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Record W2149102138 · doi:10.1109/tpel.2006.882922

A New Duty Cycle Control Strategy for Power Factor Correction and FPGA Implementation

2006· article· en· W2149102138 on OpenAlex

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

VenueIEEE Transactions on Power Electronics · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsToronto Metropolitan UniversityQueen's University
Fundersnot available
KeywordsDuty cycleBottleneckElectronic engineeringVoltageField-programmable gate arrayPower factorInductorComputer scienceDigital controlControl theory (sociology)EngineeringElectrical engineeringControl (management)Computer hardwareEmbedded system

Abstract

fetched live from OpenAlex

The bottleneck of digital control for power factor correction (PFC) implementations is mainly due to three aspects: high calculation requirements, high cost, and limited switching frequency compared with analog implementations. A new duty cycle control strategy for boost PFC implementations is proposed in this paper. The duty cycle is determined based on the input voltage, reference output voltage, inductor current, and reference current. The duty cycle determination algorithm includes two terms, the current term and the voltage term, which can be calculated in parallel and requires only one multiplication and three additions (subtractions) operations in digital implementation. A 400-kHz switching frequency boost PFC based on field programmable gate array implementation and its test results show that the proposed new duty cycle control strategy has great potential in the next generation of high switching frequency PFC implementations, due to its lower calculation requirement, lower cost, and better performance than the conventional PFC control methods

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 categoriesMeta-epidemiology (narrow)
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 score0.979
Threshold uncertainty score1.000

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 head0.005
GPT teacher head0.237
Teacher spread0.232 · 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