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Space Vector PWM Control of Dual Inverter Fed Open-End Winding Induction Motor Drive

2002· article· en· W2266162718 on OpenAlexaboutno aff
E. G. Shivakumar, K. Gopakumar, S.K. Sinha, André Pittet, V.T. Ranganathan

Bibliographic record

VenueEPE Journal · 2002
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsnot available
Fundersnot available
KeywordsControl theory (sociology)InverterPulse-width modulationInduction motorPhasorVoltageSpace vector modulationVector controlTransformerComputer scienceEngineeringPhysicsElectrical engineeringElectric power systemPower (physics)

Abstract

fetched live from OpenAlex

The technique of space vector PWM control of dual voltage source inverter fed three phase open-end winding induction motor is presented in this paper. A space vector PWM technique is developed based on the combination of space vectors from dual inverters feeding the induction motor from both ends (open-end winding without neutral point). A total of 64 voltage space vector combinations are available for PWM voltage control of the inverter fed machine with open-end winding A space phasor based PWM scheme is proposed with minimum number of switching in a cycle per inverter coupled with equal number of switching for each inverter. All the voltage space vector combinations are utilized for generating the reference voltage vector to cover the entire speed range. The open-end winding structure can have significant third harmonic currents unless suitable third harmonic filters are used to suppress it. The third harmonic currents are suppressed by using isolated transformers for both inverters.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.023
GPT teacher head0.216
Teacher spread0.193 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations109
Published2002
Admission routes1
Has abstractyes

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