A Novel Machine Learning Algorithm for State of Health Prediction of Lithium-Ion Batteries-Reference-Cited by-同舟云学术

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A Novel Machine Learning Algorithm for State of Health Prediction of Lithium-Ion Batteries

Published:2023-10-25 Issue: Volume: Page:822-827
ISSN:
Container-title:2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
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Author:

Battaglia Filippo¹,Campobello Giuseppe¹,Aloisio Davide²,Leonardi Salvatore Gianluca²,Gugliandolo Giovanni¹,Brunaccini Giovanni²,Sergi Francesco²,Donato Nicola¹

Affiliation:

1. University of Messina,Department of Engineering,Messina,Italy

2. Institute of Advanced Energy Technologies (CNR ITAE),Messina,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10405419/10405547/10405755.pdf?arnumber=10405755

Reference27 articles.

1. Low-Complexity Electrochemical-Impedance Spectroscopy for Battery Monitoring

2. Comparison of machine learning techniques for SoC and SoH evaluation from impedance data of an aged lithium ion battery

3. A Review of SOH Prediction of Li-Ion Batteries Based on Data-Driven Algorithms

4. Overview of Lithium-Ion Battery Modeling Methods for State-of-Charge Estimation in Electrical Vehicles

5. A review of machine learning state-of-charge and state-of-health estimation algorithms for lithium-ion batteries

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