Review of battery state estimation methods for electric vehicles - Part I: SOC estimation-Reference-Cited by-同舟云学术

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Review of battery state estimation methods for electric vehicles - Part I: SOC estimation

Published:2024-05 Issue: Volume:87 Page:111435
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Demirci Osman,Taskin Sezai,Schaltz Erik,Acar Demirci Burcu

Publisher

Elsevier BV

Reference141 articles.

1. Evaluation of economic and social effects of integrating a BMS system in residential and commercial housing;Chobanov,2021

2. Global EV Outlook 2015, Geo;International Energy Agengy,2015

3. An overview of electric vehicle technology;Chan;Proc. IEEE,1993

4. Recent developments of zinc-ion batteries;Kim;Energy-Sustainable Adv. Mater.,2021

5. Review of battery management systems (BMS) development and industrial standards;Gabbar;Technologies,2021

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1. Closed-loop state of charge estimation of Li-ion batteries based on deep learning and robust adaptive Kalman filter;Energy;2024-10

2. Target decomposition-led light-weighted offline training strategy-aided data-driven state-of-charge online estimation during constant current charging conditions over battery entire lifespan;Energy;2024-10

3. A comparative study on state-of-charge estimation for lithium-rich manganese-based battery based on Bayesian filtering and machine learning methods;Energy;2024-10

4. An exhaustive review of battery faults and diagnostic techniques for real-world electric vehicle safety;Journal of Energy Storage;2024-10

5. Lithium inventory estimation of battery using incremental capacity analysis, support vector machine, particle swarm optimisation;IET Energy Systems Integration;2024-09-11

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