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A Comparative Study of Control-Oriented Thermal Models for Cylindrical Li-Ion Batteries

2019· article· en· 135 citations· W2991063206 on OpenAlex· 10.1109/tte.2019.2953606

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Bench or experimentalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: none
Teacher disagreement score
0.517
Threshold uncertainty score
0.766
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

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)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.024
GPT teacher head0.279
Teacher spread
0.256 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

An accurate control-oriented thermal model is of extreme importance for temperature monitoring and thermal management of lithium (Li)-ion batteries in automotive and grid applications. This article, for the first time, presents a comprehensively comparative study of seven representative control-oriented thermal models for cylindrical Li-ion batteries. These models were selected from the state-of-the-art simplified models reported in the existing literature. All these models are introduced in detail. The model assumptions of physical structure, heat generation, and heat conduction are analyzed. Particle swarm optimization (PSO) algorithm is utilized to identify model parameters. Modeling fidelity is evaluated and compared using both simulation campaigns and experimental data sets of cylindrical Li-iron phosphate batteries. The sensitivity of all 1-D models to convective heat transfer coefficient (or convective heat resistance) is quantitatively analyzed, and the computational complexity of the models is compared under a real drive cycle. All the comparisons are thoroughly discussed, and useful insights are provided.

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.

The record

Venue
IEEE Transactions on Transportation Electrification
Topic
Advanced Battery Technologies Research
Field
Engineering
Canadian institutions
Ontario Tech University
Funders
National Natural Science Foundation of China
Keywords
Particle swarm optimizationConvectionThermalThermal conductionComputer scienceHeat transferLithium (medication)Materials scienceAutomotive industryMechanical engineeringConvective heat transferNuclear engineeringSimulationAlgorithmMechanicsAerospace engineeringEngineeringThermodynamicsPhysicsComposite material
Has abstract in OpenAlex
yes