A review of data-driven whole-life state of health prediction for lithium-ion batteries: data preprocessing, aging characteristics, algorithms, and future challenges.
(2024)
Journal Article
XIE, Y., WANG, S., ZHANG, G., TAKYI-ANINAKWA, P., FERNANDEZ, C. and BLAABJERG, F. 2024. A review of data-driven whole-life state of health prediction for lithium-ion batteries: data preprocessing, aging characteristics, algorithms, and future challenges. Journal of energy chemistry [online], In Press. Available from: https://doi.org/10.1016/j.jechem.2024.06.017
Lithium-ion batteries are the preferred green energy storage method and are equipped with intelligent battery management systems (BMSs) that efficiently manage the batteries. This not only ensures the safety performance of the batteries but also sign... Read More about A review of data-driven whole-life state of health prediction for lithium-ion batteries: data preprocessing, aging characteristics, algorithms, and future challenges..