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Internal combustion engine diagnostics using statistically processed Wiebe function

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The aim of the article is to present the concept of an indirect diagnostic method using the assessment of the variability of the amount of released heat (mass fraction burn) and the heat release rate. The Wiebe function for the assessment of variability has been used. The Wiebe function parameters from the course of the high-pressure indication in the cylinder of internal combustion engine using linear regression have been calculated. From a sufficiently large number of measured samples, the upper and lower limits of the Wiebe function parameters have been statistically determined. Lower and upper limits characterize variability of the heat release process not only in terms of quantity but also in terms of heat release rate. The assessment of variability is thus more complicated than using one integral indicator, typically the mean value of amount of the released heat. The procedure enabling a more accurate estimation of heat generation beginning has been shown. For the combustion process variability assessment of the engine, statistical test of relative frequencies has been used.
Rocznik
Strony
505--511
Opis fizyczny
Bibliogr. 34 poz., rys., tab.
Twórcy
autor
  • VSB – Technical University Ostrava, Faculty of Mechanical Engineering, Institute of Transport, 17. Listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
  • VSB – Technical University Ostrava, Faculty of Mechanical Engineering, Institute of Transport, 17. Listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
  • VSB – Technical University Ostrava, Faculty of Mechanical Engineering, Institute of Transport, 17. Listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
  • VSB – Technical University Ostrava, Faculty of Mechanical Engineering, Institute of Transport, 17. Listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
  • University of Zilina, Faculty of Operations and Economic of Transport and Communications, Department of Road and Urban Transport, Univerzitna 1, 010 26, Zilina, Slovakia
  • VSB – Technical University Ostrava, Faculty of Mechanical Engineering, Institute of Transport, 17. Listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
Bibliografia
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  • 2. Dresler P. Analysis of Gas Exchange Process in Cylinder of Reciprocating Combustion Engine, Disertation thesis, VSB - TU Ostrava 2018, ISBN 978-80-248-4250-9.
  • 3. Famfulik J, Mikova J, Lanska M, Richtar M. A stochastic model of the logistics actions required to ensure the availability of spare parts during maintenance of railway vehicles. Proceedings of the institution of mechanical engineers' part F - Journal of Rail and Rapid Transit 2014; 228, (1): 85- 92, https://doi.org/10.1177/0954409712465695.
  • 4. Ghojel J I. Review of the development and applications of the Wiebe function: a tribute to the contribution of Ivan Wiebe to engine research. International Journal of Engine Research, 2010; 11(4), 297-312, https://doi.org/10.1243/14680874JER06510.
  • 5. Giglio V, di Gaeta A. Novel regression models for wiebe parameters aimed at 0D combustion simulation in spark ignition engines, Energy, Elsevier 2020; 210(C), https://doi.org/10.1016/j.energy.2020.118442.
  • 6. Hellström E, Stefanopoulou A, Jiang L. A linear least-squares algorithm for double-wiebe functions applied to spark-assisted compression ignition, Journal of Engineering for Gas Turbines and Power 2014; 136(9): 091514, https://doi.org/10.1115/1.4027277.
  • 7. Heywood J B, Internal Combustion Engine Fundamentals, Second Edition, McGraw-Hill Education: New York 2018, ISBN:9781260116106,https://www.accessengineeringlibrary.com/content/book/9781260116106
  • 8. Knefel T, Nowakowski J. Model-based analysis of injection process parameters in a common rail fuel supply system. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (1): 94-101, https://doi.org/10.17531/ein.2020.1.11.
  • 9. Koszałka G. Model of operational changes in the combustion chamber tightness of a diesel engine. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2014; 16 (1): 133-139.
  • 10. Koszałka G. Changes in the tightness of the combustion chamber of an diesel engine during long-term operation, Journal of KONES Powertrain and Transport 2010; 17(3): 217-222.
  • 11. Liu J, Dumitrescu C E. Investigation of Multistage Combustion Inside a Heavy-Duty Natural-Gas Spark-Ignition Engine Using Three-Dimensional Computational Fluid Dynamics Simulations and the Wiebe-Function Combustion Model. ASME The Journal of Engineering for Gas Turbines and Power 2020; 142(10), 101012, https://doi.org/10.1115/1.4045869.
  • 12. Liu J, Dumitrescu C E. Single and double Wiebe function combustion model for a heavy-duty diesel engine retrofitted to natural-gas spark-ignition. Applied Energy, Elsevier 2019; 248(C): 95-103, https://doi.org/10.1016/j.apenergy.2019.04.098, https://doi.org/10.1016/j.apenergy.2019.04.098
  • 13. Maroteaux F, Saad Ch, Aubertin F. Development and validation of double and single Wiebe function for multi-injection mode Diesel engine combustion modelling for hardware-in-the-loop applications, Energy Conversion and Management 2015; 105: 630-641, https://doi.org/10.1016/j.enconman.2015.08.024.
  • 14. Merkisz J, Rymaniak Ł. The assessment of vehicle exhaust emissions referred to CO2 based on the investigations of city buses under actual conditions of operation. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2017; 19 (4): 522-529, https://doi.org/10.17531/ein.2017.4.5.
