Robustness comparison of battery state of charge observers for automotive applications
2014 (English)In: IFAC Proceedings Volumes (IFAC-PapersOnline), IFAC Secretariat , 2014, Vol. 19, p. 2138-2146Conference paper, Published paper (Refereed)
Abstract [en]
This paper compares the robustness of three different battery State of Charge (SoC) estimation algorithms: the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF) and the H∞ filter. Their performance when subject to disturbances such as parameter uncertainties, different sensor noise characteristics and sensitivity to tuning of the filter are examined. Simulations show that the appropriate choice of observer algorithm will depend on battery chemistry as well as on the intended application. For batteries with a strong correlation between SoC and OCV, the UKF is robust to disturbances such as sensor bias. The H∞ observer shows performance on par with the UKF but the variability of the estimation errors are larger. The EKF is a good all-round choice.
Place, publisher, year, edition, pages
IFAC Secretariat , 2014. Vol. 19, p. 2138-2146
Keywords [en]
Automotive, H-infinity, Hybrid vehicles, Kalman filters, Robustness, State estimation, Automation, Bearings (machine parts), Charging (batteries), Extended Kalman filters, Robustness (control systems), Secondary batteries, Automotive applications, Battery chemistries, Battery state of charge, Observer algorithms, Parameter uncertainty, Unscented Kalman Filter, Battery management systems
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:ri:diva-46401DOI: 10.3182/20140824-6-za-1003.02296Scopus ID: 2-s2.0-84929833315ISBN: 9783902823625 (print)OAI: oai:DiVA.org:ri-46401DiVA, id: diva2:1461104
Conference
19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014, 24 August 2014 through 29 August 2014
Note
Funding details: Energimyndigheten; Funding text 1: This work was supported by the Swedish Energy Agency.
2020-08-262020-08-262020-12-01Bibliographically approved