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Record W4409017614 · doi:10.4271/2025-01-8143

The Effect of Rotor Notches on Air Gap Heat Transfer Coefficient and Electromagnetic Performance in a Permanent Magnet Synchronous Motor for Traction Applications

2025· article· en· W4409017614 on OpenAlexaff
Arthur Zajac, Buddhika de Silva, Jigar Mistry, Reza Nasiri‐Zarandi, Ofelia A. Jianu, Narayan C. Kar

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2025
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTraction (geology)Air gap (plumbing)Traction motorMagnetRotor (electric)Synchronous motorMechanical engineeringAutomotive engineeringAC motorMaterials sciencePhysicsElectrical engineeringElectric motorEngineeringComposite material

Abstract

fetched live from OpenAlex

This study investigates the impact of various notch geometries on the outer surface of the rotor of an interior permanent magnet synchronous motor intended for traction applications, focusing on improving both its thermal and electromagnetic performances. Traditional motor cooling methods, such as water jackets or oil spray/impingement, typically target the stator and/or end windings, neglecting rotor cooling. As a result, the dissipation of the heat from the rotor is dependent on the heat transfer across the air gap surrounding the rotor, despite air’s poor thermal conductivity, which causes it to act as an insulator. Rotor notches are used to limit the higher order harmonics from air gap flux density which results in decreased torque ripple, cogging torque, noise, and vibration of the machine. While the effect of rotor notches on electromagnetic performance is analyzed, their impact on the thermal management of the motor, particularly the heat transfer coefficient in the air gap, remains largely unexplored. Previous experimental and numerical works have predominantly focused on heat transfer in the air gap for a smooth stator and rotor or a slotted stator with a smooth rotor; there exists a lack of studies which have simultaneously examined the electromagnetic and thermal effects of a notched rotor on electric machines. This work utilizes computational fluid dynamics to model fluid and thermal behavior and finite element analysis to determine electromagnetic performance for different notch geometries. By investigating the notch geometry with a commercially available machine as a baseline, this study enhanced heat transfer in the air gap, improving rotor cooling, and yielded modest improvements in electromagnetic performance. This analysis provides valuable insights for developing advanced rotor designs that achieve excellent thermal and electromagnetic performance for high power density applications.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.212
Teacher spread0.207 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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