Physical-based training data collection approach for data-driven lithium-ion battery state-of-charge prediction

Physical-based training data collection approach for data-driven lithium-ion battery state-of-charge prediction

Data-Driven approaches for State of Charge (SOC) prediction have been developed considerably in recent years. However, determining the appropriate training dataset is still a challenge for model development and validation due to the considerably varieties of lithium-ion batteries in terms of materia...

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Bibliographic Details
Main Authors: Jie Li, Will Ziehm, Jonathan Kimball, Robert Landers, Jonghyun Park
Format: Article
Language:English
Published: Elsevier 2021-09-01
Series:Energy and AI
Subjects:
Machine learning
Random signal
Battery soc
Dynamic current
Battery modeling
Estimation
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546821000483

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http://www.sciencedirect.com/science/article/pii/S2666546821000483

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