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Record W2043200273 · doi:10.1080/15325008.2014.890975

A Fixed-frequency Series-parallel Resonant Converter with Capacitive Output Filter: Analysis, Design, Simulation, and Experimental Results

2014· article· en· W2043200273 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

VenueElectric Power Components and Systems · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSINADRBuck–boost converterĆuk converterFlyback converterForward converterBoost converterIntegrating ADCConvertersElectronic engineeringCapacitive sensingSeries (stratigraphy)Filter (signal processing)VoltageControl theory (sociology)EngineeringComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

In this article, a fixed-frequency phase-shift-controlled full-bridge series-parallel (or LCC-type) resonant converter that uses a capacitive output filter is proposed. Steady-state analysis of this converter is performed by using a complex AC circuit analysis approach. Based on the analysis, a simple design procedure is given and exemplified with a design example of a 200- to 220-V DC input, 300-W, 100-V output converter. The relationship between the design parameters, switch stresses, and converter size is illustrated. Both computer simulation and experimental results on a lab prototype converter are presented to verify the performance of the designed converter for varying input voltage and load conditions. It is shown that this converter requires a narrow variation in pulse width for a wide variation in the load, while the peak current through the switches decreases with the load current. One typical application of this converter is for use as a second stage for AC-to-DC converters.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.804
Threshold uncertainty score0.998

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 head0.016
GPT teacher head0.215
Teacher spread0.200 · 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