Core Loss Modeling Based on Equivalent Circuit for Switched Reluctance Motors

Kusumi, Takayuki; Kobayashi, Kosuke; Hara, Takuto; Umetani, Kazuhiro; Hiraki, Eiji

doi:10.1109/icit.2019.8754931

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…The analytical methods are, by far, very fast, but they usually lack accuracy. In Kusumi et al (2019), a method for estimation of core losses in SRMs based on an equivalent circuit is provided. A technique based on the calculation of flux waveforms is reported in Hayashi and Miller (1995).…”

Section: Introductionmentioning

confidence: 99%

An adaptive method for calculation of iron losses in switched reluctance motors using a minimum number of magnetostatic finite element simulations

Fard

Mirsalim

2022

COMPEL

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Purpose This paper aims to present an adaptive method based on finite element analysis to calculate iron losses in switched reluctance motors (SRMs). Calculation of iron losses by analytical formulas has limited accuracy. On the other hand, its estimation in rotating electrical machines through fully dynamic simulations with a fine time-step is time-consuming. However, in the initial design process, a quick and sufficiently accurate method, i.e. a value close to that of iron losses, is always welcome. The method presented in this paper is a semi-analytical approach. The main problem is that iron losses depend on d B/d t. Therefore, the accuracy of the calculation of iron losses depends on the accuracy of the calculation of the first derivative of the flux density waveform. When adopting a magnetostatic model to estimate the iron losses, an important question arises: by how many magnetostatic simulations can the iron losses be estimated within the desired accuracy? In the proposed algorithm, the aim is not to accurately calculate the value of iron losses in SRMs. The objective is to find a numerical error criterion to calculate iron losses in SRMs with a minimum number of magnetostatic simulations. Design/methodology/approach A finite element solver is developed by authors in MATLAB to solve the 2 D nonlinear magnetostatic problem using the Newton–Raphson method. A parametric program is developed to create geometry and mesh. The proposed method is implemented in MATLAB using the developed solver. Counterpart simulations are done in the ANSYS Maxwell software to validate the accuracy of the results generated by the developed solver. Findings The performance of the proposed method is studied on a 12/8 (500 W) SRM. Three scenarios are studied. The first one is the calculation of iron losses by uniform refinement, and the second one is by adaptive refinement, and the last one is by adaptive refinement started by particular initial points (switching points). According to the results, the proposed method substantially reduces the number of magnetostatic simulations without sacrificing accuracy. Originality/value The main novelty of this paper is introducing an error criterion to find the minimum number of magnetostatic simulations that are needed to calculate iron losses with the desired accuracy.

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Section: Introductionmentioning

confidence: 99%

An adaptive method for calculation of iron losses in switched reluctance motors using a minimum number of magnetostatic finite element simulations

Fard

Mirsalim

2022

COMPEL

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“…However, some measurements are necessary for the determination of the non-linear virtual resistance, and therefore, [20] cannot be used in the design process. The model given in [21] is based on calculating the width of the hysteresis loop, which depends on the peak to the peak value of flux linkage and rotor position. These parameters directly affect the area of the hysteresis loop.…”

Section: Introductionmentioning

confidence: 99%

Non‐linear model of the switched reluctance motor with included core losses’ effects

Mihić

Terzić

Koprivica

2021

IET Electric Power Appl

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To accurately predict motor performance, considering the effects of core losses is of great importance, especially at speeds much higher than the base where the core losses represent a considerable portion of the total drive losses. Neglecting the effects of core losses leads to an error in the switched reluctance motor (SRM) performance prediction. In this study, a previously developed non-linear SRM model with multiphase coupling is extended by considering the instantaneous effects of core losses on the SRM performance. Using the new model, the nature of these effects is determined. A comparison of the simulation results of the proposed, basic, and finite element method (FEM) model confirms the importance of considering the effects of core losses on motor performance. Besides the FEM model, the accuracy of the proposed model is verified by experiments.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The equivalent circuit is used to establish the core loss model of SRM [5][6][7][8][9][10][11]. Bertotti loss calculation method was used to calculate the core loss of the motor, then importing the loss to the thermal domain as the heat sources for analyzing the thermal stability of the motor [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Thermal Modeling and Analysis of Hybrid Excitation Double Stator Bearingless Switched Reluctance Motor

Xiang¹,

Lǐ²,

Yuan³

et al. 2020

PIER M

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Core Loss Modeling Based on Equivalent Circuit for Switched Reluctance Motors

Cited by 3 publications

References 15 publications

An adaptive method for calculation of iron losses in switched reluctance motors using a minimum number of magnetostatic finite element simulations

An adaptive method for calculation of iron losses in switched reluctance motors using a minimum number of magnetostatic finite element simulations

Non‐linear model of the switched reluctance motor with included core losses’ effects

Thermal Modeling and Analysis of Hybrid Excitation Double Stator Bearingless Switched Reluctance Motor

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