Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 266

The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.

A Comprehensive Review of State-of-the-Art Parameter Estimation Techniques for Permanent Magnet Synchronous Motors in Wide Speed Range

Rafaq, Muhammad Saad, Jung, Jin-Woo·2020·IEEE Transactions on Industrial Informatics

Abstract

Permanent magnet synchronous motor (PMSM) drive has emerged as one of the most preferred motor drives for industrial applications owing to its distinguished advantages, such as high torque density, high efficiency, and wide speed range operation. However, accurately updated knowledge about the PMSM parameters is crucial to designing a high-performance trajectory tracking controller. This article presents a state-of-the-art comprehensive review and up-to-date progress of the offline and online parameter estimation techniques of the PMSM drives. First, the problems associated with parameter estimation of the PMSM are systematically summarized to identify the parameters having fast and accurate convergence. Second, the offline parameter estimation techniques are categorized based on the frequency and time responses. Third, the recent advances and developments of the online parameter estimation techniques for PMSMs are assessed. Finally, there is a discussion of extensive industrial applications and future research trends for the parameter estimation techniques.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tii.2019.2944413

Cites

51 of 51 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 51 references

Metadata

Authors
Rafaq, M. S., & Jung, J.-W.
Venue
IEEE Transactions on Industrial Informatics
Published
2020-07
Volume
16
Issue
7
Pages
4747-4758
ISSN
  • 1551-3203 (ISSN-L)
  • 1941-0050
OpenAlex
W2977435692
Cited by
266
References
51
FWCI
7.58
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A Comprehensive Review of State-of-the-Art Parameter Estimation Techniques for Permanent Magnet Synchronous Motors in Wide Speed Range. https://app.cochat.ai/papers/10.1109/tii.2019.2944413
The paper
Rafaq, M. S., & Jung, J.-W. (2020). A Comprehensive Review of State-of-the-Art Parameter Estimation Techniques for Permanent Magnet Synchronous Motors in Wide Speed Range. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2019.2944413

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.