A hybrid framework for predicting the remaining useful life of battery using Gaussian process regression-Reference-Cited by-同舟云学术

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A hybrid framework for predicting the remaining useful life of battery using Gaussian process regression

Published:2023-08 Issue: Volume:66 Page:107513
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Li Jiabo,Ye Min,Wang Yan,Wang Qiao,Wei Meng

Funder

National Natural Science Foundation of China

Chang'an University

Fundamental Research Funds for the Central Universities

Shanxi Provincial Key Research and Development Project

Natural Science Basic Research Program of Shaanxi Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference33 articles.

1. Detection of intermittent faults for nonuniformly sampled multirate systems with dynamic quantization and missing measurements;Zhang;Int. J. Control,2020

2. Fast clustering of retired lithium-ion batteries for secondary life with a two-step learning method;Ran;ACS Energy Lett.,2022

3. A sustainable framework for the second-life battery ecosystem based on blockchain;Sun;eTransportation,2022

4. A general end-to-end diagnosis framework for manufacturing systems;Yuan;Natl. Sci. Rev.,2020

5. Multivariate/minor fault diagnosis with severity level based on bayesian decision theory and multidimensional RBC;Zheng;J. Process Control,2021

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1. A novel sequential estimation framework for battery state of health and remaining useful life based on sparse and limited data;Journal of Energy Storage;2024-10

2. Edge–cloud collaborative estimation lithium-ion battery SOH based on MEWOA-VMD and Transformer;Journal of Energy Storage;2024-10

3. High precision estimation of remaining useful life of lithium-ion batteries based on strongly correlated aging feature factors and AdaBoost framework;Ionics;2024-08-03

4. Remaining useful life prediction of lithium-ion batteries based on performance degradation mechanism analysis and improved Deep Extreme Learning Machine model;Ionics;2024-07-06

5. A high-order strong tracking filter based on a compensated adaptive model for predicting sudden changes in remaining useful life of a lithium-ion battery;Journal of Energy Storage;2024-05

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