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Record W4389584494 · doi:10.1109/tie.2023.3337542

Continuous Input Current Isolated Resonant LED Driver With Wide Input Voltage Range

2023· article· en· W4389584494 on OpenAlexafffund
Navid Molavi, Shirin Askari, Hosein Farzanehfard, S. Ali Khajehoddin

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Alberta
FundersCanada First Research Excellence Fund
KeywordsLED circuitElectrical engineeringVoltageRippleDuty cycleConstant currentLight-emitting diodeTransformerDiodeInductorLED lampElectronic engineeringEngineeringTopology (electrical circuits)

Abstract

fetched live from OpenAlex

In this article, an isolated resonant light-emitting diode (LED) driver featuring inherent constant output current characteristic at fixed frequency operation is presented. The LED current is regulated using the main switches operating duty cycle within a wide input voltage range variation while the integrated step-up structure brings continuous input current with low current ripple suitable for battery operation. The proposed isolated CLLC resonant network incorporates the transformer magnetizing and leakage inductances as the main resonant components leading to a lower number of magnetic components while improving the power density. Also, the zero-voltage-switching operation for the main switches and zero-current switching of the rectifier diodes are realized in the entire input voltage range. A detailed theoretical analysis of the proposed LED driver is presented. To verify the analysis and effectiveness of the proposed topology, a 100-W laboratory prototype with input voltage range of 35–60 V dc is designed and implemented for 48-V dc automotive applications which delivers 1 A current to a high brightness light emitting diode string including 30 series LEDs.

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 score0.003
Threshold uncertainty score0.011

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 communication0.0010.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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

Citations10
Published2023
Admission routes2
Has abstractyes

Explore more

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