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Record W4365129424 · doi:10.1109/tpel.2023.3266300

Efficient MPPT for BLDCM-Driven PV Pumping System Based on Ripple Correlation Control

2023· article· en· W4365129424 on OpenAlexafffund
Amir Khazaee, Amirnaser Yazdani, Hamidreza Mosaddegh Hesar, Bin Wu

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2023
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRippleControl theory (sociology)Maximum power point trackingPhotovoltaic systemControl systemCorrelationPhysicsControl (management)Computer scienceEngineeringElectrical engineeringMathematicsVoltageInverterArtificial intelligence

Abstract

fetched live from OpenAlex

A fast and parameter-intensive maximum power point tracking (MPPT) technique is presented for a photovoltaic (PV) water pumping system, driven by the brushless dc motor (BLDCM). The technique is based on the application of “ripple correlation control”. As an advantage, rather than artificial signal injection, the proposed technique employs the inherent perturbations introduced due to phase commutation and nonsinusoidal back-EMF of BLDCM to determine the maximum power points of the PV system. The technique can be simply employed for different configurations of BLDCM-based PV water pumping systems. Experiments are performed to demonstrate the effectiveness of the proposed technique.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 science0.0010.000
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 head0.009
GPT teacher head0.235
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 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

Citations18
Published2023
Admission routes2
Has abstractyes

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