State of charge estimation combining physics-based and artificial intelligence models for Lithium-ion batteries-Reference-Cited by-同舟云学术

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State of charge estimation combining physics-based and artificial intelligence models for Lithium-ion batteries

Published:2023-12 Issue: Volume:73 Page:108883
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Yeregui J.^ORCID,Oca L.^ORCID,Lopetegi I.^ORCID,Garayalde E.^ORCID,Aizpurua M.^ORCID,Iraola U.

Publisher

Elsevier BV

Subject

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

Reference33 articles.

1. Aging aware operation of lithium-ion battery energy storage systems: A review;Collath;J. Energy Storage,2022

2. Battery Management Systems, Volume I: Battery Modeling;Plett,2015

3. Battery Management Systems, Volume II: Equivalent-Circuit Methods;Plett,2015

4. An SOC-based battery management system for microgrids;Miao;IEEE Trans. Smart Grid,2014

5. An active balancing method based on SOC and capacitance for lithium-ion batteries in electric vehicles;Liu;Front. Energy Res.,2021

Cited by 2 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. Thermocouple selection and its influence on temperature monitoring of lithium-ion cells;Journal of Energy Storage;2024-07

2. A New Battery SOC/SOH/eSOH Estimation Method Using a PBM and Interconnected SPKFs: Part I. SOC and Internal Variable Estimation;Journal of The Electrochemical Society;2024-03-15

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