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A hybrid system-level prognostics approach with online RUL forecasting for electronics-rich systems with unknown degradation behaviors
dc.contributor.author | Al Mohamad, Ahmad |
dc.contributor.author | Hoblos, Ghaleb |
dc.contributor.author | Puig Cayuela, Vicenç |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2021-03-01T10:13:09Z |
dc.date.available | 2022-08-01T00:27:23Z |
dc.date.issued | 2020-08 |
dc.identifier.citation | Al Mohamad, A.; Hoblos, G.; Puig, V. A hybrid system-level prognostics approach with online RUL forecasting for electronics-rich systems with unknown degradation behaviors. "Microelectronics reliability", Agost 2020, vol. 111, p. 113676:1-113676:10. |
dc.identifier.issn | 0026-2714 |
dc.identifier.other | https://www.researchgate.net/publication/342762921_A_hybrid_system-level_prognostics_approach_with_online_RUL_forecasting_for_electronics-rich_systems_with_unknown_degradation_behaviors |
dc.identifier.uri | http://hdl.handle.net/2117/340623 |
dc.description.abstract | This paper proposes a system-level prognostic approach for power electronic systems with slow degradation profiles. Although a model-based approach has been adopted to deal with such multivariable dynamical systems with degradation properties, the forecasting of the Remaining Useful Life (RUL) is independent of prior knowledge of degradation profiles. Thus, this proposition is mainly based on the estimation of the degraded parameters. A robust and well-known technique, the Adaptive Joint Extended Kalman Filter (AJEKF), has been used in previous publications for degradation estimation. Consequently, a deep comprehension of the fault mechanisms of the critical electronic components such as Electrolytic Capacitors (ECaps) and power switching devices such as MOSFETs is needed to define their fault precursors and their degradation behaviors for analytical modeling. The developed forecasting methodology highlights the importance of the historical degradation data in the modeling and estimation stages. The main goal is to increase the reliability of the Prognostics and Health Management (PHM). Thus, this technique has been fully applied to a DC-DC converter used in electric vehicles to forecast its RUL on system-level from component-level basis and the simulation results are then presented. |
dc.description.sponsorship | This work is co-funded by European Union and Normandy Region. Europe is involved in Normandy through the European Funds for Regional Development. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
dc.subject | Àrees temàtiques de la UPC::Enginyeria electrònica::Electrònica de potència |
dc.subject.lcsh | Predictive control |
dc.subject.lcsh | Kalman filtering |
dc.subject.other | Model-based prognostics |
dc.subject.other | Parameter estimation |
dc.subject.other | Power electronics |
dc.subject.other | Prediction algorithms |
dc.subject.other | Prognostics and health management |
dc.subject.other | Reliability assessment |
dc.subject.other | Remaining useful life |
dc.title | A hybrid system-level prognostics approach with online RUL forecasting for electronics-rich systems with unknown degradation behaviors |
dc.type | Article |
dc.subject.lemac | Control predictiu |
dc.subject.lemac | Kalman, Filtratge de |
dc.contributor.group | Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control |
dc.identifier.doi | 10.1016/j.microrel.2020.113676 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0026271419312399 |
dc.rights.access | Open Access |
local.identifier.drac | 28894467 |
dc.description.version | Postprint (author's final draft) |
local.citation.author | Al Mohamad, A.; Hoblos, G.; Puig, V. |
local.citation.publicationName | Microelectronics reliability |
local.citation.volume | 111 |
local.citation.startingPage | 113676:1 |
local.citation.endingPage | 113676:10 |
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