State of Health Prediction of Lithium-Ion Battery Using Machine Learning Algorithms-Reference-Cited by-同舟云学术

State of Health Prediction of Lithium-Ion Battery Using Machine Learning Algorithms

Published:2023-07-03 Issue: Volume: Page:
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Container-title:2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)
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Author:

Hemdani Jamila¹,Degaa Laid²,Rizoug Nassim²,Chaari Abdelkader¹

Affiliation:

1. The National Higher Engineering School of Tunis (ENSIT), University of Tunis,Laboratoire d'Ingenierie des Systèmes Industriels et des Energies Renouvelables,Department of Electrical Engineering,Tunis,Tunisia,BP 56-1008

2. Parc universitaire Laval-Changé, Rue Georges Charpak,Higher School of Aeronautical Techniques and Automobile Construction (ESTACA), Laboratoire des Systèmes et Energies Embarqués pour les Transports,Laval,53000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10284032/10284045/10284459.pdf?arnumber=10284459

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2. Modelling community-scale renewable energy and electric vehicle management for cold-climate regions using machine learning

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4. Electric Vehicle Market by Type, Vehicle Type, Vehicle Class, Top Speed and Vehicle Drive Type: Global Opportunity Analysis and Indus-try Forecatr, 2021–2030,2022

5. Electric Vehicle Market by Component, Vehicle Type, Vehicle Class, Propulsion (BEV, PHEV, FCEV), Vehicle Drive Type (FWD, RWD, AWD), Vehicle Top Speed (125 mph), Charging Point Type, Vehicle Connectivity, End Use, Region-Global Forecast 2030,2022

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