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https://hdl.handle.net/2440/132222
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Type: | Conference paper |
Title: | Analytical model and performance prediction of induction motors using subdomain technique |
Author: | Roshandel, E. Mahmoudi, A. Kahourzade, S. Soong, W. |
Citation: | Proceedings of the IEEE Energy Conversion Congress and Exposition (ECCE 2020), 2020, pp.3815-3822 |
Publisher: | IEEE |
Publisher Place: | online |
Issue Date: | 2020 |
Series/Report no.: | https://ieeexplore.ieee.org/xpl/conhome/9235288/proceeding |
ISBN: | 9781728158266 |
Conference Name: | IEEE Energy Conversion Congress and Exposition (ECCE) (11 Oct 2020 - 15 Oct 2020 : virtual online) |
Statement of Responsibility: | Emad Roshandel, Amin Mahmoudi, Solmaz Kahourzade, Wen Soong |
Abstract: | In this paper, the magnetic vector potential (MVP) equations are solved for a 5.5-kW radial-flux induction machine (RFIM) in five subdomains. The proposed modeling technique considers a uniform distribution of the current density in the rectangular slots of both rotor and stator. The RFIM is represented using a 2D model in the cylindrical coordinate system. The magnetic flux distribution in each region which is used to calculate the core losses and the machine inductances for the steady state analysis of the machine. T-equivalent circuit (T-EC) is considered to study the machine performance parameters. The rotor and stator resistances are calculated based on the geometry of the machine. The results demonstrate the accuracy of the model in prediction of the airgap flux density. The comparison of the machine performance parameters with the 2D FEA results demonstrate the reliability of the analytical model in the prediction of the machine behavior at the rated condition. |
Keywords: | analytical model; flux density; magnetic vector potential; Maxwell equation; radial-flux induction motor |
Rights: | ©2020 IEEE |
DOI: | 10.1109/ECCE44975.2020.9235826 |
Published version: | http://dx.doi.org/10.1109/ecce44975.2020.9235826 |
Appears in Collections: | Electrical and Electronic Engineering publications |
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