Active-learning-driven error control for data-driven state of charge estimation across the lithium battery lifecycle

Active-learning-driven error control for data-driven state of charge estimation across the lithium battery lifecycle

Accurate estimation of lithium-ion battery state of charge (SOC) is crucial for the safe and efficient operation of electric vehicles (EVs). However, both data-driven and model-driven SOC estimation methods face significant challenges under battery aging, which alters internal resistance and electro...

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Bibliographic Details
Main Authors: Jinwei Xue, Xuzhi Du, Lei Zhao, Zhigang Yang, Chao Xia, Yuan Ma, Muhammad Jahidul Hoque, Wuchen Fu, Xiao Yan, Nenad Miljkovic
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Energy and AI
Subjects:
Lithium-ion battery
State of charge (SOC)
Battery aging
data-driven SOC estimation
Deep learning
Active learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546825000813
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