Electromagnetic Reduced Order Model of a Permanent Magnet Synchronous Motor

This paper presents a high-accuracy reduced order model (ROM) for a Permanent Magnet Synchronous Motor (PMSM), addressing key performance factors such as temperature effects, core losses, and switching dynamics. Utilizing Finite Element Analysis (FEA), the proposed model integrates a comprehensive set of parameters to ensure accuracy in predicting motor behavior under different operating conditions. The developed ROM is highly adaptable, offering potential applications in various topologies and control systems. The results indicate that the ROM provides enhanced accuracy compared to conventional methods, with error rates under 5%, validating its suitability for model-based product development for industries.

Authors

Institutions

Publication Details

Published
2024-11-26
DOI
https://doi.org/10.23919/icems60997.2024.10920969
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Electromagnetic Reduced Order Model of a Permanent Magnet Synchronous Motor

Grace Firsta Lukman, Cheewoo Lee, Chansoo Park, Gyeonghwan Yun et al.
Electric Motor Design and Analysis
article

Electromagnetic Reduced Order Model of a Permanent Magnet Synchronous Motor

Grace Firsta Lukman, Cheewoo Lee, Chansoo Park, Gyeonghwan Yun, Dong-Min Park
article en

Abstract

This paper presents a high-accuracy reduced order model (ROM) for a Permanent Magnet Synchronous Motor (PMSM), addressing key performance factors such as temperature effects, core losses, and switching dynamics. Utilizing Finite Element Analysis (FEA), the proposed model integrates a comprehensive set of parameters to ensure accuracy in predicting motor behavior under different operating conditions. The developed ROM is highly adaptable, offering potential applications in various topologies and control systems. The results indicate that the ROM provides enhanced accuracy compared to conventional methods, with error rates under 5%, validating its suitability for model-based product development for industries.

Pusan National University (KR)
Affordable and clean energy
Openalex Percentile: Top 73%
Electric Motor Design and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.