RESEARCH PAPER
Internal combustion engine diagnostics using statistically processed Wiebe function
| 1 | VSB – Technical University Ostrava, Faculty of Mechanical Engineering, Institute of Transport, 17. Listopadu 15, Ostrava – Poruba, 708 00, Czech Republic |
| 2 | University of Zilina, Faculty of Operations and Economic of Transport and Communications, Department of Road and Urban Transport, Univerzitna 1, 010 26, Zilina, Slovakia |
Publication date: 2021-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(3):505–511
HIGHLIGHTS
- Assessment of variability of the combustion process using the Wiebe function.
- Procedure for obtaining the lower and upper limit of the Wiebe function and utilization for diagnostics.
- More accurate determination of the angle of fuel burning beginning.
- Statistical test of relative frequencies for combustion process variability evaluation has been used.
- Procedures are usable for different computational methods of Wiebe function parameters calculation.
KEYWORDS
automotive engineeringengine diagnosticsWiebe functionparameters estimationstatisticstechnical condition
ABSTRACT
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.
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