In a significant advancement for electric technology, Chinese researchers have developed a new deep learning model that can accurately predict the lifespan of lithium-ion batteries (LIBs) using a minimal amount of charge cycle data.
Published in the journal IEEE Transactions on Transportation Electrification, this innovative model by scientists from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences and Xi'an Jiaotong University eliminates the need for extensive charging test data, offering a real-time solution for battery life prediction.
The accurate estimation of LIBs' lifetime is crucial for the efficient and reliable operation of electric devices. However, predicting battery life has long been a challenge due to the nonlinear capacity degradation process and varying operating conditions of LIBs.
The newly proposed deep learning model leverages just 15 charge cycle data points to forecast both the current cycle life and the remaining useful life of the target battery. Experimental results have demonstrated that this limited data can still yield precise predictions, marking a significant improvement in battery management technology.
\"Our model provides a feasible solution for intelligent battery management systems,\" said Chen Zhongwei, director of the State Key Laboratory of Catalysis at DICP. This breakthrough not only enhances the accuracy of battery life predictions but also contributes to the development of more sustainable and efficient energy solutions for the future.
Reference(s):
Chinese researchers create deep learning model to predict battery life
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