Enhancing Model Robustness in Battery Health Prediction through Advanced Input Features-Reference-Cited by-同舟云学术

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Enhancing Model Robustness in Battery Health Prediction through Advanced Input Features

Published:2024-05-15 Issue: Volume:238 Page:1-6
ISSN:
Container-title:2024 International Conference on Control, Automation and Diagnosis (ICCAD)
language:
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Author:

Hemdani Jamila¹,Degaa Laid²,Rizoug Nassim²,Soltani Moez¹,Telmoudi Achraf Jabeur¹,Chaari Abdelkader¹

Affiliation:

1. University of Tunis, The National Higher Engineering School of Tunis (ENSIT),Industrial Systems and Renewable Energy Engineering Laboratory (LISIER)

2. Higher School of Aeronautical Techniques and Automobile Construction (ESTACA),Energy and Embedded Systems for Transport Department (S2ET)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10553373/10553653/10553899.pdf?arnumber=10553899

Reference24 articles.

1. The renewable energy role in the global energy Transformations

2. Prediction of aging of battery for electric vehicles based on a modified version of neural networks

3. A comprehensive approach of evolving electric vehicles (EVs) to attribute “green self-generation” – a review

4. Zero emission and clean energy concept for campus area in hot-humid tropical climate;Yosafat;ArchNet-IJAR,2022

5. Electrochemical Cells and Storage Technologies to Increase Renewable Energy Share in Cold Climate Conditions—A Critical Assessment

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