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Record W1877102982 · doi:10.1109/pesc.2006.1712135

A novel concept of employing current source inverter in valley fill electronic ballasts with dimming capability and low crest factor

2006· article· en· W1877102982 on OpenAlexaff
John Lam, Praveen Jain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsCrest factorInverterPower factorElectronic engineeringEngineeringGrid-tie inverterInductorResonant inverterElectrical engineeringPower (physics)Current sourceComputer scienceCurrent (fluid)VoltageMaximum power point trackingPhysics

Abstract

fetched live from OpenAlex

A new concept of using current source resonant inverter in passive valley fill dimming electronic ballast with variable frequency control is presented in this paper. The advantage of using a current fed resonant inverter in the proposed power circuit is that it provides isolation to the driver circuit without the use of any isolation devices. When the proposed inverter is cascaded with the valley fill circuit to achieve power factor correction, the input inductors of the current source inverter introduce a new operating mode that is able to shape the input line current to achieve high power factor. A simple modified 555 timer is used in the variable frequency controller to continuously regulate the lamp current by changing the switching frequency of the resonant inverter. As a result, dimming operations and low lamp crest factor are achieved with high power factor to be maintained. A detailed description on the operating principles of the proposed circuit is given in this paper. Powersim (PSIM) simulation and experimental results are presented to highlight the performance of the proposed circuit for a 20W compact fluorescent lamp.

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)0.000
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: Empirical
Teacher disagreement score0.707
Threshold uncertainty score0.735

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 head0.006
GPT teacher head0.195
Teacher spread0.189 · 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.

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

Citations7
Published2006
Admission routes1
Has abstractyes

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