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Record W2133594633 · doi:10.1109/apex.2007.357507

Design and Performance of a Resonant LLC 48V Voltage Regulator Module with a Self-sustained Oscillation Controller

2007· article· en· W2133594633 on OpenAlexaff
Mohamed Z. Youssef, Praveen Jain

Bibliographic record

VenueConference proceedings/Conference proceedings - IEEE Applied Power Electronics Conference and Exposition · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsController (irrigation)Oscillation (cell signaling)Voltage regulatorVoltageEngineeringPower factorPower (physics)Resonant converterTransient (computer programming)Electronic engineeringControl theory (sociology)Electrical engineeringComputer scienceConvertersPhysicsControl (management)

Abstract

fetched live from OpenAlex

This paper presents the performance and design of a new 48V/1.5V Voltage Regulator Module (VRM) for the stand-alone high-end servers, and notebook computer applications. The proposed VRM is based on the LLC-type resonant converter as it possesses much lower component stresses compared with the conventional series and series-parallel resonant topologies. Self-sustained oscillation control (SSOC) operation is used to achieve voltage regulation and high efficiency for a wide range of load currents. It is a new current mode controller for resonant converter, hence offers lower power component ratings than with the conventional variable frequency (VF) controller and a very fast transient response. It allows a minimum power factor angle and consequently a smaller primary current to reduce conduction losses, leading to a better working efficiency. Analytical, simulation and experimental results of a 48V/1.5V 30W prototype are presented to offer the proof of concept.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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 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

Citations6
Published2007
Admission routes1
Has abstractyes

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