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Titlebook: Data Science-Based Full-Lifespan Management of Lithium-Ion Battery; Manufacturing, Opera Kailong Liu,Yujie Wang,Xin Lai Book‘‘‘‘‘‘‘‘ 2022 T

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發(fā)表于 2025-3-27 01:00:29 | 只看該作者
32#
發(fā)表于 2025-3-27 01:21:33 | 只看該作者
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發(fā)表于 2025-3-27 06:23:53 | 只看該作者
34#
發(fā)表于 2025-3-27 12:53:42 | 只看該作者
35#
發(fā)表于 2025-3-27 15:47:08 | 只看該作者
Data Science-Based Battery Operation Management I,span of battery. After manufacturing, battery would be operated in various applications such as transportation electrification, stationary energy storage, and smart grid to supply or absorb the power, where suitable management solutions are necessary to ensure its efficiency, safety, and sustainabil
36#
發(fā)表于 2025-3-27 19:57:46 | 只看該作者
Data Science-Based Battery Operation Management II,prognostics, battery fault diagnosis, and battery charging. For these three key parts, their fundamentals are first given, followed by the case studies of deriving various data science-based solutions to benefit their related operation management.
37#
發(fā)表于 2025-3-28 00:52:30 | 只看該作者
Data Science-Based Battery Reutilization Management,d crucial for the sustainable development of batteries. Battery reutilization mainly includes battery echelon utilization (secondary utilization) and material recycling. During the long-term service of the battery in EVs, the consistency of the battery cell is enlarged and its health would deteriora
38#
發(fā)表于 2025-3-28 02:57:34 | 只看該作者
The Ways Ahead,ge gaps still exist. This chapter summarizes these challenges, future trends, and promising solutions to boost the development of data science solutions in the management of battery manufacturing, operation, and reutilization, respectively. This could further inform the selections of data science me
39#
發(fā)表于 2025-3-28 08:31:40 | 只看該作者
978-3-030-70073-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
40#
發(fā)表于 2025-3-28 13:43:16 | 只看該作者
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