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Record W2125046441 · doi:10.1109/tia.2009.2031890

High-Quality Single-Phase Power Conversion by Reconsidering the Magnetic Components in the Output Stage—Building a Better Half-Bridge

2009· article· en· W2125046441 on OpenAlexafffund
C. Chapelsky, John Salmon, Andrew M. Knight

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2009
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsTotal harmonic distortionInductorTopology (electrical circuits)Audio power amplifierRippleH bridgeElectronic engineeringEngineeringElectromagnetic coilAmplifierPower (physics)InverterElectrical engineeringComputer scienceVoltagePhysics

Abstract

fetched live from OpenAlex

A novel half-bridge switching topology is presented which is based on using a split-wound series-connected coupled-winding inductor, interleaved switching, and zero-deadtime operation to achieve multilevel pulsewidth-modulation output with a reduced part count, reduced current ripple, and improved total harmonic distortion (THD) performance. This new topology is presented to highlight the design process for low-power high switching frequency designs requiring high performance, where circuit size and complexity are normally limiting factors. The design process demonstrated includes considering the current performance characteristics of the inverter and the design of the coupled-winding inductor. Design tradeoffs that are unique to this topology are explored that allow optimized designs for electrical performance, magnetic component size, or system losses. The benefit of the new topology is demonstrated using a case design for a class-D audio power amplifier, which shows a reduction in open-loop THD + N to as low as 0.29%.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score0.772

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 integrity0.0000.001
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 head0.081
GPT teacher head0.275
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations39
Published2009
Admission routes2
Has abstractyes

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