Zobrazeno 1 - 6
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pro vyhledávání: '"Zhou, Kate Qi"'
Publikováno v:
Journal of Energy Storage, Volume 100, Part A, 15 October 2024, 113502
Data-driven methods have gained extensive attention in estimating the state of health (SOH) of lithium-ion batteries. Accurate SOH estimation requires degradation-relevant features and alignment of statistical distributions between training and testi
Externí odkaz:
http://arxiv.org/abs/2409.00141
Publikováno v:
IEEE Transactions on Transportation Electrification, 2023
Lithium-ion batteries (LiBs) degrade slightly until the knee onset, after which the deterioration accelerates to end of life (EOL). The knee onset, which marks the initiation of the accelerated degradation rate, is crucial in providing an early warni
Externí odkaz:
http://arxiv.org/abs/2304.00691
Accurately estimating a battery's state of health (SOH) helps prevent battery-powered applications from failing unexpectedly. With the superiority of reducing the data requirement of model training for new batteries, transfer learning (TL) emerges as
Externí odkaz:
http://arxiv.org/abs/2208.11204
The state of health (SOH) estimation plays an essential role in battery-powered applications to avoid unexpected breakdowns due to battery capacity fading. However, few studies have paid attention to the problem of uneven length of degrading cycles,
Externí odkaz:
http://arxiv.org/abs/2109.13448
Akademický článek
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Publikováno v:
IEEE/ASME Transactions on Mechatronics; 2023, Vol. 28 Issue: 2 p692-702, 11p
