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Record W4402401523 · doi:10.1109/ojia.2024.3457505

A High-Efficiency Propulsion Motor With Distributed High-Density Winding Technology

2024· article· en· W4402401523 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

VenueIEEE Open Journal of Industry Applications · 2024
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPropulsionAutomotive engineeringAerospace engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

This article presents the development of an electric motor with the novel distributed high-density (DHD) winding technology. The DHD winding technology utilizes round wires instead of bar wires. Unlike conventional round-wire winding technique (shed winding), the wires are orderly positioned in the slots in the DHD winding technology, resulting in high fill factor and high efficiency. The implementation of a stator with the DHD winding is presented which utilizes state-of-the-art coil winding and assembly processes. To compare against existing stator designs, a 100 kW, 800 V, and 15 000 RPM propulsion motor is tested experimentally to validate the performance of the DHD winding technology. The acoustic noise behavior of the propulsion motor is also characterized experimentally. The motor efficiency with the DHD, hairpin, and shed windings is compared for the same stator geometry using simulation results to demonstrate the performance improvement with the DHD winding technology.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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