A comprehensive review of state-of-charge and state-of-health estimation for lithium-ion battery energy storage systems

With the gradual transformation of energy industries around the world, the trend of industrial reform led by clean energy has become increasingly apparent. As a critical link in the new energy industry chain, lithium-ion (Li-ion) battery energy storage system plays an irreplaceable role. Accurate es...

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Vydané v:	Ionics Ročník 30; číslo 10; s. 5903 - 5927
Hlavní autori:	Tao, Junjie, Wang, Shunli, Cao, Wen, Takyi-Aninakwa, Paul, Fernandez, Carlos, Guerrero, Josep M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2024 Springer Nature B.V
Predmet:	Accuracy Algorithms Batteries Chemistry Chemistry and Materials Science Clean energy Clean technology Condensed Matter Physics Deep learning Electric vehicles Electrochemistry Energy Storage Energy utilization Lithium-ion batteries Machine learning Methods Neural networks Optical and Electronic Materials Renewable and Green Energy Review State estimation State of charge Trends Deep learning Kalman filtering Li-ion battery state estimation Equivalent circuit model Parameter identification Based on data-driven algorithms
ISSN:	0947-7047, 1862-0760
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