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A New Fully Soft-Switched, Single-Stage LLC Resonant Based Grid Connected Inverter

2021· article· en· W3186519610 on OpenAlexaff
Parham Mohammadi, John Lam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsYork University
Fundersnot available
KeywordsInverterGalvanic isolationTotal harmonic distortionResonant inverterPulse-width modulationComputer scienceGrid-tie inverterHarmonicController (irrigation)VoltageLC circuitElectronic engineeringElectrical engineeringControl theory (sociology)EngineeringTopology (electrical circuits)PhysicsCapacitorMaximum power point trackingControl (management)AcousticsTransformer

Abstract

fetched live from OpenAlex

A new single-stage fully soft-switched resonant grid-connected inverter is proposed in this paper. The proposed inverter is able to provide ZVS turn-on for all the switches without requiring complex switching modulation or using additional passive auxiliary circuits. A front-end half-bridge LLC resonant inverter is connected to a high frequency AC link, where galvanic isolation is provided. On the secondary side of the high frequency AC link, two switch pairs are controlled with sinusoidal PWM and they are connected to an output LC-type filter to provide the required sinusoidal grid side current. The operating stages of the proposed circuit and the circuit’s characteristics are discussed. A closed loop control algorithm based on a proportional resonant and a harmonic compensator controller is implemented so that the output grid current is synchronized with the grid voltage and can achieve very low THD. Results are provided on 1.5kW system, an input voltage range of 200–300V and an AC output voltage of 120Vac,rms with a switching frequency of 103 kHz to validate the performance of the proposed inverter.

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: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.201
Teacher spread0.185 · 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
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

Citations3
Published2021
Admission routes1
Has abstractyes

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