Data-Driven Prognostics of the SOFC System Based on Dynamic Neural Network Models
Prognostics technology is important for the sustainability of solid oxide fuel cell (SOFC) system commercialization, i.e., through failure prevention, reliability assessment, and the remaining useful life (RUL) estimation. To solve SOFC system issues, data-driven prognostics methods based on the dyn...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-09-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/14/18/5841 |