Active acoustic emission sensing for fast co-estimation of state of charge and state of health of the lithium-ion battery-Reference-Cited by-同舟云学术

Active acoustic emission sensing for fast co-estimation of state of charge and state of health of the lithium-ion battery

Published:2023-08 Issue: Volume:64 Page:107192
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Wang Zuolu,Zhao Xiaoyu,Zhang Hao,Zhen Dong,Gu Fengshou,Ball Andrew

Funder

National Natural Science Foundation of China

Hebei University of Technology

University of Huddersfield

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference41 articles.

1. An execution time optimized state of charge estimation method for lithium-ion battery;Çelikten;J.Energy Storage,2022

2. Constant current charging time based fast state-of-health estimation for lithium-ion batteries;Lin;Energy,2022

3. A novel fuzzy adaptive cubature Kalman filtering method for the state of charge and state of energy co-estimation of lithium-ion batteries;Yang;Electrochim. Acta,2022

4. Deep learning enabled state-of-charge estimation of LiFePO4 batteries: a systematic validation on state-of-the-art charging protocols;Hu;Energy,2022

5. A data-model fusion method for online state of power estimation of lithium-ion batteries at high discharge rate in electric vehicles;Guo;Energy,2022

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