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Fault Detection for Common Rail Diesel Engines with Low and High Pressure Exhaust Gas Recirculation
Technical Paper
2011-24-0139
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The complexity of the air path of modern common rail diesel engines is rapidly increasing and simultaneously, the demand on air and turbocharger control performances is becoming more challenging. To meet the upcoming emission regulations, the usage of a low pressure exhaust gas recirculation (EGR) circuit in addition to the standard high pressure EGR circuit is often considered. This kind of architecture usually requires a more sophisticated air control system in which a precise control of the EGR flow delivered by the two recirculation branches is required. Moreover, as an alternative or in addition to the low pressure EGR, the implementation of a NOx reduction system e.g. a NOx trap is possible. To proper maintain the correct efficiency of this kind of after-treatment system, special regeneration strategies are adopted where a rich combustion is used instead of the standard Diesel lean mode. During the rich phase the air control plays a key role since the air charge delivered to the cylinders is directly related to the torque. The above example shows that an air system monitoring function capable of detecting even small deviations from the nominal required control behaviour is becoming important. Additionally, due to an increasing number of components and a demand for a better service quality, particular attention is now required on the fault isolation capabilities of the diagnostic functions.
In the above introductory section a representative scenario has been described recognizing the necessity to improve diagnostic functions for the air system monitoring. In this paper, diagnostic methods with enhanced fault detection and isolation capability for air systems with both low and high pressure EGR circuits are presented. For the detection of the faults, physical and semi-physical process and signal models for the components of the air path have been developed. Using these models a set of residuals is derived mainly by applying the parity equation approach. This set of model-based residuals is investigated using measurements from a real engine in fault-free and faulty condition. Typical faults like leakages, clogging, sensor or actuator errors are investigated. The fault detection system is verified over a wide operating range in closed loop operation (EGR and charge pressure control loops are working in parallel to the fault detection system). To evaluate the isolation capability of the residual sets the relationship between symptoms and faults is fully investigated.
This paper presents results from a research corporation between the Institute of Automatic Control at TU Darmstadt and GM Powertrain Europe.
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Eck, C., Sidorow, A., Konigorski, U., and Isermann, R., "Fault Detection for Common Rail Diesel Engines with Low and High Pressure Exhaust Gas Recirculation," SAE Technical Paper 2011-24-0139, 2011, https://doi.org/10.4271/2011-24-0139.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
- Eck, C. Konigorski, U. Cianflone, F. Landsmann, G. “Fault Detection System for the Air Path of Common Rail Diesel Engines with Low Pressue EGR,” SAE Technical Paper 2011-01-0701 2011 10.4271/2011-01-0701
- Mrosek, M. Zahn, S. Isermann, R. “Parameter Estimation for Physical Based Air Path Models of Turbocharged Diesel Angines - An Experience Based Guidance,” SAE Technical Paper 2009-24-0134 2009 10.4271/2009-01-0134
- Clever, S. Muenchhof, M. Mueller, D. “A Fault Diagnosis Toolbox Applying Classification and Inference Methods” the 7 th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes SAFEPROCESS, July 2009 Barcelona, Spain 2009
- Hoefling, T. “Methods for Fault Detection with parameter Estimation and Parity Equations,” Doctoral Thesis Institute of Automatic Control, TU Darmstadt 978-3-18-354608-6 1996