Remaining Useful Life Prediction of a Lithium–Ion Battery Based on a Temporal Convolutional Network with Data Extension
Unmanned underwater vehicles are typically deployed in deep sea environments, which present unique working conditions. Lithium-ion power batteries are crucial for powering underwater vehicles, and it is vital to accurately predict their remaining useful life (RUL) to maintain system reliability and...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-03-01
|
| Series: | International Journal of Applied Mathematics and Computer Science |
| Subjects: | |
| Online Access: | https://doi.org/10.61822/amcs-2024-0008 |