  • 15. Młynarski S, Pilch R, Smolnik M, Szybka J, Wiązania G. A model of an adaptive strategy of preventive maintenance of complex technical objects. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22(1): 35- 41, https://doi.org/10.17531/ein.2020.1.5.
  • 16. Paszkowski W. Modeling of vibroacoustic phenomena using the method of parameterizing the audio signal. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (3): 501-507, https://doi.org/10.17531/ein.2020.3.13.
  • 17. Paszkowski W. The assessment of acoustic effects of exploited road vehicles with the use of subjective features of sound. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21 (3): 522-529, https://doi.org/10.17531/ein.2019.3.19.
  • 18. Pawlik P. Single-number statistical parameters in the assessment of the technical condition of machines operating under variable load. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21 (1): 164-169, https://doi.org/10.17531/ein.2019.1.19.
  • 19. Pielecha I, Skowron M, Mazanek A. Evaluation of the injectors operational wear process based on optical fuel spray analysis. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018;20 (1): 83- 89, https://doi.org/10.17531/ein.2018.1.11.
  • 20. Rodrigues J, Costa I, Torr es Farinha J, Mendes M, Margalho L. Predicting motor oil condition using artificial neural networks and principal component analysis. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (3): 440-448, https://doi.org/10.17531/ein.2020.3.6.
  • 21. Salkind N J. Encyclopedia of research design (Vols. 1-0). Thousand Oaks, CA: SAGE Publications Inc. 2010, https://doi.org/10.4135/9781412961288.
  • 22. Sejkorova M, Sarkan B, Caban J, Marczuk A. On relationship between infrared spectra of worn out engine oils and their kinematic viscosity. Przemysl Chemiczny, 2018; 97(1): 49-54, https://doi.org/10.15199/62.2018.1.5.
  • 23. Sobaszek Ł, Gola A, Świć A. Time-based machine failure prediction in multi-machine manufacturing systems. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (1): 52-62, https://doi.org/10.17531/ein.2020.1.7.
  • 24. Sofer M, Kucera P, Mazancova E, Krejci L. Acoustic Emission and Fractographic Analysis of Seamless Steel Pressure Cylinders with Artificial Flaws Under Hydrostatic Burst Testing. Journal of Nondestructive Evaluation, Springer New York LLC 2019; 38(3), https://doi.org/10.1007/s10921-019-0627-0.
  • 25. Stanik W, Jakóbiec J, Mazanek A. Engine tests for coking and contamination of modern multi-injection injectors of high-pressure fuel supplies compression-ignition engine. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20 (1): 131-136, https://doi.org/10.17531/ein.2018.1.17.
  • 26. Sui W, Hall M C. Combustion phasing modeling and control for compression ignition engines with high dilution and boost. Proceedings of the Institution of mechanical engineers Part D: Journal of Automobile Engineering, SAGE Publications Ltd. 2019; 233(7): 1834-1850, https://doi.org/10.1177/0954407018790176.
  • 27. Tabaszewski M, Szymański GM. Engine valve clearance diagnostics based on vibration signals and machine learning methods. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (2): 331- 339, https://doi.org/10.17531/ein.2020.2.16.
  • 28. Valis D, Zak L. Vintr Z. Application of fuzzy inference system for analysis of oil field data to optimize combustion engine maintenance. Proceedings of the Institution of mechanical engineers Part D - Journal of Automobile Engineering, SAGE Publications Ltd. 2019; 2: 3736-3745, https://doi.org/10.1177/0954407019833521.
  • 29. Waliszyn A, Adamkiewicz A. A method of vibration damping for diesel engine cylinder liners to prevent the consequences of erosion. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20 (3): 371- 377, https://doi.org/10.17531/ein.2018.3.4.
  • 30. Wolak A, Zając G, Kumbar V. Evaluation of engine oil foaming tendency under urban driving conditions. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20 (2): 229-235, https://doi.org/10.17531/ein.2018.2.07.
  • 31. Wu Y-Y, Wang J H, Mir F M. Improving the Thermal Efficiency of the Homogeneous Charge Compression Ignition Engine by Using Various Combustion Patterns. Energies 2018; 11(11): 3002, https://doi.org/10.3390/en11113002.
  • 32. Yang X, Zhu G G. A control-oriented hybrid combustion model of a homogeneous charge compression ignition capable spark ignition engine. Proceedings of the Institution of mechanical engineers Part D: Journal of Automobile Engineering, SAGE Publications Ltd, 380-1395, https://doi.org/10.1177/0954407012443334.
  • 33. Yasar H, Soyhan H S, Walmsley H, Head B, Sorusbay C. Double-Wiebe function: An approach for single-zone HCCI engine modeling. Applied Thermal Engineering 2008; 28(11): 1284-1290, https://doi.org/10.1016/j.applthermaleng.2007.10.014.
  • 34. Zhu O. A Study Model Predictive Control for Spark Ignition Engine Management and Testing. Dissertation thesis. 1760. Clemson University. 2015. https://tigerprints.clemson.edu/all_dissertations/1760.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9f5ce93e-dda2-4f99-8a54-675028edec1c
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