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Record W2996282178 · doi:10.1109/ojpel.2019.2959553

Design Oriented Analysis of Switched Capacitor DC–DC Converters

2019· article· en· W2996282178 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 · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConvertersSwitched capacitorRippleVoltage multiplierCapacitorElectronic engineeringPower (physics)CapacitanceVoltageComputer scienceElectrical engineeringEngineeringVoltage sourcePhysicsElectrodeDropout voltage

Abstract

fetched live from OpenAlex

A novel approach to the design of switched capacitor (SC) converters is presented in this article. By recognizing the relationship between three design parameters in SC converters, namely capacitance, switching frequency, and switch on-resistance, this work is able to align the design method of SC more closely with conventional power converters. Using the charge-multiplier framework for design, capacitor sizes can be related to one another and subsequently to output voltage ripple, a key design parameter of converters. Optimization tools are used to take the equations developed for hand calculation and enable a more broad generalization of how SC converters can be designed. Typically it is thought that the larger the voltage ripple in SC converters is, the less efficient the converter is. However, this design method shows that this is not necessarily the case. Experimental prototypes are designed with these tools to show the validity of the proposed method.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.688
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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