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Impact of Wide-Bandgap Devices on Turn-to-Turn Insulation Performance in Hairpin Windings for Electric Vehicle Traction Motors

2025· article· en· W4412976721 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Applied Research
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTraction motorTurn (biochemistry)Electromagnetic coilTraction (geology)Automotive engineeringElectrical engineeringElectric motorMaterials scienceEngineeringMechanical engineeringPhysicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

This study examines the performance of turn-to-turn insulation in hairpin windings of electric vehicle motors when exposed to stress conditions representative of wide-bandgap (WBG) power converter operation. Using corona-resistant rectangular enameled wires, back-to-back samples were fabricated to emulate turn-to-turn insulation and were subjected to 24-hour aging under high-voltage unipolar pulses with a 40 ns rise time. The tests explored the effects of pulse overshoot (10%, 20%), switching frequency (5 kHz, 10 kHz), and duty cycle (20%, 50%). Insulation performance was assessed through partial discharge inception voltage (PDIV) and dissipation factor (%DF) measurements before and after aging. Results showed the intensity of the turn-to-turn insulation damage of hairpin winding under PD activities caused by WBG drives.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.277
Teacher spread0.268 · 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

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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