A Novel Battery Thermal Management System based on Capillary Driven Evaporative Cooling
Bibliographic record
Abstract
In this paper we present an experimental and a numerical study on a novel battery thermal management system (BTMS) based on capillary driven evaporative cooling (CDEC).The experimental study was conducted using Cu foam and Novec 7000 to determine the cooling performance of this system when cooled through a single surface of the battery at three different heating inputs: 10W, 20W and 30W.The system was further expanded to incorporate cooling from the two larger surfaces of the battery using a numerical model.Results from the experimental study showed that the maximum temperature of battery can be maintained below 50℃ for a heat input of 30W, when the cell is cooled using a single surface.This was further reduced to 40℃ when cooled from both surfaces.Furthermore, these temperatures were achieved through partial wetting of the battery surface due to a capillary rise of about 11% of the total battery height.This clearly demonstrates the superior cooling capabilities of this novel BTMS.However, the maximum temperature different recorded in the battery at a heat input of 30W was 5.47℃ which was a result of the uneven cooling rates in the wetted and nonwetted regions of the battery due to partial capillary rise.
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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".