Next Generation Materials for Lithium-Ion Space Batteries
Bibliographic record
Abstract
EaglePicher has been supplying batteries for energy storage for satellites and other space applications since 1958. These batteries have achieved over 2.6 billion hours of cell operations with no failures in orbit. Over the decades the battery chemistry has changed amongst various chemistries with some overlap and some still being used today. Typical space battery chemistries include: silver-zinc, nickel-hydrogen, nickel-cadmium, and then lithium-ion. Even within the lithium-ion chemistry the formulations and packaging has evolved over time and continues to change. Lithium-ion space batteries continue to evolve today. New satellites and space applications are demanding increased energy, more power, and smaller volumes. This has led to improvements in increased energy, wider operating temperatures, more power and smaller packages. Every change in battery performance requires new or modified battery materials. For increased energy the incumbent cathode material for lithium-ion batteries is Lithiated Nickel Cobalt Oxide (NCO). This was changed to the Lithiated Nickel Cobalt Aluminum Oxide to increase the energy and improve cycle life. For wider operating temperatures the electrolyte formulation has evolved with new components and additives. Newer and next generation satellites are carrying state of the art instruments that demand high power or pulses of power. New lithium-ion battery chemistries have been developed to supply very high power discharges to supply the large currents. As small satellites are increasing in popularity, there is a push for smaller battery packs. This has led to a decrease in cell capacity and the introduction of commercial of the shelf (COTS) cells. These are often cylindrical in shape and typically 18650 in size. Transitioning to COTS cells has increased the ability to create modular space batteries, but has brought up new concerns on quality and reliability. Quality and reliability, plus safety, are top concerns for space batteries. Replacement of batteries in space is extremely difficult and expensive. As each of the next generation battery materials are developed, reliability and safety much be eminent. These materials and batteries are often expected to supply power for decades. The continued testing, evaluation and analysis of the new chemistries and designs provides assurances for long-term performance and reliability. As these batteries have the potential to power satellites, landers, rovers, capsules, and habitats, EaglePicher continues to develop, evolve, demonstrate, and produce new battery chemistries and designs to meet the mission requirements. Acknowledgements We would like to thank: NASA JPL, Lockheed Martin and the Unites States Government for supporting some of this effort, and many of the EaglePicher employees who worked on these projects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".