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Record W1830149700 · doi:10.1109/pesc.2006.1712244

A low-power DC-DC converter with digital spread spectrum for reduced EMI

2006· article· en· W1830149700 on OpenAlexafffund
Olivier Trescases, Guowen Wei, Wai Tung Ng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEMIDuty cycleRipplePulse-width modulationElectronic engineeringInductorVoltageElectromagnetic interferenceElectrical engineeringDelta-sigma modulationBuck converterComputer sciencePhysicsEngineeringCMOS

Abstract

fetched live from OpenAlex

This paper presents a 1.8 V step-down DC-DC converter prototype with a hybrid delay-line based digital pulse-width modulator. A spread spectrum clock generation scheme is demonstrated for reducing EMI. The switching frequency of the buck converter prototype is automatically varied from 1.74 MHz to 2.84 MHz in 128 steps using a pseudo-random 512 cycle pattern, resulting in a 23 dB reduction in the conducted EMI peak. The digital pseudo-random pattern is converted to an analog reference voltage using a low-cost one-bit delta-sigma DAC having an over-sampling rate of 4096. The DAC output modulates the reference voltage of an LDO that regulates the delay-line supply voltage. It is shown that the effective duty-cycle changes by only 0.27 % over the frequency range. With spread spectrum mode enabled, the inductor current ripple becomes time-dependent but the efficiency degrades by less than 0.1%. The proposed architecture can be applied to a wide variety of state-of-the-art digital controllers that rely on delay-line based pulse width modulators.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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 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

Citations35
Published2006
Admission routes2
Has abstractyes

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