Multiscale Dual-path Feature Aggregation Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Published:Dec 16, 2025 14:20
•1 min read
•ArXiv
Analysis
This article presents a research paper on predicting the remaining useful life (RUL) of lithium-ion batteries using a novel neural network architecture. The approach focuses on feature aggregation across multiple scales and utilizes a dual-path design. The source is ArXiv, indicating a pre-print or research paper.
Key Takeaways
- •Focuses on RUL prediction for lithium-ion batteries.
- •Employs a multiscale feature aggregation network.
- •Utilizes a dual-path design for feature processing.
- •Published on ArXiv, suggesting it's a research paper or pre-print.
Reference
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