Automotive battery prognostics using dual extended Kalman filter

Matteo Rubagotti, Simona Onori, Giorgio Rizzoni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

This paper proposes a strategy for estimating the remaining useful life of automotive batteries based on dual Extended Kalman Filter. A nonlinear model of the battery is exploited for the on-line estimation of the State of Charge, and this information is used to evaluate the actual capacity and predict its future evolution, from which an estimate of the remaining useful life is obtained with suitable margins of uncertainty. Simulation results using experimental data from lead-acid batteries show the effectiveness of the approach.

Original languageEnglish
Title of host publicationProceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009
PublisherAmerican Society of Mechanical Engineers (ASME)
Pages1169-1175
Number of pages7
EditionPART B
ISBN (Print)9780791848920
DOIs
Publication statusPublished - Jan 1 2010
Externally publishedYes
Event2009 ASME Dynamic Systems and Control Conference, DSCC2009 - Hollywood, CA, United States
Duration: Oct 12 2009Oct 14 2009

Publication series

NameProceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009
NumberPART B

Conference

Conference2009 ASME Dynamic Systems and Control Conference, DSCC2009
CountryUnited States
CityHollywood, CA
Period10/12/0910/14/09

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ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Rubagotti, M., Onori, S., & Rizzoni, G. (2010). Automotive battery prognostics using dual extended Kalman filter. In Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009 (PART B ed., pp. 1169-1175). (Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009; No. PART B). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DSCC2009-2725