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Record W3118517066 · doi:10.3390/electronics10020106

Active Gate Driver and Management of the Switching Speed of GaN Transistors during Turn-On and Turn-Off

2021· article· en· W3118517066 on OpenAlex

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

VenueElectronics · 2021
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSlew rateSwitching timeGate driverTransistorVoltagePower (physics)High-electron-mobility transistorTurn (biochemistry)Electrical engineeringControl theory (sociology)Computer scienceEngineeringElectronic engineeringControl (management)Physics

Abstract

fetched live from OpenAlex

The paper investigates the management of drain voltage and current slew rates (i.e., dv/dt and di/dt) of high-speed GaN-based power switches during the transitions. An active gate voltage control (AGVC) is considered for improving the safe operation of a switching cell. In an application of open-loop AGVC, the switching speeds vary significantly with the operating point of the GaN HEMT on either or both current and temperature. A closed-loop AGVC is proposed to operate the switches at a constant speed over different operating points. In order to evaluate the reduction in the electromagnetic disturbances, the common mode currents in the system were compared using the active and a standard gate voltage control (SGVC). The closed-loop analysis carried out in this paper has shown that discrete component-based design can introduce limitations to fully resolve the problem of high switching speeds. To ensure effective control of the switching operations, a response time fewer than 10 ns is required for this uncomplex closed-loop technique despite an increase in switching losses.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.406

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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