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Record W2136678985 · doi:10.1109/apec.2010.5433682

One-step digital dead-time correction for DC-DC converters

2010· article· en· W2136678985 on OpenAlex
Anyang Zhao, Arash A. Fomani, Wai Tung Ng

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConvertersDead timeComputer scienceDigital controlElectronic engineeringMOSFETPower (physics)Buck converterPower MOSFETController (irrigation)VoltageControl theory (sociology)EngineeringElectrical engineeringControl (management)TransistorPhysics

Abstract

fetched live from OpenAlex

This paper introduces a novel one-step digital control technique that can dynamically optimize the dead-times for the turn-on and turn-off of the power MOSFETs in DC-DC converters. A NOR gate and a delay-line circuit are used to detect and measure the duration of the unwanted low-side MOSFET body-diode conduction. Based on this measurement, the optimum dead-time is calculated on-the-fly and the DPWM controller will respond immediately to maximize the conversion efficiency in the next switching cycle. This approach is well suited for digital IC implementation. Experimental results from a digitally controlled 6V to 1V, 10A synchronous buck converter verified the efficiency improvement and the practical implementation of the proposed one-step dead-time correction algorithm. This one-step dead-time correction can improve the converter's efficiency by 2 to 4%, depending on output current, output voltage and switching frequency.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.770

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)0.0000.001

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Quick stats

Citations32
Published2010
Admission routes1
Has abstractyes

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