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Record W2979331792 · doi:10.1109/access.2019.2947047

A Comprehensive Review of Flux Barriers in Interior Permanent Magnet Synchronous Machines

2019· review· en· W2979331792 on OpenAlexafffund
Ehab Sayed, Yinye Yang, Berker Bilgin, Mohamed H. Bakr, Ali Emadi

Bibliographic record

VenueIEEE Access · 2019
Typereview
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Excellence Research Chairs, Government of Canada
KeywordsMagnetPermanent magnet synchronous generatorComputer scienceFlux (metallurgy)Electrical engineeringEngineeringMaterials science

Abstract

fetched live from OpenAlex

Interior permanent magnet synchronous machines (IPMSMs) are commonly utilized in many applications where high-torque density and low torque ripple are required. Flux barriers inside the rotor have a great impact on the electromagnetic performance and thus considered as an effective design parameter. This paper provides a comprehensive review of the function and design methodologies of flux barriers in IPMSMs. Both symmetric and asymmetric flux barriers that improve the torque capability and decrease torque ripples are discussed. The paper also investigates different flux barrier designs to reduce the stator and rotor iron losses to enhance the motor efficiency. The optimization of the shape of the flux barriers to mitigate irreversible demagnetization of the rotor magnets is also presented. It is concluded that a good design of flux barriers can significantly improve the motor's electromagnetic performance while reducing the manufacturing costs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.322
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations54
Published2019
Admission routes2
Has abstractyes

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