Original paper
Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression
Abstract
To solve the problem of the inaccurate prediction on remaining useful life (RUL) for lithium-ion battery, we proposed an integrated algorithm which combines adaptive unscented kalman filter (AUKF) and genetic algorithm optimized support vector regression (GA-SVR). Firstly, the state space model with double exponential is established to describe the degradation of lithium battery. Then, the AUKF algorithm is introduced to update adaptively both...
Paper Details
Title
Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression
Published Date
Feb 1, 2020
Journal
Volume
376
Pages
95 - 102
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