Optimized Training Options of a Deep Learning Model for Lithium-Ion Battery State of Charge Estimation-Reference-Cited by-同舟云学术

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Optimized Training Options of a Deep Learning Model for Lithium-Ion Battery State of Charge Estimation

Published:2023-11-20 Issue: Volume: Page:267-270
ISSN:
Container-title:2023 IEEE International Future Energy Electronics Conference (IFEEC)
language:
Short-container-title:

Author:

Li Yuyue¹,Ding Ping²,Zheng Linfeng³

Affiliation:

1. International Energy College, Jinan University,Zhuhai,China

2. Energy and Electricity Research Center, Jinan University,Zhuhai,China

3. International Energy College, Jinan University, Institute of Rail Transportation, Jinan University Zhuhai,Zhuhai,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10458412/10458440/10458627.pdf?arnumber=10458627

Reference11 articles.

1. Energy Management for a Power-Split Plug-in Hybrid Electric Vehicle Based on Dynamic Programming and Neural Networks

2. LiFePO4 battery charging strategy design considering temperature rise minimization

3. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

4. A Simplified Model-Based State-of-Charge Estimation Approach for Lithium-Ion Battery With Dynamic Linear Model

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