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Record W3080105835

MPPT Controlled Battery Charger Design and Simulation

2017· article· en· W3080105835 on OpenAlexaboutno aff
Bassam Al-Hanahi, Burak Akın

Bibliographic record

VenueMajlesi journal of energy management/Majlesi journal of mechatronic systems · 2017
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMaximum power point trackingDuty cycleBoost converterPhotovoltaic systemMaximum power principleBattery (electricity)Battery chargerĆuk converterPower (physics)InsolationMATLABElectrical engineeringComputer scienceEngineeringControl theory (sociology)Electronic engineeringVoltageInverterPhysicsControl (management)
DOInot available

Abstract

fetched live from OpenAlex

In this paper, the design of MPPT controlled DC-DC boost converter for PV charger application is presented.  Duty cycle of the designed boost converter, which operates in 50 KHz, is controlled directly by P & O algorithm in order to track maximum power point of the PV panel that is changing in response of variation insolation of sunny day. The designed Boost converter is used as interface unit for matching 24V battery bank (20AH, 12V, C/5) with CANADIAN SOLAR CS5C-90 panel. The overall system is built and validated by using MATLAB SIMULINK. The simulation results show that the average efficiency of proposed MPPT controlled DC-DC converter is 98.34%, which is calculated by comparing the tracked PV power by designed converter and the proposed maximum power of the panel for different level of insolation. The results express the effective operation of designed converter system by tracking MPP for PV panel in different insolation situations.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.260
Teacher spread0.239 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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Same venueMajlesi journal of energy management/Majlesi journal of mechatronic systemsSame topicPhotovoltaic System Optimization TechniquesFrench-language works237,207