Dynamic dq Model of PMSM Using FE‐Based LUTs

ABSTRACT In recent years, a significant amount of research on modelling of electrical machines was dedicated to high fidelity hybrid models that incorporate pre‐calculated FEA data in the form of lookup tables (LUTs). Despite the increasing interest in this dynamic modelling approach, the literature largely disregards how the construction process of LUTs can impact both the accuracy of the model and the computational efficiency. This paper explores the LUT accuracy level attainable by application of various relevant data fitting interpolation algorithms and data calibration parameters using a standard permanent magnet machine geometry. It is demonstrated that an optimal trade‐off between high accuracy LUT demand and the inherent high computational requirements associated with creating the requisite FEA datasets is important for facilitating effective development of hybrid model LUTs.

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Publication Details

Journal
IET Electric Power Applications
Published
2025-01-01
DOI
https://doi.org/10.1049/elp2.70037
Citations
3
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
2.19

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article

Dynamic dq Model of PMSM Using FE‐Based LUTs

Siniša Djurović, Judith Apsley, Christian Kukura
3 citations
IET Electric Power Applications
Electric Motor Design and Analysis
2.19
article

Dynamic dq Model of PMSM Using FE‐Based LUTs

Siniša Djurović, Judith Apsley, Christian Kukura
article en
3 citations

Abstract

ABSTRACT In recent years, a significant amount of research on modelling of electrical machines was dedicated to high fidelity hybrid models that incorporate pre‐calculated FEA data in the form of lookup tables (LUTs). Despite the increasing interest in this dynamic modelling approach, the literature largely disregards how the construction process of LUTs can impact both the accuracy of the model and the computational efficiency. This paper explores the LUT accuracy level attainable by application of various relevant data fitting interpolation algorithms and data calibration parameters using a standard permanent magnet machine geometry. It is demonstrated that an optimal trade‐off between high accuracy LUT demand and the inherent high computational requirements associated with creating the requisite FEA datasets is important for facilitating effective development of hybrid model LUTs.

IET Electric Power ApplicationsVol. 19(1)
University of Manchester (GB)
UK Research and Innovation, Faculty of Science and Engineering, University of Manchester
Openalex Percentile: Top 12%
Electric Motor Design and Analysis
2.19
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