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Record W1991852117 · doi:10.1109/apex.2007.357622

Direct PWM Synchronization Using An All Digital Phase-Locked Loop for High Power Grid-Interfacing Converters

2007· article· en· W1991852117 on OpenAlexaff
Dewei Xu, Yunwei Li, Bin Wu

Bibliographic record

VenueConference proceedings/Conference proceedings - IEEE Applied Power Electronics Conference and Exposition · 2007
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPulse-width modulationPhase-locked loopHarmonicsConvertersComputer scienceElectronic engineeringInterfacingJitterSynchronization (alternating current)Control theory (sociology)EngineeringVoltageElectrical engineeringComputer hardwareTopology (electrical circuits)

Abstract

fetched live from OpenAlex

For medium voltage high power grid-interfacing converters, the operating switching frequency is often around several hundred Hz to reduce the switching power losses. Therefore, to eliminate the even order harmonics and non-characteristic harmonics and to minimize the beat phenomenon, synchronous PWM techniques are desired for the high power low-switching converters. In this paper, a direct PWM synchronization method using an all digital phase-locked loop (ADPLL) is proposed for the grid-connected converter implementation. The control method is realized using a designed DSP-FPGA control system. The proposed ADPLL implemented in the FPGA has wide track-in range and fast pull-in time with an input frequency feed-forward loop. The phase error and pulse jitter is minimized by selecting a high clock frequency (150MHz). The synchronous PWM waveform can be generated effectively and conveniently by the ADPLL through external synchronized interrupt from FPGA to DSP at the desired sampling angle and switching frame starting angle. The proposed ADPLL synchronized PWM strategy has been verified experimentally using a 10kVA grid-connected PWM current source rectifier prototype.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0010.000
Research integrity0.0010.001
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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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 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

Citations10
Published2007
Admission routes1
Has abstractyes

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