A Novel Remaining Useful Life Prediction Method for Capacity Diving Lithium-Ion Batteries
Author:
Affiliation:
1. School of Engineering, Huzhou University, Huzhou City, 516007, China
2. Institute of Technology, Huzhou College, Huzhou City, 313000, China
3. ZheJiang Tianneng New Materials Co, Huzhou City, 313103, China
Funder
Huzhou University
Basic Public Welfare Research Program of Zhejiang Province
Huzhou public welfare applied research project
Publisher
American Chemical Society (ACS)
Subject
General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c03043
Reference42 articles.
1. Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods
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3. A review on lithium-ion battery ageing mechanisms and estimations for automotive applications
4. Lithium-ion battery state of health monitoring and remaining useful life prediction based on support vector regression-particle filter
5. A review of the state of health for lithium-ion batteries: Research status and suggestions
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