Joint nonlinear-drift-driven Wiener process-Markov chain degradation switching model for adaptive online predicting lithium-ion battery remaining useful life

Author:

Zhang Yixing,Feng Fei,Wang Shunli,Meng Jinhao,Xie Jiale,Ling Rui,Yin Hongpeng,Zhang Ke,Chai Yi

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference37 articles.

1. Intelligent data-driven prognostic methodologies for the real-time remaining useful life until the end-of-discharge estimation of the Lithium-Polymer batteries of unmanned aerial vehicles with uncertainty quantification;Eleftheroglou;Appl Energy,2019

2. Battery state of health modeling and remaining useful life prediction through time series model;Lin;Appl Energy,2020

3. Electrochemical impedance characteristics at various conditions for commercial solid-liquid electrolyte lithium-ion batteries: Part 1. experiment investigation and regression analysis;Feng;Energy,2022

4. Multiple time scale state-of-charge and capacity-based equalisation strategy for lithium-ion battery pack with passive equaliser;Feng;J Storage Mater,2022

5. Nonlinear-drifted fractional Brownian motion with multiple hidden state variables for remaining useful life prediction of lithium-ion batteries;Zhang;IEEE Trans Reliab,2020

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