eprintid: 1219
rev_number: 9
eprint_status: archive
userid: 37
dir: disk0/00/00/12/19
datestamp: 2012-03-06 13:19:59
lastmod: 2013-09-30 12:26:33
status_changed: 2012-03-06 13:19:59
type: book_section
metadata_visibility: show
creators_name: Rubagotti, Matteo
creators_name: Onori, Simona
creators_name: Rizzoni, Giorgio
title: Automotive battery prognostics using dual Extended Kalman Filter
ispublished: pub
subjects: TJ
divisions: CSA
full_text_status: none
note: ASME 2009 Dynamic Systems and Control Conference (DSCC2009)
October 12–14, 2009 , Hollywood, California, USA 
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
date: 2009
date_type: published
volume: 2
publisher: American Society of Mechanical Engineers
pagerange: 257-263
id_number: 10.1115/DSCC2009-2725
refereed: TRUE
isbn: 978-0-7918-4893-7
book_title: Proceedings of the Dynamic Systems and Control Conference (DSCC2009) 
official_url: http://dx.doi.org/10.1115/DSCC2009-2725
citation:   Rubagotti, Matteo and Onori, Simona and Rizzoni, Giorgio  Automotive battery prognostics using dual Extended Kalman Filter.   In:  Proceedings of the Dynamic Systems and Control Conference (DSCC2009).   American Society of Mechanical Engineers, pp. 257-263.  ISBN 978-0-7918-4893-7      (2009)