This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Fault Detection System for the Air Path of Common Rail Diesel Engines with Low Pressure EGR
Technical Paper
2011-01-0701
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Future automotive engines have to comply with upcoming emission legislations (EURO 6, CARB 2) raising the requirements on onboard diagnostic systems (OBD). Faulty conditions of the engine leading to higher emissions must be detected with rising accuracy. Additionally, car manufacturers have a strong interest in improving the reliability of fault diagnosis in their workshops in the sense of being able to find the smallest changeable part. The legislation requirements can be reached using the present methodology, as has been shown in first series applications. But advanced methods of model-based fault detection and isolation can help to accomplish with future requirements as well as to extend the present OBD systems, especially with the ability of detecting small faults and the ability of a root cause isolation. This contribution describes a new approach to detect and isolate typical faults in the air path of common rail Diesel engines with high as well as low pressure exhaust gas recirculation (EGR). The presented fault detection system aims at bringing advanced model-based fault detection methodology to the ECU. The fault detection and isolation capabilities of the system are investigated with the help of measurement data acquired from a dynamic engine test bench.
This paper presents results from a research corporation between the Institute of Automatic Control at TU Darmstadt and GM Powertrain Europe.
Recommended Content
Authors
Citation
Eck, C., Konigorski, U., Cianflone, F., and Landsmann, G., "Fault Detection System for the Air Path of Common Rail Diesel Engines with Low Pressure EGR," SAE Technical Paper 2011-01-0701, 2011, https://doi.org/10.4271/2011-01-0701.Also In
References
- Isermann, R. “Fault Diagnosis Systems” Springer Berlin, Heidelberg 978-3-540-24112-6 2005 10.1007/3-540-30368-5
- Guzzella, L. Onder, C. H. “Introduction to Modeling and Control of Internal Combustion Engine Systems” Springer Berlin Heidelberg 978-3-642-10774-0 2010 10.1007/978-3-642-10775-7
- Heywood, J.B. “Internal Combustion Engine Fundamentals” McGraw-Hill New York, St. Louis, San Francisco, Auckland 1988
- Clever, S. Isermann, R. “Model-based Fault Diagnosis for Passenger Car Diesel Engines,” 18. Aachener Kolloquium Fahrzeug- und Motorentechnik 2009 Aachen, Germany October 05 07 2009 33 281 310
- Schwarte, A. “Modellbasierte Fehlererkennung und Diagnose des Ansaug- und Abgassystems von Dieselmotoren,” Doctoral thesis Institute of Automatic Control, TU Darmstadt 978-3-18-363412-5 2007
- Kimmich, F. Schwarte, A. Isermann, R. “Fault detection for modern diesel engines using signal- and process model-based methods,” Control Engineering Practice 13 1 189 203 2005 10.1016/j.conengprac.2004.03.002
- Nelles, O. “Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models” Springer Berlin 978-3-540-67369-9 2000
- Proakis, J. G. Manolakis, D. G. “Digital Signal Processing” Prentice Hall 978-0-131-87374-2 2006
- Mrosek, M. Zahn, S. Isermann, R. “Parameter Estimation for Physical Based Air Path Models of Turbocharged Diesel Engines - An Experience Based Guidance,” SAE Int. J. Engines 2 2 570 583 2009 10.4271/2009-24-0134