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Record W1983308956 · doi:10.1109/intlec.2014.6972135

Measurement and equivalent circuit modeling of a lithium-ion cell

2014· article· en· W1983308956 on OpenAlexaff
Melody Shengru Ren, Chi-Wah Eddie Fok, John D. W. Madden, William G. Dunford

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEquivalent circuitCapacitanceMaterials scienceCapacitorEquivalent series resistanceLithium (medication)Electrical impedanceElectrodeTime constantElectrical engineeringAnalytical Chemistry (journal)VoltageChemistryEngineering

Abstract

fetched live from OpenAlex

Impedance spectroscopy, charge/discharge curves and pulsed current measurements are used to identify cell response as a function of voltage and frequency, and in turn to create a non-linear time domain circuit model of a cell. The cell studied incorporates a lithium nickel manganese cobalt electrode. Linear finite transmission line models are fitted to the frequency response to identify model parameters, including equivalent series resistance, charge transfer resistance, double layer capacitance and mass transfer resistance. The frequency response is obtained at a number of states of charge so that the dependence of these properties on state of charge can be estimated. Constant current charging is used to estimate effective capacitance as a function of state of charge. A non-linear capacitor in series with an equivalent circuit resistance effectively predicts cell time response to pulsed current inputs, except where gradients in local state of charge exist within electrodes.

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)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
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 head0.054
GPT teacher head0.252
Teacher spread0.197 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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