Sensor selection for fault parameter identification applied to an internal combustion engine

Author

Huber, Johannes ; Kopecek, Herbert ; Hofbaur, Michael

Author_Institution

Inst. of Autom. & Control Eng., UMIT, Hall, Austria

fYear

2014

fDate

8-10 Oct. 2014

Firstpage

89

Lastpage

96

Abstract

This paper presents a methodology for the selection of suitable sensors for a diagnosis problem that is relevant for control of internal combustion engines. The diagnosis is formulated as a parameter estimation problem, which is solved by augmenting the plant model with additional states that represent the faults. An Extended Kalman Filter is applied to estimate the states of the augmented model. The sensor selection is based on the classical concepts of observability as well as on the distinguishability analysis for the faults.

Keywords

Kalman filters; fault diagnosis; internal combustion engines; nonlinear filters; observability; parameter estimation; sensors; augmented model; diagnosis problem; distinguishability analysis; extended Kalman filter; fault parameter identification; internal combustion engine control; observability analysis; parameter estimation problem; plant model; sensor selection; Actuators; Engines; Equations; Indexes; Mathematical model; Observability; Valves;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications (CCA), 2014 IEEE Conference on

Conference_Location

Juan Les Antibes

Type

conf

DOI

10.1109/CCA.2014.6981334

Filename

6981334