Sensitivity Analysis of Multiphase Induction Machine Parameter Identification Methods

A multiphase induction machine (MPIM) modeled using vector space decomposition (VSD) provides insight into space harmonics which are segregated into vector spaces. Depending on the winding configuration of the MPIM, some vector spaces can produce torque in addition to the fundamental vector space, and they can be represented by a standard equivalent circuit (EC) of an induction machine (IM). This paper evaluates multiple EC parameters identification methods (IDMs) and proposes a robust IDM routine for their accurate estimation. Furthermore, the proposed IDM routine shows reduced sensitivity to errors in known parameters compared to the standard IDMs, which is validated with the help of a detailed simulation model of a 9-phase IM.

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Publication Details

Published
2025-05-18
DOI
https://doi.org/10.1109/iemdc60492.2025.11061036
Primary Topic
Metallurgy and Material Forming
Type
article
Field-Weighted Citation Impact
0.00

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article

Sensitivity Analysis of Multiphase Induction Machine Parameter Identification Methods

Omer Ikram ul Haq, Luca Peretti, Sjoerd G. Bosga, R. S. Kanchan
Metallurgy and Material Forming
article

Sensitivity Analysis of Multiphase Induction Machine Parameter Identification Methods

Omer Ikram ul Haq, Luca Peretti, Sjoerd G. Bosga, R. S. Kanchan
article en

Abstract

A multiphase induction machine (MPIM) modeled using vector space decomposition (VSD) provides insight into space harmonics which are segregated into vector spaces. Depending on the winding configuration of the MPIM, some vector spaces can produce torque in addition to the fundamental vector space, and they can be represented by a standard equivalent circuit (EC) of an induction machine (IM). This paper evaluates multiple EC parameters identification methods (IDMs) and proposes a robust IDM routine for their accurate estimation. Furthermore, the proposed IDM routine shows reduced sensitivity to errors in known parameters compared to the standard IDMs, which is validated with the help of a detailed simulation model of a 9-phase IM.

KTH Royal Institute of Technology (SE)
ABB
Openalex Percentile: Top 82%
Metallurgy and Material Forming
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