End-cloud collaboration method enables accurate state of health and remaining useful life online estimation in lithium-ion batteries
Bin Ma(Jilin University), Xinhua Liu(Beihang University), Bosong Zou(Jilin University), Wentao Wang(Chinese Academy of Sciences), Cheng Zhang(University of Warwick), Hanqing Yu(Beihang University), Lisheng Zhang(Beihang University), Shichun Yang(Beihang University)
Cited by 46
Related Papers
A brief review on key technologies in the battery management system of electric vehicles
|Frontiers of Mechanical Engineering|2018|596
Emission of Oxygenated Polycyclic Aromatic Hydrocarbons from Indoor Solid Fuel Combustion
|Environmental Science & Technology|2011|149
Remaining useful life and state of health prediction for lithium batteries based on differential thermal voltammetry and a deep-learning model
|Journal of Power Sources|2022|107