To download article.DOI: 10.15507/2658-4123.032.202202.235-248
Using Diagnostics to Research the Operational Reliability of Electronic Engine Control Systems of Skoda Car
Petr V. Senin
Head of the Technical Service Machines Chair of Institute of Mechanics and Power Engineering, National Research Mordovia State University (68 Bolshevistskaya St., Saransk 430005, Russian Federation), Dr.Sci. (Engr.), Professor, ORCID: https://orcid.org/0000-0003-3400-7780, Researcher ID: H-1219-2016, This email address is being protected from spambots. You need JavaScript enabled to view it.
Dmitriy A. Galin
Associate Professor of the Technical Service Machines Chair of Institute of Mechanics and Power Engineering, National Research Mordovia State University (68 Bolshevistskaya St., Saransk 430005, Russian Federation), Cand.Sci. (Engr.), ORCID: https://orcid.org/0000-0002-2858-2685, Researcher ID: AGA-8511-2022, This email address is being protected from spambots. You need JavaScript enabled to view it.
Leonid O. Krush
Postgraduate Student of the Technical Service Machines Chair of Institute of Mechanics and Power Engineering, National Research Mordovia State University (68 Bolshevistskaya St., Saransk 430005, Russian Federation), ORCID: https://orcid.org/0000-0002-0876-0739, Researcher ID: AGA-8642-2022, This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Introduction. Some physical processes active in the electronic engine control systems lead to wear and tear of the system elements. Experience in operating and diagnosing vehicles at the service station has shown that there is the operation of vehicles with failures, many of which subsequently lead to malfunctions of different complexities. The purpose of the study is to apply diagnostics for determining the operational reliability and assessing the technical condition of electronic engine control systems.
Materials and Methods. A batch of cars was selected to assess the operational reliability of modern electronic engine control system. There were carried out experimental tests of Skoda Octavia cars with 1.8 TSI CDAB 152 hp Euro5 engine and CDAA 160 hp Euro5 engine. The sample consisted of 60 vehicles. Every vehicle was registered for diagnostics, pre-maintenance and computer diagnostics. After a short test, the vehicle was taken back to the service station and subjected to a detailed diagnosis of the electronic engine control system.
Results. The results of analyzing reliability of the main elements of the electronic engine control system have been obtained. It can be concluded that most of the failures of the structural elements of the electronic engine control system occur within the actuators of the system, which have moving elements, sensors measuring the parameters of the system wear out to a lesser extent. The analysis of dependence of failure rates of the fuel pump pressure regulator on operating time intervals has been carried out.
Discussion and Conclusion. It was determined that the spark plugs have the least mileage lifetime. At the same time, the failure within the fuel pressure regulator of the car fuel system occurs most frequently (19.8% of total). The resource of this element of the electronic engine control system averages 125,000 km. It is proved that diagnostics using modern technological equipment is effective.
Keywords: diagnostics, fuel pressure, injector, fault code, electronic engine control system, electronic control unit, throttle valve, high pressure fuel pump, scanner, performance
Conflict of interest: The authors declare no conflict of interest.
For citation: Senin P.V., Galin D.A., Krush L.О. Using Diagnostics to Research the Operational Reliability of Electronic Engine Control Systems of Skoda Car. Engineering Technologies and Systems. 2022;32(2):235‒248. doi: https://doi.org/10.15507/2658-4123.032.202202.235-248
Contribution of the authors:
P. V. Senin – scientific guidance, development of the terms of reference for the study.
D. A. Galin – conducting scientific research, text preparation, mathematical calculation, analysis of the research results.
L. O. Krush – preparation and analysis of literary data, conducting scientific research, analysis of the results.
All authors have read and approved the final manuscript.
