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Remaining Useful Life Prediction of Lithium Batteries Based on Extended Kalman Particle Filter

Title
Remaining Useful Life Prediction of Lithium Batteries Based on Extended Kalman Particle Filter
Author
홍승호
Issue Date
2021-01
Publisher
WILEY
Citation
IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, v. 16, Issue. 2, Page. 206-214
Abstract
The prognosis of time-to-failure for a battery can avoid the failure caused by battery performance loss. In this paper, a novel and effective algorithm is proposed to predict the remaining useful life of lithium-ion batteries. The extended Kalman particle filter is used to improve particle degradation problem existing in standard particle filter algorithm. In order to fit battery capacity degradation, a transformed model is proposed based on double exponential empirical degradation model. It can reduce the number of parameters and the training difficulty of parameters
URI
https://onlinelibrary.wiley.com/doi/full/10.1002/tee.23287https://repository.hanyang.ac.kr/handle/20.500.11754/167027
ISSN
1931-4973; 1931-4981
DOI
10.1002/tee.23287
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ELECTRICAL ENGINEERING(전자공학부) > Articles
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