An overview of data-driven battery health estimation technology for battery management system-Reference-Cited by-同舟云学术

An overview of data-driven battery health estimation technology for battery management system

Published:2023-05 Issue: Volume:532 Page:152-169
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Chen Minzhi,Ma Guijun^ORCID,Liu Weibo^ORCID,Zeng Nianyin^ORCID,Luo Xin^ORCID

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference185 articles.

1. U.S. Department of Energy, Energy Storage Grand Challenge: Energy Storage Market Report, 2020. https://www.energy.gov/energy-storage-grand-challenge/downloads/energy-storage-market-report-2020.

2. A survey on evolved LoRa-based communication technologies for emerging internet of things applications;Yao;Int. J. Network Dyn. Intelligence,2022

3. Non-negativity constrained missing data estimation for high-dimensional and sparse matrices from industrial applications;Luo;IEEE Trans. Cybernetics,2020

4. United States Environmental Protection Agency, Fact Sheet | Energy Storage (2019) | White Papers | EESI, (n.d.). https://www.eesi.org/papers/view/energy-storage-2019 (accessed March 9, 2021).

5. An overview of calibration technology of industrial robots;Li;IEEE/CAA J. Autom. Sin.,2021

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