2020 IEEE Energy Conversion Congress and Exposition (ECCE) 2020
DOI: 10.1109/ecce44975.2020.9235826
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Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique

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Cited by 20 publications
(20 citation statements)
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“…The loss separation technique for estimation of the core losses is not limited to the FEA based software. Some analytical models which can estimate the flux density in the iron parts have employed in (1) to predict the core loss [119][120][121]. The estimation of the flux density based on the sizing equation and magnetic equivalent circuit of the electrical machines allows to find the core loss by (1) [122][123][124].…”
Section: Core Lossesmentioning
confidence: 99%
“…The loss separation technique for estimation of the core losses is not limited to the FEA based software. Some analytical models which can estimate the flux density in the iron parts have employed in (1) to predict the core loss [119][120][121]. The estimation of the flux density based on the sizing equation and magnetic equivalent circuit of the electrical machines allows to find the core loss by (1) [122][123][124].…”
Section: Core Lossesmentioning
confidence: 99%
“…This paper is the continuation of our earlier work presented in [38]. Compared to [38], firstly, the calculation of the EEC inductances in this paper using the energy equations is improved by consideration of the mutual inductance between the stator windings. This improves the accuracy of the calculated inductances from the MVPs.…”
Section: Introductionmentioning
confidence: 95%
“…In Mollaeian et al (2021), the authors used Fourier-based modeling considering finite permeability to model magnetic saturation in IM. Recent work has focused on the calculation of the magnetic field inside the machine considering the magnetic saturation effects (Roshandel et al , 2020) and (Roshandel et al , 2022). The authors proposed a coupled model based on electric equivalent circuit (EEC) and SD technique with magnetostatic formulation.…”
Section: Introductionmentioning
confidence: 99%