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Record W3211338056 · doi:10.1109/tie.2021.3127032

Integrated Transformerless EV Charger With Symmetrical Modulation

2021· article· en· W3211338056 on OpenAlexaff
Caniggia Viana, Sepehr Semsar, Mehanathan Pathmanathan, Peter W. Lehn

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInverterModulation (music)Leakage (economics)Electronic engineeringElectrical engineeringCommon-mode signalPower (physics)Computer scienceVoltageEngineeringPhysicsAcoustics

Abstract

fetched live from OpenAlex

This article introduces a modulation technique that nearly eliminates the common-mode (CM) leakage currents in the transformerless (nonisolated) dual-inverter single-phase charger. This improvement allows for the safe use and commercialization of the transformerless charger, making superior charger efficiency, power density, and cost possible. The CM model of the system is derived to guide the choice of the modulation scheme. Simulations are conducted to validate the CM performance predictions derived analytically. Finally, an experimental 6.6-kW charger prototype is presented to verify the CM leakage current elimination. The experimental results show not only that the proposed modulation meets the required standards regarding CM currents, but also that it does so by a wide margin, and it even outperforms the isolated system used for comparison.

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 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 score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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.

Study designOther design
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

Citations17
Published2021
Admission routes1
Has abstractyes

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