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Record W2947585286 · doi:10.1049/joe.2018.8178

Dual three‐phase permanent magnet synchronous machine investigation for battery electric vehicle power‐trains

2019· article· en· W2947585286 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

VenueThe Journal of Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
FundersOak Ridge National LaboratoryCanada Research Chairs
KeywordsTraction (geology)Automotive engineeringTorqueMagnetRotor (electric)Traction motorTorque densityAutomotive industryPower (physics)Computer scienceTrainSynchronous motorDirect torque controlElectrical engineeringEngineeringMechanical engineeringPhysicsVoltageInduction motorAerospace engineering

Abstract

fetched live from OpenAlex

A dual three‐phase machine with interior permanent magnet rotor and distributed winding has been studied and compared to a commercial automotive traction machine, the Nissan Leaf IPM machine. The performance of the two designs are compared for typical traction operating points, via high torque, low speed and low torque, high speed, and constant power field weakening operation. The dual three‐phase machine is shown to have improved torque density and torque quality without compromising efficiency.

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 score0.588
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.196
Teacher spread0.189 · 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