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Record W2159909447 · doi:10.1109/tie.2009.2038939

A New Space-Vector PWM With Optimal Switching Selection for Multilevel Coupled Inductor Inverters

2010· article· en· W2159909447 on OpenAlexaff
Behzad Vafakhah, John Salmon, Andrew M. Knight

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2010
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInductorPulse-width modulationRippleCommon-mode signalInverterControl theory (sociology)WaveformVoltageModulation (music)Electronic engineeringComputer scienceEngineeringPhysicsElectrical engineeringDigital signal processingControl (management)

Abstract

fetched live from OpenAlex

Multilevel space vector pulsewidth modulation (SVPWM) control is shown to be a very useful tool for coupled inductor inverters as six independent pulsewidth modulation (PWM) signals are required, and there is additional complexity of meeting the performance requirements for the coupled inductor while balancing the winding common-mode dc current and generating high-quality multilevel PWM output voltages. A new multilevel SVPWM technique with a five-segment switching sequence is described, where half-wave symmetrical PWM voltage waveforms are used to balance the inductor common-mode dc voltages and also to avoid all possible switching states with a high winding current ripple. The proposed SVPWM is shown to have better inverter performance, compared with traditional carrier-based and the original multilevel SVPWM schemes at low modulation depths. Inverter operation with the proposed SVPWM is validated through simulation and experimental results.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.822
Threshold uncertainty score1.000

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 integrity0.0010.002
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 head0.020
GPT teacher head0.220
Teacher spread0.200 · 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 teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations52
Published2010
Admission routes1
Has abstractyes

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