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Record W2748370324 · doi:10.1109/compel.2017.8013397

DC ripple regulation of single-phase converters with reduced harmonic impact

2017· article· en· W2748370324 on OpenAlexaff
Caniggia Viana, Hannah Mundel, Theodore Soong, Peter W. Lehn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRippleCapacitorConvertersElectrolytic capacitorHarmonicElectronic engineeringFilter capacitorComputer scienceTopology (electrical circuits)AC powerCapacitancePhotovoltaic systemHarmonicsThree-phaseEngineeringElectrical engineeringVoltagePhysics

Abstract

fetched live from OpenAlex

Single-phase power converters are commonly employed to integrate renewable sources, such as solar PV or fuel cells, among other applications. However, they typically require large and limited lifetime electrolytic capacitors to filter large DC side ripple components, representing a limit for the power density and durability of converters, potentially making the technology unpractical for some applications. Alternatively, active filtering methods can be used to lower DC capacitor requirements and enable the use of durable film capacitors with minimum sizing. This paper presents a closed loop control strategy that applies single-input space vector theory in order to increase component utilization, and decrease AC harmonic content. A systematic approach is introduced to achieve DC side harmonic mitigation without increasing the DC side capacitance requirement. Simulation results are presented in Matlab/Simulink™ to compare two active filtering topologies using the proposed control with a conventional DC-AC single-phase topology.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.270
Teacher spread0.250 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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