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Copyright © 2024 CGTN. 京ICP备20000184号
Disinformation report hotline: 010-85061466
Illustration of a battery. /CFP
Chinese researchers have proposed a new type of deep learning model to predict the lifetime of lithium-ion batteries (LIBs), according to a recent article published in the journal IEEE Transactions on Transportation Electrification.
The deep learning model effectively eliminated the dependence on a large amount of charging test data and provided a new idea for predicting battery life in real-time.
The article noted that the accurate lifetime prediction of LIBs is essential to the normal and effective operation of electric devices. However, such estimation faces huge challenges due to the nonlinear capacity degradation process and uncertain operating conditions of LIBs.
The researchers from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences and the Xi'an Jiaotong University proposed a deep learning model based on a small amount of charge cycle data to predict the target battery's current cycle life and remaining useful life.
The learning model can accurately predict the battery's current cycle life and remaining service life using only 15 charge cycle data points. According to the experiment results, this data can make an accurate prediction.
The proposed model is expected to provide a solution for intelligent battery management, said Chen Zhongwei, the director of the State Key Laboratory of Catalysis, DICP.