(Invited) Safety Enhancements for Large Format, High Power, Lithium-Ion Cells and Batteries
Bibliographic record
Abstract
Batteries are inherently a complex electrical, chemical and mechanical system. For such systems, safety can not be a single-point problem; and addressing safety requires a semi-holistic approach to provide a meaningful advancement of system-level safety. The Yardney Technology Center of EaglePicher Technologies is focused on the advancement of large Lithium-ion systems for high power applications such as aircraft and Directed Energy systems; which requires a targeted approach to system-level safety. The effort has focused on cell chemistry and design aspects, battery/module mechanical and thermal designs, and other design features to enhance overall tolerance to abuse, limit cell-to-cell propagation, and mitigate impact to other systems. Cell-level chemical and physical design enhancements help reduce both the likelihood and severity of a safety event. Reduced flammability electrolytes and proper material selection help to reduce the secondary impacts of a thermal runaway event in a cell or battery. Mechanical design of the cells improve thermal management of any heat generation. Thermal management of these systems is required not only for safety enhancements, but the ability to quickly and uniformly heat cells provides for better operation in very low temperature environments (as low as -40⁰C), and rapid cooling of cells during high rate discharges allows for multiple pulses or quick recharges for the next pulse. Thus, designing cells with high surface area to volume ratios assist in transferring heat both into and out of the cells for improved performance and safety. Analyzing the thermal design aspects of modules and batteries has led to designs that can manage the thermal load from a single cell thermal runaway event and prevent propagation to nearest neighbors in a battery pack. Other battery-level design features, such as flame suppression materials and proper thermal venting of gasses provide an additional level of safety enhancements for high power batteries. The overarching goal of all of these enhancements is to mitigate the effects of an abuse event within the battery and control impact to exterior systems and personnel. Demonstration test results for all of these design enhancements in large-format cells and batteries will be presented.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.025 |
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".