Application of Jets and Vortex Generators to Improve Air-Cooling and Temperature Uniformity in a Simple Battery Pack
Bibliographic record
Abstract
Abstract In this paper, the problem of air cooling and temperature nonuniformity at the cell and pack level is addressed. Passive techniques are developed by integrating jet inlets and vortex generators (VGs) in a simple battery pack with the goal to achieve an effective cooling, and the desired temperature uniformity at the cell and pack level to less than 5 °C, without an increase in the required mass flow and power requirements. Moreover, various configurations of the developed techniques are assessed and compared. In order to achieve the objectives, computational fluid dynamics (CFD) is used to conduct numerical studies on the battery packs. The results concluded that by adding both the delta winglet (DW) vortex generator arrays and jet inlet arrays in the same configuration, improvements in temperature reduction and uniformity can be achieved. The results showed that the maximum temperature of the battery pack was reduced by ∼6% and the temperature uniformity at the pack level was increased by 24%. Additionally, a ∼37% improvement in the temperature uniformity at cell level was achieved.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".