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• W2964017960 abstract "Lithium-ion batteries are the main form of energy providers for electric vehicles. To ensure the reliability and the safety of electric vehicles, it is necessary to estimate the remaining useful life of lithium-ion batteries. Aiming at the strong nonlinear characteristics prevalent in the battery degradation process, this paper proposes a new method for predicting the remaining useful life of lithium-ion batteries based on stochastic model. A new nonlinear degradation model is established based on the diffusion process to characterize the degradation process in the lithium-ion batteries. The battery lifetime and the remaining useful life at any inspection cycle are defined based on the concept of the first hitting time, and the probability density functions of battery lifetime and remaining useful life are derived. Finally, the unknown parameters of the model are estimated by using the maximum likelihood estimation method and the historical data of battery degradation. Remaining useful life prediction experiments are performed based on two published data sets. The experimental results verify with the reliability and accuracy of the proposed method." @default.
• W2964017960 created "2019-07-30" @default.
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• W2964017960 date "2019-01-01" @default.
• W2964017960 modified "2023-10-16" @default.
• W2964017960 title "Research on Degradation Modeling and Life Prediction Method of Lithium-Ion Battery in Dynamic Environment" @default.
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• W2964017960 doi "https://doi.org/10.1109/access.2019.2929177" @default.
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