Fault diagnostics in air intake system of combustion engine using virtual sensors
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University of Technology and Humanities in Radom
Submission date: 2017-07-28
Final revision date: 2017-09-14
Acceptance date: 2017-12-04
Online publication date: 2017-12-18
Publication date: 2018-03-12
Corresponding author
Iwona Monika Komorska   

University of Technology and Humanities in Radom, Chrobrego, 45, 26-600 Radom, Polska
Diagnostyka 2018;19(1):25-32
The method for the fault diagnosing of the air intake system of a gasoline engine, not detected by the on-board diagnostics system in a car, is described in this article. The aim is to detect and identify such faults like changes in sensor characteristic, faults of mass airflow measurement in the intake manifold or manifold leakages. These faults directly affect the air intake system performance that results in engine roughness and a power decrease. The method is based on the generation of residuals on the grounds of differences in indications of the manifold absolute pressure (MAP) and mass air flow (MAF) sensors installed in the car and the virtual, model-based sensors. The empirical model for the fault-free state was constructed at stationary operations of the engine. The residuals were then evaluated to classify the system health. Investigations were conducted for a conventional gasoline engine with port-fuel injection (PFI) and for a gasoline direct injection engine (GDI).
Dąbrowski Z Madej H. Masking mechanical damages in the modern control systems of combustion engines. Journal of Kones Powertrain and Transport 2006; 13(3): 53-60.
Dąbrowski Z, Zawisza M. Investigations of the vibroacoustic signals sensitivity to mechanical defects not recognised by the OBD system in diesel engines. Mechatronic Systems, Mechanics and Materials. Solid State Phenomena 2012; 180: 194-199.
Dutka A, Javaherian H, Grimble M. Model-based engine fault detection and isolation. Proceedings of American Control Conference ACC '09 2009: 4593 – 4600.
Figlus T, Konieczny Ł, Burdzik R, Czech P. Assessment of diagnostic usefulness of vibration of the common rail system in the diesel engine. Vibroengineering Proceedia 2015; 6: 185‑189.
Franchek MA, Buehler PJ, Makki I. Intake air path diagnostics for internal combustion engines. Journal of Dynamic Systems, Measurement and Control 2007; 129(1): 32-40.
Guzzella L, Onder C. Introduction to Modelling and Control of Internal Combustion Engine Systems. Springer; ETH Zurich; 2004.
Isermann R. Model-based fault-detection and diagnosis – status and applications. Annual Reviews in Control 2005; 29: 71–85.
Jongeneel J, Nijmeijer H, Manzie C, Nesic D. Input redundant internal combustion engine with linear quadratic Gaussian control and dynamic control allocation. Internal Report. Eindhoven University of Technology; Eindhoven, Netherlands; 2009.
Kiencke U, Nielsen L. Automotive Control Systems. For Engine, Driveline, and Vehicle. Springer-Verlag; Berlin Heidelberg; 2005.
Komorska I, Puchalski A. On-board diagnostics of mechanical defects of the vehicle drive system based on the vibration signal reference model. Journal of Vibroengineering 2013; 15(1): 450-458.
Komorska I, Wołczyński Z. Fault Diagnostics of Air Intake System of the Internal Combustion Engine. ICTD-CMMNO 2016 Congress; Gliwice 12-16.09.2016.
Komorska I, Wołczyński Z, Borczuch A. Model-based analysis of sensor faults in SI engine. Combustion Engines 2017; 169(2): 146-151.
Merkisz J, Pielecha J, Radzimirski S. New trends in emission control in the European Union. Springer; 2014.
Nyberg M, Nielsen L. Model Based Diagnosis for the Air Intake System of the SI-Engine. SAE Technical Paper 970209; 1997. DOI:10.4271/970209.
Nyberg M. Model-based diagnosis of an automotive engine using several types of fault models. IEEE Transactions on Control Systems Technology 2002; 10(5): 679 – 689. DOI: 10.1109/TCST.2002.801873.
Puchalski A, Komorska I. On-line Fault Diagnosis of Automotive Powernets by Kalman Filtering. Key Engineering Materials 2014; 588: 209-213.
Reif K. Gasoline Engine Management. Systems and Components. Springer-Vieweg; 2015. DOI:10.1007/978-3-65803964-6.
Wenzel TA, Burnham KJ, Blundell MV. Kalman filter as a virtual sensor: applied to automotive stability systems. Transactions of the Institute of Measurement and Control 2007; 29(2): 95-115.
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