Visualizing the Battery Degradation through Non-destructive Methods on Predicting the State of Health (SoH) of Second Life Batteries (SLB)-Reference-Cited by-同舟云学术

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Visualizing the Battery Degradation through Non-destructive Methods on Predicting the State of Health (SoH) of Second Life Batteries (SLB)

Published:2023-10-19 Issue: Volume: Page:1-7
ISSN:
Container-title:2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI)
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Author:

S Vignesh¹,Selvaraj Jeyraj A-L²,Che Hang Seng²,Tey Kok Soon³

Affiliation:

1. Universiti Malaya,HiCoE, UMPEDAC Level 4, WISMA R&D Faculty of Institute for Advanced Studies,Kuala Lumpur,Malaysia,59990

2. Universiti Malaya,HiCoE, UMPEDAC Level 4, WISMA R&D,Kuala Lumpur,Malaysia,59990

3. Universiti Malaya,Department of Computer System & Technology,Kuala Lumpur,Malaysia,50603

Funder

Ministry of Education

Japan International Cooperation Agency

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10370005/10370765/10370779.pdf?arnumber=10370779

Reference34 articles.

1. Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation

2. World energy outlook 2022,2022

3. A novel State of Health estimation method for Lithium-ion battery in electric vehicles

4. Online State-of-Health Estimation for Li-Ion Battery Using Partial Charging Segment Based on Support Vector Machine

5. Lithium-Ion Battery Degradation Indicators Via Incremental Capacity Analysis

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