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Record W4225555920 · doi:10.1109/jestie.2022.3159474

Analysis and Design of Efficient Interleaved Bidirectional Converter With Winding Cross Coupled Inductors

2022· article· en· W4225555920 on OpenAlexaff
Afshin Amoorezaei, Mohammad Reza Mohammadi, S. Ali Khajehoddin, Kambiz Moez, Adib Abrishamifar

Bibliographic record

VenueIEEE Journal of Emerging and Selected Topics in Industrial Electronics · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInductorRippleBoost converterElectronic engineeringVoltageElectronic circuitBuck converterTopology (electrical circuits)Buck–boost converterHigh voltageComputer scienceElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

This article presents a nonisolated bidirectional converter (BDC) with high voltage conversion ratio. The structure of winding-cross-coupled-inductors (WCCIs) is developed in the two-phase interleaved BDC to achieve the excellent features of current-ripple-cancellation, current sharing, and high voltage-gain. Furthermore, the proposed topology uses two active and passive clamp circuits to recover the coupled inductors’ leakage energy and to maintain the overall efficiency at a high level providing zero voltage switching (ZVS) in boost mode. A rearrangement is applied to high-voltage-side switches to avoid the interference of clamp circuits operation in boost and buck modes. Detailed analysis and design methodology of the proposed converter are provided and a high gain 500 W, 48 V/380 V prototype is implemented to verify the performance of the proposed converter. Peak efficiencies of 96% and 94.3% are measured for boost and buck modes, respectively.

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 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: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.241
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

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