Long-range battery state-of-health and end-of-life prediction with neural networks and feature engineering
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DOI: 10.1016/j.apenergy.2023.121761
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References listed on IDEAS
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Cited by:
- Wang, Cong & Chen, Yunxia, 2024. "Unsupervised dynamic prognostics for abnormal degradation of lithium-ion battery," Applied Energy, Elsevier, vol. 365(C).
- Singh, S. & Budarapu, P.R., 2024. "Deep machine learning approaches for battery health monitoring," Energy, Elsevier, vol. 300(C).
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Keywords
Lithium-ion batteries; Automated feature extraction; Deep learning; State of health; End of life;All these keywords.
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