Thermal behaviour of Li-ion battery: An improved electrothermal model considering the effects of depth of discharge and temperature
Bibliographic record
Abstract
The current paper presents a two-dimensional electrothermal model that evaluates the thermal and voltage behaviour of a LiFePO 4 -20 Ah Li-ion pouch cell. The electrothermal model considers the impact of depth of discharge (DoD) and temperature on heat generated inside Li-ion cells by precisely simulating the internal equivalent resistance and entropy change utilizing experimental data. The proposed electrothermal model is validated utilizing experimental data. The results for the temperature estimation utilizing the electrothermal model show a similar result for all discharge current rates. The temperature prediction for all the discharge current rates (C-rate) shows slightly more accurate and precise results toward the end of discharge of Li-ion pouch cell. Overall, the absolute maximum relative error for the temperature prediction is around 6.30 % at 4C discharge rate. Similarly, the voltage estimation shows a high level of accuracy compared to the experimental data, and the simulated voltage has slightly higher values than the experimental voltage data, but the voltage trend is similar to the experimental data. Overall, the simulated results obtained from the proposed electrothermal model exhibit similar trends and high accuracy when compared to the experimental data.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".