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Record W2911625067 · doi:10.1109/tie.2019.2893826

Hybrid Buck Converter With Constant Mode Changing Point and Smooth Mode Transition for High-Frequency Applications

2019· article· en· W2911625067 on OpenAlexaff
Bing Yuan, Mengxue Liu, Wai Tung Ng, Xinquan Lai

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsPulse-width modulationBuck converterVoltageControl theory (sociology)Operating pointModulation (music)Constant (computer programming)Mode (computer interface)Transient (computer programming)Constant currentPulse-frequency modulationMaterials scienceComputer scienceElectronic engineeringPhysicsElectrical engineeringEngineeringPulse (music)Pulse-amplitude modulationAcousticsControl (management)

Abstract

fetched live from OpenAlex

To achieve high frequency and high efficiency over a wide load range, a monolithic voltage-mode dc-dc buck converter with advanced burst mode (ABM) and pulsewidth modulation (PWM) is presented in this paper. The load current is detected by estimating the currents flowing through the high-side and low-side switches, which maintains a near constant mode changing point. A counter-based scheme is used to achieve seamless and smooth transition between PWM and ABM. Both operating modes share the same control blocks, and no additional zero current detecting circuit is needed. In addition, the output stage switch size can be adjusted to reduce switching loss and improve efficiency under ultra-light load conditions. Experimental results show that the integrated 3 MHz converter achieves high efficiency from 80 to 91%, over a wide load range from 0.001 to 5 A. When the switch size is set to 1/3 of the maximum value, an additional 5% efficiency improvement at under 0.1 A load can be realized. The mode changing point is set at 0.4 A with less than 10% variation when the input voltage changes from 3 to 5 V. The load transient response is also improved significantly.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations36
Published2019
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Industrial ElectronicsSame topicAdvanced DC-DC ConvertersFrench-language works237,207