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Record W2746532192 · doi:10.1109/tmag.2017.2661994

A Computational Study of Efficiency Map Calculation for Synchronous AC Motor Drives Including Cross-Coupling and Saturation Effects

2017· article· en· W2746532192 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.

Bibliographic record

VenueIEEE Transactions on Magnetics · 2017
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsSynchronous motorControl theory (sociology)Nonlinear systemComputer scienceExcitationSaturation (graph theory)TorqueCoupling (piping)Magnetic reluctanceFinite element methodElectric vehicleAC motorPhysicsMagnetControl (management)Mechanical engineeringMathematicsEngineeringPower (physics)

Abstract

fetched live from OpenAlex

After designing and optimizing an electric machine, efficiency maps are needed to predict a vehicle's performance in a dynamic simulation. Calculating efficiencies at various torque and speed points, however, requires prior knowledge of the input excitation conditions, such as the current magnitude and advance angle, in an electromagnetic finite-element analysis simulation. Hence, this paper derives and uses nonlinear motor control equations (MTPA, FW, MTPV) in the study of efficiency map calculation while accounting for both saturation and cross-coupling effects. Two synchronous ac motors are considered in this paper, including the 2010 Prius IPM and a PM-assisted synchronous reluctance machine, with all procedure steps outlined in detail.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.502
Threshold uncertainty score0.498

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 head0.014
GPT teacher head0.275
Teacher spread0.261 · 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