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Record W2989633012 · doi:10.1109/tte.2019.2956355

A Review on Multiphase Drives for Automotive Traction Applications

2019· review· en· W2989633012 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 Transactions on Transportation Electrification · 2019
Typereview
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutomotive industryTraction (geology)Computer scienceNetwork topologyDual (grammatical number)Process (computing)Electric vehicleEngineeringAutomotive engineeringControl engineeringMechanical engineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

This article attempts to cover the most recent advancements in multiphase drives (MPDs), which are candidates for replacing three-phase drives in electric vehicle (EV) applications. Multiphase machines have distinctive features that arouse many research directions. This article reviews the recent advancements in several aspects such as topology, control, and performance to evaluate the possibility of exploiting them more in EV applications in future. The six-phase drives are extensively covered here because of their inherent structure as a dual three-phase system, which eases the production process. This article presents different topologies used in dual three-phase drives and the modulation techniques used to operate them as well as the status of using MPDs in traction applications industrially and the upcoming trends toward promoting this technology more.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.049
GPT teacher head0.316
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