Review of “grey box” lifetime modeling for lithium-ion battery: Combining physics and data-driven methods

Lithium-ion batteries are a popular choice for a wide range of energy storage system applications. The current motivation to improve the robustness of lithium-ion battery applications has stimulated the need for in-depth research into aging effects and the establishment of lifetime prediction models...

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Vydané v:	Journal of energy storage Ročník 56; s. 105992
Hlavní autori:	Guo, Wendi, Sun, Zhongchao, Vilsen, Søren Byg, Meng, Jinhao, Stroe, Daniel Ioan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.12.2022
Predmet:	Data-driven assisted physical models Data-driven methods Lifetime modeling Lithium-ion batteries Physics-based models Physics-guided data-driven RBPF OCV DNN DRT FNN LS GPR MCMC RVM XRD ETNN Data-driven methods MLP ODE SPM RNN MC LASSO EODV PITT UQ Lifetime modeling BOL ML P2D NODE EM IMM FSW EIS Mask R-CNN EV ROM GHPF SEI PCDNN SEM UODE ANN GITT LiB EnKF Physics-based models FLW Lithium-ion batteries Data-driven assisted physical models PDF PHM IEKF RLS GA XPS KF PINN Physics-guided data-driven MOA SPKF EKF SPMT CDKF LSTM SOA SOC BTMS EST PDEs RUL BMS DAE RMSE SOH ECM CT UKF DRA PC PF PEM
ISSN:	2352-152X, 2352-1538
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