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Parameter Estimation of Asymmetrical Six-phase Induction Machines using Modified Standard Tests

Levi, E, Che, HS, Dordevic, O and Abdel-Khalik, AS (2017) Parameter Estimation of Asymmetrical Six-phase Induction Machines using Modified Standard Tests. IEEE Transactions on Industrial Electronics, 64 (8). pp. 6075-6085. ISSN 0278-0046

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Abstract

In multiphase machine drives, accuracy of the estimated machine parameters is crucial for effective performance prediction and/or control. While a great amount of work has been done on parameter estimation for three-phase machines, corresponding discussions for six-phase machine remain scarce. It has been proven in the literature that the effect of mutual leakage inductance between different winding layers has a significant impact on the equivalent machine reactance, which challenges the standard separation method of stator and rotor leakage inductances from the measured locked-rotor impedance. In this paper, parameter identification of an asymmetrical six-phase induction machine using six-phase no-load and locked-rotor tests is discussed. A zero-sequence test using an improved equivalent circuit is proposed to improve the accuracy of the estimated parameters. The concept is verified using experimental results obtained from a low-power prototype asymmetrical six-phase machine.

Item Type: Article
Additional Information: 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Uncontrolled Keywords: 08 Information And Computing Sciences, 09 Engineering
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Electronics & Electrical Engineering (merged with Engineering 10 Aug 20)
Publisher: Institute of Electrical and Electronics Engineers
Date Deposited: 03 Mar 2017 09:20
Last Modified: 04 Sep 2021 11:51
DOI or ID number: 10.1109/TIE.2017.2677349
URI: https://researchonline.ljmu.ac.uk/id/eprint/5744
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