MétaCan
Menu
Back to cohort
Record W2957249192 · doi:10.18280/ejee.210218

A Farah Charging System Based on Constant Power Supply

2019· article· en· W2957249192 on OpenAlexvenueno aff
Hongyi Xiao, Rui Li

Bibliographic record

VenueEuropean Journal of Electrical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicIoT-based Smart Home Systems
Canadian institutionsnot available
Fundersnot available
KeywordsPower (physics)Constant (computer programming)Electrical engineeringEnvironmental scienceAutomotive engineeringPhysicsEngineeringComputer scienceThermodynamics

Abstract

fetched live from OpenAlex

The efficiency and time of charging are critical to the application of Farad capacitor. To reduce the loss and enhance the efficiency of Farad capacitor charging, this paper designs a constant power charging system for Farah capacitor based on negative feedback control. Centering on KEAZN64 microprocessor, the system collects the charging voltage and current in real time, which are processed by the microprocessor using the proportional-integral-derivative (PID) algorithm. Then, the microprocessor outputs pulse-width modulation (PWM) signals. Under the control of these signals, the half-bridge drive circuit realizes the constant power charging of Farad capacitor bank. Several experiments were conducted to compare the charging efficiency and time of three charging modes on a Farad capacitor bank, namely, constant voltage charging, constant current charging and constant power charging. The experimental results show that the constant power charging outperformed the other two modes, and the proposed system could charge the Farad capacitor bank with a constant power between 1~60W. The charging efficiency of the system reached 96%. The research findings provide a strong technical support for the promoting of Farad capacitor.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.153
Teacher spread0.150 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Electrical EngineeringSame topicIoT-based Smart Home SystemsFrench-language works237,207