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Record W2980489123 · doi:10.1115/1.4045193

Experimental Study of a Thermal Cooling Technique for Cylindrical Batteries

2019· article· en· W2980489123 on OpenAlexafffund
Yuyang Wei, Martin Agelin‐Chaab

Bibliographic record

VenueJournal of Electrochemical Energy Conversion and Storage · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoolantWater coolingNuclear engineeringAir coolingActive coolingMaterials scienceComputer coolingPhase-change materialRange (aeronautics)ThermalAir conditioningFree coolingPassive coolingEvaporative coolerEnvironmental scienceIonLithium (medication)Mechanical engineeringAutomotive engineeringThermodynamicsChemistryComposite materialEngineeringThermal management of electronic devices and systemsPhysics

Abstract

fetched live from OpenAlex

Abstract Lithium-ion (Li-ion) batteries have been considered the most promising power source for road transportation. However, the performance and lifespan of Li-ion batteries are strongly dependent on the working temperature. The optimal working temperature is usually within a narrow range, from 25 to 40 °C, and the non-uniformity is usually required to be lower than 5 °C. Therefore, the industry is seeking a thermal management system that is lightweight, simple-structure, energy-saving, and environmentally friendly. Air-cooling, liquid-cooling, and phase-change material (PCM) are the three most common cooling methods in the literature. In this study, a new concept of hybrid-cooling which utilizes all the three cooling methods is proposed. The concept can use either normal tap water or the condensate from a vehicle’s air-conditioner as the coolant source. Also, the coolants can be released back to the ambient environment instead of a coolant recirculation system to reduce weight and complexity. The concept was studied in detail experimentally using the 26,650 Li-ion batteries. The results indicate that the proposed hybrid-cooling concept reduced the maximum surface temperature by about 83%, 70%, and 57% compared with the other three cooling methods: the no-cooling, air-cooling, and water-cooling test results, respectively. Additionally, the concept successfully maintained the temperature uniformity below the recommended 5 °C.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.357

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 head0.008
GPT teacher head0.247
Teacher spread0.238 · 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 designBench or experimental
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

Citations8
Published2019
Admission routes2
Has abstractyes

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