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Record W3203221962

A new high speed charge and high efficiency li-ion battery charger interface using pulse control technique in TSMC 180 nm CMOS technology

2022· article· en· W3203221962 on OpenAlexaff
Mustapha El Alaoui, Karim El Khadiri, Rachid El Alami, Ahmed Tahiri, Ahmed Lakhssassi, Hassan Qjidaa

Bibliographic record

VenueInternational Journal of Electrical and Computer Engineering (IJECE) · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsCMOSBattery (electricity)VoltageElectrical engineeringTrickle chargingMaterials scienceCadenceIonOptoelectronicsPulse (music)Charge controlPower (physics)PhysicsElectronic engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

A new Li-Ion Battery Charger Interface (B. C. I.) using Pulse Control (P. C.) Technique is designed and analyzed in this paper. Thanks to the use of Pulse Control Technique, the main standards of the Li-Ion battery charger, i.e. fast charge, small surface area and high efficiency, are achieved. The proposed charger achieves full charge in forty-one minutes passing by the constant current (C. C.) charging mode which also included the start-up and the constant voltage mode (C. V.) charging mode. It designed, simulated and layouted which occupies a small size area 0.1mm 2 by using TSMC 180 nm CMOS technology in Cadence Virtuoso software. The battery voltage V BAT varies between 2.9V to 4.35V and the maximum battery current I BAT is 2.1A in C. C. charging mode, according to a maximum input voltage V IN equal 5V. The maximum charging efficiency reaches 98%.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.229
Teacher spread0.224 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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