Fractional Extended and Unscented Kalman Filtering for State of Charge Estimation of Lithium-Ion Batteries
Abstract:
Two state of charge estimation methods using fractional order extended and unscented Kalman filter and a nonlinear variable fractional order battery model are implemented. Both, battery model and Kalman filters are evaluated and compared using measurements of an actual lithium-ion polymer battery cell. The observability of the battery model and the influence of an initialization function on the estimation algorithms is investigated.
| Zugehörige Institution(en) am KIT | Institut für Regelungs- und Steuerungssysteme (IRS) |
| Publikationstyp | Proceedingsbeitrag |
| Publikationsjahr | 2018 |
| Sprache | Englisch |
| Identifikator | ISBN: 978-1-5386-5429-3 urn:nbn:de:swb:90-853951 KITopen-ID: 1000085395 |
| Erschienen in | 2018 Annual American Control Conference (ACC), Milwaukee, WI, USA, 27–29 June 2018 |
| Verlag | Institute of Electrical and Electronics Engineers (IEEE) |
| Seiten | 3855–3862 |
| Vorab online veröffentlicht am | 16.08.2018 |
| Nachgewiesen in | Scopus Dimensions |
| Globale Ziele für nachhaltige Entwicklung |