| Autor: |
Luciano Sánchez, Nahuel Costa, José Otero, David Anseán, Inés Couso |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Array, Vol 20, Iss , Pp 100321- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2590-0056 |
| DOI: |
10.1016/j.array.2023.100321 |
| Popis: |
This study proposes a method for developing equipment lifespan estimators that combine physical information and numerical data, both of which may be incomplete. Physical information may not have a uniform fit to all experimental data, and health information may only be available at the initial and final periods. To address these issues, a procedure is defined to adjust the model to different subsets of available data, constrained by feasible trajectories in the health status space. Additionally, a new health model for rechargeable lithium batteries is proposed, and a use case is presented to demonstrate its efficacy. The optimistic (max–max) strategy is found to be the most suitable for diagnosing battery lifetime, based on the results. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
