Performance Analysis of Vector-Controlled Interior Permanent Magnet Synchronous Motors Based on an Accurate Dynamic Model

Recent research suggests that Permanent Magnet Synchronous Motors (PMSM) may emerge as a formidable competitor to Induction Motors (IM) in high-performance servo applications. The literature extensively uses the simple lumped-parameters model "LPM", also known as the lumped-parameters dqo model or conventional model, to depict the dynamic response of the machine using Park and Clarke transformations. The notion of vector control is applied to PMSM to provide linear dynamics similar to those of a DC motor. The linearized model contains two control loops: the current loop and the speed loop. The control scheme aims to trace the specified reference speed accurately while having a quick dynamic reaction. This has been achieved in various literature along with different enhancements. However, due to the linearized lumped-parameters model and its assumption of constant parameters, the control system's accuracy and dynamic performance can be affected. This paper aims to study the effect of accurate physical motor modeling (in terms of the degree of complexity) on the dynamic response of the vector controller. The industry-standard Finite Element Method (FEM) is used in the modeling method, and its simulation results under vector control are compared with those of conventionally modeled motors. The simulation results show that the proposed model has successfully introduced a more realistic response to the machine's dynamic performance under vector control compared with conventional model performance, especially with torque and back-emf responses.

Authors

Institutions

Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/mepcon63025.2024.10850186
Citations
1
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
0.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance Analysis of Vector-Controlled Interior Permanent Magnet Synchronous Motors Based on an Accurate Dynamic Model

Said M. Allam, Mohamed A. Almozayen, Nisar Ahmed
1 citations
Electric Motor Design and Analysis
0.21
article

Performance Analysis of Vector-Controlled Interior Permanent Magnet Synchronous Motors Based on an Accurate Dynamic Model

Said M. Allam, Mohamed A. Almozayen, Nisar Ahmed
article en
1 citations

Abstract

Recent research suggests that Permanent Magnet Synchronous Motors (PMSM) may emerge as a formidable competitor to Induction Motors (IM) in high-performance servo applications. The literature extensively uses the simple lumped-parameters model "LPM", also known as the lumped-parameters dqo model or conventional model, to depict the dynamic response of the machine using Park and Clarke transformations. The notion of vector control is applied to PMSM to provide linear dynamics similar to those of a DC motor. The linearized model contains two control loops: the current loop and the speed loop. The control scheme aims to trace the specified reference speed accurately while having a quick dynamic reaction. This has been achieved in various literature along with different enhancements. However, due to the linearized lumped-parameters model and its assumption of constant parameters, the control system's accuracy and dynamic performance can be affected. This paper aims to study the effect of accurate physical motor modeling (in terms of the degree of complexity) on the dynamic response of the vector controller. The industry-standard Finite Element Method (FEM) is used in the modeling method, and its simulation results under vector control are compared with those of conventionally modeled motors. The simulation results show that the proposed model has successfully introduced a more realistic response to the machine's dynamic performance under vector control compared with conventional model performance, especially with torque and back-emf responses.

Tanta University (EG)
Affordable and clean energy
Openalex Percentile: Top 44%
Electric Motor Design and Analysis
0.21
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.