Author
Listed:
- Alexis Geslin
(Stanford University
Stanford University
SLAC National Accelerator Laboratory)
- Le Xu
(Stanford University
SLAC National Accelerator Laboratory)
- Devi Ganapathi
(Stanford University
SLAC National Accelerator Laboratory)
- Kevin Moy
(Stanford University)
- William C. Chueh
(Stanford University
Stanford University
SLAC National Accelerator Laboratory)
- Simona Onori
(Stanford University
SLAC National Accelerator Laboratory)
Abstract
Laboratory ageing campaigns elucidate the complex degradation behaviour of most technologies. In lithium-ion batteries, such studies aim to capture realistic ageing mechanisms to optimize cell chemistries and designs as well as to engineer reliable battery management systems. In this study, we systematically compared dynamic discharge profiles representative of electric vehicle driving to the well-accepted constant current profiles. Surprisingly, we found that dynamic discharge enhances lifetime substantially compared with constant current discharge. Specifically, for the same average current and voltage window, varying the dynamic discharge profile led to an increase of up to 38% in equivalent full cycles at end of life. Explainable machine learning revealed the importance of both low-frequency current pulses and time-induced ageing under these realistic discharge conditions. This work quantifies the importance of evaluating new battery chemistries and designs with realistic load profiles, highlighting the opportunities to revisit our understanding of ageing mechanisms at the chemistry, material and cell levels.
Suggested Citation
Alexis Geslin & Le Xu & Devi Ganapathi & Kevin Moy & William C. Chueh & Simona Onori, 2025.
"Dynamic cycling enhances battery lifetime,"
Nature Energy, Nature, vol. 10(2), pages 172-180, February.
Handle:
RePEc:nat:natene:v:10:y:2025:i:2:d:10.1038_s41560-024-01675-8
DOI: 10.1038/s41560-024-01675-8
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