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A review of data-driven whole-life state of health prediction for lithium-ion batteries: Data preprocessing, aging characteristics, algorithms, and future challenges

Yanxin Xie, Shunli Wang, Gexiang Zhang, Paul Takyi‐Aninakwa, Carlos Fernández, Frede Blaabjerg

2024Journal of Energy Chemistry110 citationsDOIOpen Access PDF

Topics & Concepts

State of healthComputer scienceHealth management systemPreprocessorBattery (electricity)Control reconfigurationReliability engineeringData miningEngineeringArtificial intelligenceEmbedded systemAlternative medicineMedicinePhysicsPathologyQuantum mechanicsPower (physics)Advanced Battery Technologies ResearchAdvancements in Battery MaterialsExtraction and Separation Processes
A review of data-driven whole-life state of health prediction for lithium-ion batteries: Data preprocessing, aging characteristics, algorithms, and future challenges | Litcius