Remaining useful life prediction of lithium-ion battery based on fusion model considering capacity regeneration phenomenon

Author:

He Ning,Yang Ziqi,Qian Cheng,Li Ruoxia,Gao Feng,Cheng Fuan

Funder

Shanxi Provincial Key Research and Development Project

National Key Research and Development Program of China

Xi'an University of Architecture and Technology

Publisher

Elsevier BV

Reference41 articles.

1. A method for state of energy estimation of lithium-ion batteries based on neural network model;Dong;Energy,2015

2. Advanced mathematical methods of SOC and SOH estimation for lithium-ion batteries;Andre;J. Power Sources,2013

3. Data-driven health estimation and lifetime prediction of lithium-ion batteries: a review;Li;Renew. Sust. Energ. Rev.,2019

4. Remaining useful life prediction of lithium-ion batteries based on support vector regression optimized and grey wolf optimizations;Yang,2021

5. Estimation of health state and prediction of remaining life of lithium battery based on new health factors;Feng;Journal of Nanjing University (Natural Science),2021

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