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High Performance Gate-Driver Power Supply for Multilevel-based 1500 V Converters

2020· article· en· W3095387010 on OpenAlexaff
Emanuel Serban, Mohammad Ali Saket, Martin Ordonez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGate driverElectronic engineeringElectrical engineeringTransformerBoost converterConvertersIsolation transformerEngineeringInductorLeakage inductanceTopology (electrical circuits)Computer scienceVoltage

Abstract

fetched live from OpenAlex

Power semiconductor devices require advanced pulse-width gate-driver capability to successfully convert power for high performance operation. In this paper, a simplified forward isolated converter topology with an integrated planar transformer is proposed, which eliminates the need of output filter inductor while rearranging the clamp circuit for reduced components ratings and voltage stress in a cost-effective solution. The proposed single-switch forward converter topology employs switch protection and transformer core demagnetization with Zener diode voltage-clamped circuit. Through the converter analysis, the switching frequency has been selected in relationship to the transformer inductance and the equivalent circuit capacitance for the benefit of soft-switching devices transitions. The converter features multiple isolated secondaries necessary for independent gate-driver voltage supplies in multi-level converters. Specifically, the proposed converter provides voltage supplies for a gate-driver power devices pair, such as half-bridge SiC devices. The integrated solution reduces the total number of gate-drivers transformers necessary in multilevel-based 1500V converters. The simulation and experimental results are obtained from a gate-drive application platform to demonstrate the validity of the proposed isolated dc-dc converter design with integrated planar transformer.

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), Insufficient payload (model declined to judge)
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 score0.799
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)0.0010.000

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 head0.015
GPT teacher head0.190
Teacher spread0.175 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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