State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach

State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach

The traditional machine learning approach requires substantial computational resources which are scarce in the embedded devices. Recently, the confluence of Edge computing with IoT has enabled resource constrained embedded devices to implement machine learning algorithms. TinyML, with its emphasis o...

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Bibliographic Details
Main Authors: Sesidhar Dvsr, Chandrashekhar Badachi, Chandrashekar Nagawaram, Panduranga Chary Kondoju, C. Dhanamjayulu, Innocent Kamwa
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Data-driven model
edge-computing
Li-ion battery
optimization
state-of-charge
training
Online Access:https://ieeexplore.ieee.org/document/11039786/
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