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Record W4283588590 · doi:10.11159/ffhmt22.190

Hydrothermal Performance of Liquid-Cooled Battery Thermal Management System with Multiple Inlets

2022· article· en· W4283588590 on OpenAlexvenueno aff
Kuuku-Dadzie Botchway, Mohammad Reza Shaeri

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsnot available
FundersCore Research for Evolutional Science and TechnologyNuclear Safety and Security CommissionNational Aeronautics and Space AdministrationU.S. Department of EnergyNational Science Foundation
KeywordsInletThermalPower (physics)Pressure dropLaminar flowVolumetric flow rateMarine engineeringMaterials scienceMechanical engineeringEnvironmental scienceMechanicsEngineeringMeteorologyPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Heat transfer and pumping power of water-cooled thermal management systems (TMSs) for lithium-ion batteries (LIBs) in electric vehicles (EVs) are investigated through a three-dimensional computational approach. TMSs are cylindrical shells that cover LIBs. Water flows through the shell and removes heat from LIBs. The focus of this study is to provide practical insights on the effects of number of inlets on the thermal performance and pumping power of TMSs. Two TMSs with one and four inlets at the top of the TMS's case are considered. Both TMSs include one outlet, which is located at the bottom of the case. The thermal performance of individual TMSs is evaluated by the maximum temperature of the battery cell and the temperature difference across the cell. The thermal performances are described based on the pumping power. Simulations are performed at different flow rates within a laminar regime. Results indicate that both TMSs provide safe operational temperatures for LIBs. However, compared to the one-inlet design, the four-inlet TMS archives the same thermal performance but at a lower pumping power. The lower pumping power is due to lower pressure drop in the four-inlet TMS resulting from flowing water with lower flow rate at individual inlets, and through a shorter path from individual inlets to the outlet, compared with the one-inlet TMS. Minimizing pumping power without any penalty in the thermal performance is significantly beneficial, especially when the TMS is used for a pack of LIBs in EVs.

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 score0.400
Threshold uncertainty score0.512

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 science0.0010.000
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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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