Thermal performance of liquid cooled and air cooled thermal ground plane-based battery thermal management systems for a high-power density Lithium-ion battery
Bibliographic record
Abstract
This work evaluates the performance of two battery thermal management systems (BTMS) based on thermal ground planes (TGP) in fast charging and high C-rate operation. The battery module considered consist of a matrix of cylindrical Li-ion cells sitting on four TGPs (also referred to as 2D flat heat pipe) for bottom-cooling. Heat is removed from the TGPs by coupling its extremity with a heat sink (air cooled) or a cold plate (liquid cooled). The battery module of 1.3 kWh is experimentally cycled with 0.7 C charge rate, 1 C and 2 C discharge rate in a CC-CV protocol. The thermal performances of the two heat-dissipation configurations are evaluated based on cell averaged temperatures, in-cell temperature differences and in-module temperature differences. The two systems showed comparable performances regarding the maximum cell averaged temperature. During the 2 C discharges, the maximum cell-averaged temperatures are $50^{\circ} \mathrm{C}$ and $54^{\circ} \mathrm{C}$ for air cooling and liquid cooling respectively, while the maximum in-module temperature difference are $8^{\circ} \mathrm{C}$ and $10^{\circ} \mathrm{C}$ respectively. These maximums all happen at the end of the CC phase of the cycling. This experimental work concludes that fast charging and high-power operation can be sustained with the use of TGPs. Also, given the comparable performances of the two heat dissipation configurations and the ease of implementation of air cooling, thermal ground planes can make air cooling a viable option in commercial electrical vehicle batteries.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".