Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique

Emad Roshandel; Amin Mahmoudi; Solmaz Kahourzade; Wen Soong

doi:10.1109/ECCE44975.2020.9235826

Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique

Emad Roshandel, Amin Mahmoudi, Solmaz Kahourzade, Wen Soong

College of Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

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.

Original language	English
Title of host publication	ECCE 2020 - IEEE Energy Conversion Congress and Exposition
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3815-3822
Number of pages	8
ISBN (Electronic)	9781728158266, 9781728158273
DOIs	https://doi.org/10.1109/ECCE44975.2020.9235826
Publication status	Published - 11 Oct 2020
Event	12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020 - Virtual, Detroit, United States Duration: 11 Oct 2020 → 15 Oct 2020 Conference number: 12

Publication series

Name	ECCE 2020 - IEEE Energy Conversion Congress and Exposition

Conference

Conference	12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020
Country/Territory	United States
City	Virtual, Detroit
Period	11/10/20 → 15/10/20

Keywords

analytical model
flux density
magnetic vector potential
Maxwell equation
radial-flux induction motor

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10.1109/ECCE44975.2020.9235826Licence: In Copyright

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Roshandel, E., Mahmoudi, A., Kahourzade, S., & Soong, W. (2020). Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique. In ECCE 2020 - IEEE Energy Conversion Congress and Exposition (pp. 3815-3822). Article 9235826 (ECCE 2020 - IEEE Energy Conversion Congress and Exposition). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE44975.2020.9235826

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title = "Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique",

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",

author = "Emad Roshandel and Amin Mahmoudi and Solmaz Kahourzade and Wen Soong",

year = "2020",

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doi = "10.1109/ECCE44975.2020.9235826",

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series = "ECCE 2020 - IEEE Energy Conversion Congress and Exposition",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020 ; Conference date: 11-10-2020 Through 15-10-2020",

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Roshandel, E, Mahmoudi, A, Kahourzade, S & Soong, W 2020, Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique. in ECCE 2020 - IEEE Energy Conversion Congress and Exposition., 9235826, ECCE 2020 - IEEE Energy Conversion Congress and Exposition, Institute of Electrical and Electronics Engineers Inc., pp. 3815-3822, 12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020, Virtual, Detroit, Michigan, United States, 11/10/20. https://doi.org/10.1109/ECCE44975.2020.9235826

Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique. / Roshandel, Emad; Mahmoudi, Amin; Kahourzade, Solmaz et al.
ECCE 2020 - IEEE Energy Conversion Congress and Exposition. Institute of Electrical and Electronics Engineers Inc., 2020. p. 3815-3822 9235826 (ECCE 2020 - IEEE Energy Conversion Congress and Exposition).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique

AU - Roshandel, Emad

AU - Mahmoudi, Amin

AU - Kahourzade, Solmaz

AU - Soong, Wen

N1 - Conference code: 12

PY - 2020/10/11

Y1 - 2020/10/11

N2 - 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.

AB - 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.

KW - analytical model

KW - flux density

KW - magnetic vector potential

KW - Maxwell equation

KW - radial-flux induction motor

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T3 - ECCE 2020 - IEEE Energy Conversion Congress and Exposition

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BT - ECCE 2020 - IEEE Energy Conversion Congress and Exposition

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Roshandel E, Mahmoudi A, Kahourzade S, Soong W. Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique. In ECCE 2020 - IEEE Energy Conversion Congress and Exposition. Institute of Electrical and Electronics Engineers Inc. 2020. p. 3815-3822. 9235826. (ECCE 2020 - IEEE Energy Conversion Congress and Exposition). doi: 10.1109/ECCE44975.2020.9235826

Analytical Model and Performance Prediction of Induction Motors using Subdomain Technique

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