MétaCan
Menu
Back to cohort

A Novel High Step-up Voltage Gain DC-DC Converter with Low Source Current Ripple

2022· article· en· W4323895121 on OpenAlexaff
Motiur Reza Mohammed, Malik Abdul Haleem, Apparao Dekka, Deepak Ronanki, Abdul R. Beig

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsLakehead University
Fundersnot available
KeywordsRippleBoost converterInductorĆuk converterDuty cycleVoltage multiplierConvertersForward converterElectronic engineeringVoltageElectrical engineeringBuck–boost converterDiodeVoltage sourceComputer scienceTopology (electrical circuits)EngineeringDropout voltage

Abstract

fetched live from OpenAlex

In this paper, an interleaved boost converter topology with a high step up voltage gain and low source current ripple is proposed. The current in two interleaved inductors are controlled in phase opposition manner such that the ripple in the source current reduces by a greater extent. The operating principles and the steady state analysis of the proposed converter are presented in detail. The proposed converter offers high step up voltage gain in the full range of duty cycle in comparison to the existing boost converters. Furthermore, the voltage stress across the active switches, diodes and passive elements is low. The feasibility of the proposed converter is validated through experimental studies on a developed 400 W laboratory prototype to stepup the voltage from 25 V to 400 V.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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
GenreMethods

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

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced DC-DC ConvertersFrench-language works237,207