Development of Extended MVEM based UKF estimators

Author

Vasu, Jonathan ; Deb, A.K. ; Mukhopadhyay, S.

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Technol., Kharagpur, India

fYear

2011

fDate

16-18 Dec. 2011

Firstpage

1

Lastpage

6

Abstract

Mean Value Engine Models (MVEM) have been used to model the averaged dynamics of an automobile engine system for automotive control and fault diagnosis. For these purposes, it is common to estimate states of interest given noisy measurements using state observers. Since the measurements could be noisy and asynchronous, they should be suitably post-processed before feeding them to a state observer. In this paper, an Unscented Kalman Filter (UKF) was developed for an Extended MVEM and a suitable post-processing algorithm for the measurements has been described.

Keywords

Kalman filters; fault diagnosis; internal combustion engines; nonlinear filters; observers; automobile engine system; automotive control; extended mean value engine model; fault diagnosis; post-processing algorithm; state observer; unscented kalman filter; Covariance matrix; Engines; Fuels; Manifolds; Mathematical model; Noise measurement; Temperature measurement; Mean Value Engine Model (MVEM); Simple Moving Averager (SMA); Unscented Kalman Filter (UKF); boot-strapping; estimation; post-prcessing;

fLanguage

English

Publisher

ieee

Conference_Titel

India Conference (INDICON), 2011 Annual IEEE

Conference_Location

Hyderabad

Print_ISBN

978-1-4577-1110-7

Type

conf

DOI

10.1109/INDCON.2011.6139369

Filename

6139369