Detecting Abnormality of Battery Lifetime from First‐Cycle Data Using Few‐Shot Learning (Adv. Sci. 6/2024)
Xiaopeng Tang, Xin Lai, Changfu Zou, Yuanqiang Zhou, Jiajun Zhu, Yuejiu Zheng, Furong Gao
Abstract
Lithium-Ion Batteries The lifetime of large battery packs can be influenced by only one or two abnormal cells with faster aging rates in it. In article number 2305315, Changfu Zou, Furong Gao, and co-workers propose a method to predict battery lifetime abnormality using only the first-cycle battery aging data and achieve a typical accuracy greater than 90%. It can be used to screen out abnormal batteries before grouping, improving the capacity, lifetime, and cost-benefit of a battery pack with immediate effect.
Topics & Concepts
AbnormalityBattery (electricity)Computer scienceArtificial intelligenceMaterials sciencePattern recognition (psychology)MedicinePhysicsQuantum mechanicsPower (physics)PsychiatryAdvanced Battery Technologies ResearchFault Detection and Control Systems