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Record W2094826597 · doi:10.1109/apec.2014.6803517

Assisting converter based integrated battery management system for low power applications

2014· article· en· W2094826597 on OpenAlexaff
Mahmoud Shousha, Timothy McRae, Aleksandar Prodić, Victor Marten

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFlyback converterBuck–boost converterFlyback transformerBattery (electricity)Electrical engineeringCapacitorBoost converterPower managementBuck converterComputer scienceVoltageForward converterInductorController (irrigation)Power (physics)Electronic engineeringPower management systemEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper introduces a new battery management system for portable electronics applications based on the flyback converter. This new architecture integrates the voltage step-up and balancing functions inside a single converter. The step-up function is obtained using an assisting concept, where the flyback output is placed at the top of the battery pack and is therefore only processing a portion of the output power. As a result, high power processing efficiency and small converter volume are achieved. The operation of the system is regulated by a digital controller that provides voltage regulation and charge balancing of the battery cells at the same time. Experimental results obtained with 8-to-12V, 20W, 250 KHz prototype demonstrate a peak efficiency of 93.4% and show that the assisting flyback requires about 9 times smaller output capacitor than the conventional boost while maintaining approximately the same inductor volume.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations12
Published2014
Admission routes1
Has abstractyes

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