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Record W3131952974 · doi:10.1049/iet-pel.2020.0594

Logic‐based space‐vector modulation for neutral‐point‐clamped multilevel inverter with DC‐link voltage balancing capability

2020· article· en· W3131952974 on OpenAlex
Jalal Amini, Mehrdad Moallem

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

VenueIET Power Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLink (geometry)Modulation (music)Space vector modulationVoltageInverterComputer sciencePoint (geometry)Space vectorControl theory (sociology)Electronic engineeringTopology (electrical circuits)EngineeringElectrical engineeringMathematicsPhysicsComputer networkArtificial intelligence

Abstract

fetched live from OpenAlex

This study proposes a new simple and fast space‐vector modulation scheme with the capability of balancing capacitor voltages in neutral‐point‐clamped converters. In the first step, transformations from the commonly used reference frames to the 60°‐frame are discussed. Next, a new method is presented to generate an appropriate switching sequence based on the voltage of the clamp point and direction of the phase currents. The proposed method is computationally efficient and its algorithm only needs knowledge of the load current directions, leading to further simplification of the hardware. This method can easily be generalised to control diode‐clamped multilevel inverters with an arbitrary number of levels. The feasibility, effectiveness, and performance of the method are investigated through simulation and experimental studies under various load conditions.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.874
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 integrity0.0000.000
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 head0.212
Teacher spread0.197 · 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