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Record W2762443835 · doi:10.23919/cjee.2016.7933113

Evolution of single-phase power converter topologies underlining power decoupling

2016· article· en· W2762443835 on OpenAlexaff
Shuang Xu, Liuchen Chang, Riming Shao

Bibliographic record

VenueChinese Journal of Electrical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsDecoupling (probability)Network topologyPower factorElectronic engineeringAC powerConvertersTopology (electrical circuits)Computer scienceSwitched-mode power supplyControl theory (sociology)VoltageEngineeringElectrical engineeringControl engineering

Abstract

fetched live from OpenAlex

Single-phase power converters are widely used in electric distribution systems under 10 kilowatts, where the second-order power imbalance between the AC side and DC side is an inherent issue. The pulsating power is decoupled from the desired constant DC power, through an auxiliary circuit using energy storage components. This paper provides a comprehensive overview of the evolution of single-phase converter topologies underlining power decoupling techniques. Passive power decoupling techniques were commonly used in single-phase power converters before active power decoupling techniques were developed. Since then, active power decoupling topologies have generally evolved based on three streams of concepts: 1) current-reference active power decoupling; 2) DC voltage-reference active power decoupling; and 3) AC voltage-reference active power decoupling. The benefits and drawbacks of each topology have been presented and compared with its predecessor, revealing underlying logic in the evolution of the topologies. In addition, a general comparison has also been made in terms of decoupling capacitance/inductance, additional cost, efficiency and complexity of control, providing a benchmark for future power decoupling topologies.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.233
Teacher spread0.227 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

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