Neural network‐based learning and estimation of battery state‐of‐charge : A comparison study between direct and indirect methodology-Reference-Cited by-同舟云学术

Neural network‐based learning and estimation of battery state‐of‐charge : A comparison study between direct and indirect methodology

Published:2020-07-16 Issue:13 Volume:44 Page:10307-10319
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Int J Energy Res

Author:

Sun Wen¹,Qiu Yicheng¹,Sun Li¹^ORCID,Hua Qingsong²

Affiliation:

1. Key Lab of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment Southeast University Nanjing China

2. Key Laboratory of Beam Technology of Ministry of Education, College of Nuclear Science and Technology, College of Nuclear Science and Technology Beijing Normal University Beijing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.5654

Reference38 articles.

1. The lithium-ion battery: State of the art and future perspectives

2. Integration issues of lithium-ion battery into electric vehicles battery pack

3. Rapidly falling costs of battery packs for electric vehicles

4. Data-driven prediction of battery cycle life before capacity degradation

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

Cited by 27 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. Balancing accuracy and efficiency: a homogeneous ensemble approach for lithium-ion battery state of charge estimation in electric vehicles;Neural Computing and Applications;2024-08-02

2. A new online SOC estimation method using broad learning system and adaptive unscented Kalman filtering algorithm;Energy;2024-08

3. Advanced State of Charge Estimation Using Deep Neural Network, Gated Recurrent Unit, and Long Short-Term Memory Models for Lithium-Ion Batteries under Aging and Temperature Conditions;Applied Sciences;2024-07-30

4. Reinforcement Learning-Based Energy Management for Fuel Cell Electrical Vehicles Considering Fuel Cell Degradation;Energies;2024-03-26

5. Comparative Study-Based Data-Driven Models for Lithium-Ion Battery State-of-Charge Estimation;Batteries;2024-03-03