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

語言學(xué)

聰明

Data Science-Based Battery Reutilization Management,te. Therefore, the batteries retired from EVs cannot be directly used for secondary utilization. It is necessary to evaluate the residual value of these batteries by using the historical data or the test data, and then sort and regroup them for safe secondary utilization.

獨行者

Key Stages for Battery Full-Lifespan Management,first offer the concept and give a systematic framework for the full-lifespan of Li-ion battery, which can be mainly divided into three stages including the battery manufacturing, battery operation, and battery reutilization. Then key management tasks of each stage would be introduced in detail.

拉開這車床

Data Science-Based Battery Operation Management I,age, and smart grid to supply or absorb the power, where suitable management solutions are necessary to ensure its efficiency, safety, and sustainability. In this context, numerous state-of-the-art data science strategies have been developed to perform efficient management of battery operation.

Homocystinuria

Anterior

assail

Terminal

https://doi.org/10.1007/978-3-031-01340-9Lithium-ion Battery; Battery Manufacturing Management; Battery Operation Management; Battery Recycling

一回合

978-3-031-01342-3The Editor(s) (if applicable) and The Author(s) 2022

使聲音降低

Kailong Liu,Yujie Wang,Xin LaiProvides an up-to-date summary of current expertise in battery management.Includes step-by-step instructions for practical battery management and real case studies.Consolidates studies in the rapidly