Submitted 09.03.2022; approved after reviewing 11.04.2022;
accepted for publication 20.04.2022
REFERENCES
1. Villforth J., Kulzer A.C., Deeg H.-P., et al. Methods to Investigate the Importance of eFuel Properties for Enhanced Emission and Mixture Formation. In: SAE Technical Papers. SAE 15th International Conference on Engines and Vehicles, ICE. 2021. doi: https://doi.org/10.4271/2021-24-0017
2. Komorska I., Wołczyński Z, Borczuch A. Diagnosis of Sensor Faults in a Combustion Engine Control System with the Artificial Neural Network. Diagnostyka. 2019;20(4):19‒25. doi: https://doi.org/10.29354/diag/110440
3. Chen T., Wang X., Zhao H., et al. Control and Optimization of Spark Ignition–Controlled Auto-Ignition Hybrid Combustion Based on Stratified Flame Ignition. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 2019;233(12):3057‒3073. doi: https://doi.org/10.1177/0954407018817626
4. Poorghasemi K., Saray R.K., Ansari E., et al. Effect of Diesel Injection Strategies on Natural Gas/Diesel RCCI Combustion Characteristics in a Light Duty Diesel Engine. Applied Energy. 2017;199:430‒446. doi: https://doi.org/10.1016/j.apenergy.2017.05.011
5. Song Q., Gao W., Zhang P., et al. Detection of Engine Misfire Using Characteristic Harmonics of Angular Acceleration. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 2019;233(14):3816‒3823. doi: https://doi.org/10.1177/0954407019834104
6. Rossi E., Hummel S., Cupo F., et al. Experimental and Numerical Investigation for Improved Mixture Formation of an eFuel Compared to Standard Gasoline. In: SAE Technical Papers. SAE 15th International Conference on Engines and Vehicles, ICE. 2021. doi: https://doi.org/10.4271/2021-24-0019
7. Zhang P., Gao W., Li Y., Wang Y. Misfire Detection of Diesel Engine Based on Convolutional Neural Networks. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 2021;235(8):2148‒2165. doi: https://doi.org/10.1177/0954407020987077
8. Kannadhasan A. Self Diagnostic Cars: Using Infotainment Electronic Control Unit. In: SAE Technical Papers. 17th Symposium on International Automotive Technology. 2021. doi: https://doi.org/10.4271/2021-26-0027
9. Kihas D., Khaled N., Kihas D., et al. Concept Analysis and Initial Results of Engine-Out NOx Estimator Suitable for on ECM Implementation. In: SAE Technical Papers. SAE 2016 World Congress and Exhibition. 2016. doi: https://doi.org/10.4271/2016-01-0611
10. Price K.S., Wang L., Pauly T. Evaluation of Field NOx Performance of Diesel Vehicles Using ECM - Provided OBD/SAEJ1979 Data. In: SAE Technical Papers. SAE 2015 World Congress and Exhibition. 2015. doi: https://doi.org/10.4271/2015-01-1067
11. Krush L.O., Galin D.A. Development of a Device for Determining the Magnetic Field Based on Arduino Uno Microcontroller. Sura Bulletin. 2021;13(1):47‒51. (In Russ.) doi: https://doi.org/10.36461/2619-1202_2021_13_01_009
12. Azizahwati A., Rahmad M., Hidayat F. Development of a Circular Motion Experimental Device Using an Arduino Uno Microcontroller. In: Journal of Physics: Conference Series. Universitas Riau International Conference on Science and Environment (11–13 September 2020). Vol. 1655. Pekanbaru; 2020. doi: https://doi.org/10.1088/1742-6596/1655/1/012154
13. Takeuchi Y., Oike H., Ishikawa T. Development of Motor Health Examination System Using Arduino Uno. In: 23rd International Conference on Electrical Machines and Systems (24–27 November 2020). Hamamatsu; 2020. doi: https://doi.org/10.23919/ICEMS50442.2020.9290982
14. Rezaei R., Schwalbe J., Weber M., et al. Model-Based Development and OBD Calibration for Heavy-Duty Applications. In: Proceedings of China SAE Congress 2020: Selected Papers. Lecture Notes in Electrical Engineering. Vol. 769. Springer: Singapore; 2020. p. 753‒770. doi: https://doi.org/10.1007/978-981-16-2090-4_45
15. Mirmohammadsadeghi M., Zhao H., Ito A. Optical Study of Gasoline Substitution Ratio and Diesel Injection Strategy Effects on Dual-Fuel Combustion. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 2020;234(4):1075‒1097. doi: https://doi.org/10.1177/0954407019864013
16. Daily J., Kongs A., Johnson J., Corcega J. Extracting Event Data from Memory Chips within a Detroit Diesel DDEC v. In: SAE Technical Papers. SAE 2015 World Congress and Exhibition. 2015. doi: https://doi.org/10.4271/2015-01-1450
17. Krogerus T.R., Hyvönen M.P., Huhtala K.J. A Survey of Analysis, Modeling, and Diagnostics of Diesel Fuel Injection Systems. Journal of Engineering for Gas Turbines and Power. 2016;138(8). doi: https://doi.org/10.1115/1.4032417
18. Krivoshapov S. Development of a Piston Fuel Flow Meter Based on a Microcontroller and Its Use for Vehicle Diagnostics. In: SAE Technical Papers. SAE 2021 Powertrains, Fuels and Lubricants Digital Summit, FFL. 2021. doi: https://doi.org/10.4271/2021-01-1150
19. Selvam H.P., Shekhar S., Northrop W.F. Prediction of NOx Emissions from Compression Ignition Engines Using Ensemble Learning-Based Models with Physical Interpretability. In: SAE Technical Papers. SAE 15th International Conference on Engines and Vehicles, ICE. 2021. doi:
20. Accurso F., Zanelli A., Rolando L., Millo F. Real Time Energy Management Control Strategies for an Electrically Supercharged Gasoline Hybrid Vehicle. In: SAE Technical Papers. SAE 2020 World Congress Experience, WCX. 2020. doi: https://doi.org/10.4271/2020-01-1009
21. De Robbio R., Cameretti M.C., Mancaruso E., et al. Combined CFD ‒ Experimental Analysis of the In-Cylinder Combustion Phenomena in a Dual Fuel Optical Compression Ignition Engine. In: SAE Technical Papers. SAE 15th International Conference on Engines and Vehicles, ICE. 2021. doi: https://doi.org/10.4271/2021-24-0012
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