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Record W4407899918 · doi:10.1109/ojpel.2025.3544908

A Soft-Switched High-Conversion-Ratio Quasi-Resonant Flying Capacitor DC–DC Converter

2025· article· en· W4407899918 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 Open Journal of Power Electronics · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSwitched capacitorElectrical engineeringCapacitorFlyback converterCharge pumpMaterials scienceOptoelectronicsEngineeringVoltageBoost converter

Abstract

fetched live from OpenAlex

This article presents a new flying capacitor-based quasi-resonant DC-DC converter topology for high step-down, low-power applications, ranging from fractions of a watt to tens of watts. The converter has a structure similar to that of a conventional three-level flying capacitor buck, but it operates in a fundamentally different manner, offering a favorable trade-off for many targeted applications. By allowing a small flying capacitor to fully charge and discharge between 0 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{in}$</tex-math></inline-formula>, using a unique switching scheme, switching losses are drastically reduced at the expense of requiring transistors rated for the full input voltage. The converter can operate in both discontinuous conduction mode (DCM) and continuous conduction mode (CCM). In DCM, soft switching is achieved on all edges, independent of operating conditions, while in CCM, soft switching occurs on most edges. The capacitor charging process causes the converter to draw a fixed amount of energy per switching cycle, resulting in a unified small-signal model and a transfer function with a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q_{o}$</tex-math></inline-formula> factor limited to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1/\sqrt{2}$</tex-math></inline-formula>, simplifying voltage-mode compensator design compared to standard buck solutions. The effectiveness of the introduced solution is verified through simulations and experimental prototypes, processing up to 50 W of power with varying inductor values. These prototypes were designed to explore trade-offs for different applications while maintaining a low converter volume and high power processing efficiency. Experimental results for a 48 V-to-1 V/4 A converter demonstrate peak efficiencies of 81.74% at 3 W, 87.36% for 48 V-to-2 V/10 A at 6.4 W, 89.87% for 48 V-to-3.3 V/10 A at 10.6 W, and 91.33% for 48 V-to-5 V/10 A at 16 W.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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