State-of-charge estimation for the lithium-ion battery based on adaptive extended Kalman filter using improved parameter identification-Reference-Cited by-同舟云学术

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State-of-charge estimation for the lithium-ion battery based on adaptive extended Kalman filter using improved parameter identification

Published:2022-01 Issue: Volume:45 Page:103518
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Shi Na,Chen Zewang,Niu Mu,He Zhijia,Wang Youren,Cui Jiang

Funder

Fundamental Research Funds for the Central Universities

Nanjing University of Aeronautics and Astronautics

Aeronautical Science Foundation of China

Publisher

Elsevier BV

Subject

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

Reference43 articles.

1. Classification, summarization and perspectives on state-of-charge estimation of lithium-ion batteries used in electric vehicles: A critical comprehensive survey;Yang;J. Energy Storage,2021

2. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations;Hannan;Renew. Sustain. Energy Rev.,2017

3. Electric vehicle battery modelling methods based on state of charge–review;Thiruvonasundari;J. Green Eng.,2020

4. Critical review on the battery state of charge estimation methods for electric vehicles;Xiong;IEEE Access,2017

5. Review on the state of charge estimation methods for electric vehicle battery;Zhang;World Electr. Veh. J.,2020

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