Neural Network Approaches for State of Charge Prediction of Rechargeable Lithium Polymer Batteries-Reference-Cited by-同舟云学术

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Neural Network Approaches for State of Charge Prediction of Rechargeable Lithium Polymer Batteries

Published:2024-06-25 Issue: Volume: Page:236-241
ISSN:
Container-title:2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)
language:
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Author:

Apa Ludovica¹,Del Prete Zaccaria¹,Forconi Flavia²,Palermo Martina²,Fulginei Francesco Riganti²,Rizzuto Emanuele¹,Sabino Lorenzo²

Affiliation:

1. University of Rome “Sapienza”,Department of Mechanical and Aereospace Engineering,Rome,Italy

2. University of Roma Tre,Department of Industrial, Electronic and Mechanical Engineering,Rome,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10608458/10608460/10608570.pdf?arnumber=10608570

Reference26 articles.

1. Review of Challenges and Opportunities in the Integration of Electric Vehicles to the Grid

2. Potential of lithium-ion batteries in renewable energy

3. Lithium-ion battery-packs for solar home systems: Layout, cost and implementation perspectives

4. Battery monitoring system using machine learning

5. State-of-charge estimation of lithium-ion batteries using LSTM and UKF

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