Enhanced early prediction of Li-ion battery degradation using multicycle features and an ensemble deep learning model
Achieving high accuracy in the early prediction of Li-ion battery degradation is challenging owing to the nonlinear and dynamic nature of battery aging. This study introduces a GRU-LSTM ensemble model that combines Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) networks to forecast th...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025003214 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|