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Record W2077839022 · doi:10.1109/apec.2013.6520233

Sensorless control of a boost PFC AC/DC converter with a very fast transient response

2013· article· en· W2077839022 on OpenAlexaff
Majid Pahlevaninezhad, Pritam Das, Gerry Moschopoulos, Praveen Jain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsWestern UniversityQueen's University
Fundersnot available
KeywordsRippleBoost converterControl theory (sociology)Transient responseInductorComputer scienceĆuk converterTransient (computer programming)Buck–boost converterVoltageForward converterFlyback converterObservabilityElectronic engineeringEngineeringControl (management)Electrical engineeringMathematics

Abstract

fetched live from OpenAlex

This paper presents a novel approach to control a boost PFC AC/DC converter without using any current sensors. Due to the particular structure of the boost PFC AC/DC converter, sensorless control of the converter is very challenging. As illustrated in this paper, the converter loses its observability for some operating points. This is the reason that the sensorless control of the boost PFC entails special attentions. A very simple and practical senseless scheme is proposed in this paper, which is able to accurately estimate the inductor current for the entire operating range of the converter. In addition, a very simple and practical closed-loop control approach is proposed in order to improve the transient response of the single-phase boost PFC converter. This approach eliminates the need for filtering double frequency ripple from the output voltage, which allows increasing the bandwidth of the external voltage loop. Simulation and experimental results validate the feasibility of the proposed technique and confirm its superior performance compared to the conventional control system.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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 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

Citations17
Published2013
Admission routes1
Has abstractyes

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