A Machine Learning-based Digital Twin for Electric Vehicle Battery Modeling-Reference-Cited by-同舟云学术

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A Machine Learning-based Digital Twin for Electric Vehicle Battery Modeling

Published:2022-08-01 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)
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Author:

Alamin Khaled Sidahmed Sidahmed¹,Chen Yukai¹,Macii Enrico²,Poncino Massimo¹,Vinco Sara¹

Affiliation:

1. Politecnico di Torino,Department of Control and Computer Engineering,Turin,Italy

2. Politecnico di Torino,Interuniversity Department of Regional and Urban Studies and Planning,Turin,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9854928/9854933/09854960.pdf?arnumber=9854960

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial intelligence in digital twins—A systematic literature review;Data & Knowledge Engineering;2024-05

2. A comprehensive survey on digital twin for future networks and emerging Internet of Things industry;Computer Networks;2024-05

3. Machine learning for battery systems applications: Progress, challenges, and opportunities;Journal of Power Sources;2024-05

4. State of Health Estimation for Second Life Lithium-Ion Batteries: Indicators and Considerations;2024 Second International Conference on Smart Technologies for Power and Renewable Energy (SPECon);2024-04-02

5. Model-Driven Feature Engineering for Data-Driven Battery SOH Model;2024 Design, Automation & Test in Europe Conference & Exhibition (DATE);2024-03-25

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