Diagnosis is an algorithm for finding and isolating faults in a dynamic system. In 1994, California designated some regulations which were called OBD II. According to these regulations, there is a system installed in an automobile which can analyze the function of the automobile continuously. The decrease of pollution for the expansion of diagnostic system is necessary in the future. To reach the aims of diagnosis, some redundancies are required in the system, either hardware or soft ware. In the hardware redundancy methods, the installation of additional sensors or actuators on the system is required which is costly and takes up a lot of space, whereas in software redundancy methods, this is done with no expense. In this article, one of the software redundancy methods or analytical methods is implied for solving the problem. At first a discussion on literature survey is mentioned, and then a modified mathematical model for SI engine is acquired. The usage of this method and parity space relations, which is a model based method, accomplished the process of diagnosis. Developing a modified SI engine model and diagnosis of MAT sensor which less has been considered besides other components are this article contributions.

1.
R. Beard, Failure Accommodation in Linear Systems through Self-Reorganization. Dept. MVT – 71–1, 1971, Man Vehicle Laboratory, Cambridge, MA.
2.
H. L. Jones, Failure Detection in Linear Systems. Ph.D. Thesis, 1973, MIT, Cambridge, MA.
3.
A. Willsky, A Survey of Design Methods for Failure Detection in Dynamic Systems, Automatica, No. 12, pp. 601–611, Nov. 1976
4.
Bakiotis, C. et al. parameter and Discriminant Analysis for Jet Engine Mechanical State Diagnosis, Proceeding of the IEEE Conference on Decision and Control, pp. 1–11, 1979, Piscataway, NJ
5.
G. Gerger, Fault Identification of a Motor Pump System Using Parameter Estimation and Pattern Classification, Proceeding of the 9th IFAC Congress, Budapest, Pergamon, Oxford Press, 1984
6.
D. Filbert, and K. Metzger, Quality Test of Systems by Parameter Estimation, 9th IMEKO Congress, Berlin, 1982.
7.
R. J. Patton, and J. Chen, Robust Fault Detection Using Eigenstructure Assignment: A Tutorial Consideration and Some New Results, in Proceeding of the 30th IEEE Conference on Decision and Control, pp. 2242–2247, Brighton, 1991.
8.
Gertler
J.
,
Costin
M.
,
Luo
Q.
,
Fang
X. W.
,
Hira
R.
, and
Kowalczuk
Z.
,
On-Board Fault Detection and Isolation for Automotive Engines Using Orthogonal Parity Equations. Invited Paper
.
Preprints of IFAC Conference on Fault Detection, Supervision and Safety (Baden-Baden, Germany, 1991), pp.
Vol.
2
, pp.
241
246
.
9.
T. Hofling, Detection of Parameter Variations by Continuous Time Parity Equations. IFAC World Congress, pp. 513–518, Sydney, Australia, 1993.
10.
D. E. Rumelhart, and J. L. McClelland, Parallel Distributed Processing, M.I.T. Press, Cambridge, Massachusetts, 1986.
11.
Patton, R. J., Lopez, C. J. and Uppal, F. J. Artificial Intelligence Approaches to Fault Diagnosis, Condition Monitoring: Machinery, External Structures and health, IEEE Colloquium on, pp. 22–23, Apr. 1999.
12.
T. Pfeuffer, and M. Ayubi, Application of a Hybrid Neuro-Fuzzy System to the Fault Diagnosis of an Automotive Electromechanical Actuator, Elsevier North-Holland, Inc. 10.1016/S0165-0114(97)00022-5, 1997.
13.
Y. Kim, G. Rizzoni, and V. Utkin, Automotive Engine Diagnosis and Control via Nonlinear Estimation, IEEE Control Systems, 0272-1708, 1998
14.
M. Willimowski, F. Kimmich, and R. Isermann, Signal Model Based Fault Diagnosis for Combustion Engines, Darmstadt University of Technology, Institute of Automatic Control, Landgraf Georg Straße 4, D-64283 Darmstadt, Germany.
15.
M. Nyberg, Model Based Diagnosis of an Automotive Engine Using Several Types of Fault Models, IEEE Transactions on Control Systems Technology, Vol. 10, No. 5, Sept. 2002.
16.
M. Naidu, T. J. Shoepf, and S. Gopalakrishnan Arc fault Detection Schemes for an Automotive 42 V Wire Harness, 2005-01-1742, 2005 SAE Congress, Detrorit, Michigan, Apr. 11–14 2005.
17.
M Fons, M. Muller, A. Chevalier, E. Hendricks, Mean Value Engine Modeling of an SI Engine with EGR, SAE International Cogress and Exposition, Detroit, 1999
This content is only available via PDF.
You do not currently have access to this content.