DocumentCode :
1709808
Title :
Model-based fault detection of a battery system in a hybrid electric vehicle
Author :
Gadsden, S.A. ; Habibi, S.R.
Author_Institution :
Dept. of Mech. Eng., McMaster Univ., Hamilton, ON, Canada
fYear :
2011
Firstpage :
1
Lastpage :
6
Abstract :
Recently, a new type of interacting multiple model (IMM) method was introduced based on the relatively new smooth variable structure filter (SVSF), and is referred to as the IMM-SVSF. The SVSF is a type of sliding mode estimator that is formulated in a predictor-corrector fashion. This strategy keeps the estimated state bounded within a region of the true state trajectory, thus creating a stable and robust estimation process. The IMM method may be utilized for fault detection and diagnosis, and is classified as a model-based method. In this paper, for the purposes of fault detection, the IMM-SVSF is applied through simulation on a simple battery system which is modeled from a hybrid electric vehicle.
Keywords :
estimation theory; hybrid electric vehicles; secondary cells; variable structure systems; battery system; hybrid electric vehicle; interacting multiple model; model-based fault detection; predictor-corrector fashion; robust estimation; sliding mode estimator; smooth variable structure filter; Batteries; Equations; Estimation; Fault detection; Hybrid electric vehicles; Mathematical model; Probability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicle Power and Propulsion Conference (VPPC), 2011 IEEE
Conference_Location :
Chicago, IL
ISSN :
Pending
Print_ISBN :
978-1-61284-248-6
Electronic_ISBN :
Pending
Type :
conf
DOI :
10.1109/VPPC.2011.6043175
Filename :
6043175
Link To Document :
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