A lightweight two-stage physics-informed neural network for SOH estimation of lithium-ion batteries with different chemistries
Southwest University of Science and Technology · Yibin University · +4 more institutions
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Abstract
No abstract available for this paper.
Citation impact
60
total citations
- FWCI
- 33.51
- Percentile
- 100%
- References
- 39
Citations per year
Authors
7- CLChunsong Lin
Southwest University of Science and Technology, Yibin University, Sichuan University of Science and Engineering
- LWLongxing WuCorresponding
Anhui University of Science and Technology, Anhui Science and Technology University
- XTXianguo Tuo
Southwest University of Science and Technology, Yibin University, Sichuan University of Science and Engineering
- CLChunhui Liu
Anhui University of Science and Technology, Anhui Science and Technology University
- WZWei Zhang
Anhui University of Science and Technology, Anhui Science and Technology University
Topics & keywords
Topics
Keywords
- Lithium (medication)
- Ion
- Artificial neural network
- Stage (stratigraphy)
- Computer science
- Nanotechnology
- Materials science
- Chemistry
UN Sustainable Development Goals
- Affordable and clean energy
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