Random health indicator and shallow neural network based robust capacity estimation for lithium-ion batteries with different fast charging protocols
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DOI: 10.1016/j.energy.2023.127029
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- Wang, Qiao & Ye, Min & Li, Bin & Lian, Gaoqi & Li, Yan, 2024. "Co-estimation of state of charge and capacity for battery packs in real electric vehicles with few representative cells and physics-informed machine learning," Energy, Elsevier, vol. 306(C).
- Wang, Qiao & Ye, Min & Cai, Xue & Sauer, Dirk Uwe & Li, Weihan, 2023. "Transferable data-driven capacity estimation for lithium-ion batteries with deep learning: A case study from laboratory to field applications," Applied Energy, Elsevier, vol. 350(C).
- Wang, Shuhui & Wang, Zhenpo & Cheng, Ximing & Zhang, Zhaosheng, 2023. "A double-layer fault diagnosis strategy for electric vehicle batteries based on Gaussian mixture model," Energy, Elsevier, vol. 281(C).
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Keywords
Lithium-ion batteries; Capacity estimation; Fast charging; Shallow neural network; Hierarchical scenarios;All these keywords.
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