excitation CPPM machine with three-dimensional (3-D) flux flow has been proposed. Considering finite element method (FEM) is time-consuming, for the analysis of the CPPM machine, this paper presents a nonlinear varying-network magnetic circuit (NVNMC), which can analytically calculate the corresponding electromagnetic performances. The key is to separate the model of CPPM machine into different elements reasonably; thus, the reluctances and magnetomotive force (MMF) sources in each element can be deduced. While taking into account magnetic saturation in the iron region, the proposed NVNMC method can accurately predict the 3-D magnetic field distribution, hence determining the corresponding back-electromotive force and electromagnetic power. Apart from providing fast calculation, this analytical method can provide physical insight on how to optimize the design parameters of this CPPM machine. Finally, the accuracy of the proposed model is verified by comparing the analytical results with the results obtained by using FEM. As a result, with so many desired attributes, this method can be employed for machine initial optimization to achieve higher power density.
ISSN: 2032-6653
DOI: 10.3390/wevj12040254
Schools: School of Electrical and Electronic Engineering 
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// 4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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