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Article information
2021 , Volume 26, ¹ 6, p.54-67
Dobrolubov I.P., Savchenko O.F., Alt V.V., Elkin O.V., Klimenko D.N.
Accuracy of identification of the state of the internal combustion engine with the customized model using the measuring expert system
Purpose and methods. Improving the accuracy of identification for the technical condition of the internal combustion engine (ICE) in operational conditions using the engine measurement expert system (EMSE) is addressed by adjusting the computer dynamic model of the internal combustion engine. Results. Algorithmic schemes of computer models for the state of the ICE are obtained using the equations of its dynamics, which takes into account the factors such as the movement of the fuel supply body, the force on the hook – the load. The structural schemes of modeling at the input of a step-by-step action are presented. A promising method of tuning the model in the EMSE is proposed, which consists of measuring its working processes, in particular the angular acceleration of the crankshaft, for a specific brand of ICE. Then the corresponding set of models of its technical condition is obtained: normal, permissible, limit, pre-accident and emergency. By adjusting the values of the coefficients of these models in the EMSE, they achieve their coincidence with the actual state of the ICE. The identification error is minimized using the gradient method of steepest descent. The presence of several computer models is a practical advantage in the examination of the technical condition of the tested engines allowing its effective implementation in operational conditions. In this case, based on the experience of operation, the computer model closest to the actual state of the ICE is adjusted. At the same time, the efficiency of localization of ICE malfunctions increases, since the coefficients reflecting the state of the engine components and systems are consistently adjusted. Conclusions. The application of the proposed methodology using the criterion of minimizing the identification error by the gradient method allows implementation of this effective method for identifying the state of the ICE. It increases the reliability of determining the technical state of the ICE and its components by adjusting the computer model.
[full text]
Keywords: internal combustion engine, technical condition, model, parameters, identification, error rate, optimization, gradient
doi: 10.25743/ICT.2021.26.6.005
Author(s):
Dobrolubov Ivan Petrovich
Dr. , Professor
Office: Federal State Budgetary Educational Institution of Higher Education Novosibirsk State Agrarian University
Address: 630039, Russia, Novosibirsk, Dobrolyubova str., 160
Phone Office: (383) 267-39-44
E-mail: sof-oleg46@yandex.ru
SPIN-code: 2295-7662Savchenko Oleg Fedorovich
PhD. , Senior Scientist
Position: Leading research officer
Office: Federal state budgetary institution of science of the Siberian Federal scientific centre of agrobiotechnology the Russian Academy of Sciences
Address: 633501, Russia, Krasnoobsk, Dobrolyubova str., 160
Phone Office: (383) 348-39-62
E-mail: sof-oleg46@yandex.ru
SPIN-code: 8198-5827Alt Viktor Valentinovich
Dr. , Academician RAS, Professor
Position: Professor
Office: Federal state budgetary institution of science of the Siberian Federal scientific centre of agrobiotechnology of the Russian Academy of Sciences
Address: 633501, Russia, Krasnoobsk, Dobrolyubova str., 160
Phone Office: (383) 348-35-24
E-mail: sibfti.n@ngs.ru
SPIN-code: 6687-6684Elkin Oleg Vladimirovich
PhD.
Position: Leading research officer
Office: Federal state budgetary institution of science of the Siberian Federal scientific centre of agrobiotechnology the Russian Academy of Sciences, leading researcher
Address: 633501, Russia, Krasnoobsk, Dobrolyubova str., 160
Phone Office: (383) 348-39-62
SPIN-code: 8589-9504Klimenko Denis Nikolaevich
PhD.
Position: Leading research officer
Office: Federal state budgetary institution of science of the Siberian Federal scientific centre of agrobiotechnology the Russian Academy of Sciences, leading researcher
Address: 633501, Russia, Krasnoobsk, Dobrolyubova str., 160
Phone Office: (383) 348-39-62
SPIN-code: 8541-6305 References:
1. Dobrolyubov I.P., Savchenko O.F., Alt V.V. Identifikatsiya sostoyaniya sel’skokhozyaystvennykh ob"ektov izmeritel’nymi ekspertnymi sistemami [Identification of the state of agricultural objects by measuring expert systems]. Novosibirsk: RASKhN. Sib. otd. SibFTI; 2003: 209. (In Russ.)
2. Savchenko O.F., Dobrolyubov I.P., Alt V.V., Olshevskiy S.N. Avtomatizirovannye tekhnologicheskie kompleksy ekspertizy dvigateley [Automated technological complexes for expertise of engines]. Novosibirsk: RASKhN. Sib. otd. SibFTI; 2006: 272. (In Russ.)
3. Dobrolyubov I.P., Alt V.V., Olshevskiy S.N., Savchenko O.F. Patent RF 2543091 S1, MPK G01M15/00; G01M15/04. Sposob opredeleniya ugla operezheniya vpryska topliva dvigatelya vnutrennego sgoraniya i ustroystvo dlya ego osushchestvleniya [Patent RU 2543091 Ñ1, MPK G01Ì15/00; G01Ì15/04. Method for determining the fuel injection advance angle (IAA) for an internal combustion engine and a device for its implementation]. Moscow: FIPS; Ofitsial’nyy byulleten’ “Izobreteniya. Poleznye modeli” No. 6; 27.02.2015: 40. (In Russ.)
4. Dobrolyubov I.P., Alt V.V., Olshevskiy S.N., Savchenko O.F., Klimenko D.N. Patent RF 2721992 S1, MPK G01M15/00; G01M15/04. Sposob opredeleniya tekhnicheskogo sostoyaniya dvigateley vnutrennego sgoraniya i ustroystvo dlya ego osushchestvleniya [Ìethod for determining the technical state of internal combustion engines and a device for its implementation]. Moscow: FIPS; Ofitsial’nyy byulleten’ “Izobreteniya. Poleznye modeli” No. 15; 25.05.2020: 24. (In Russ.)
5. Dobrolyubov I.P., Savchenko O.F. The choice of informative characteristics when using the expert measuring system of an engine. Measurement Techniques. 2005; 48(2):128–132.
6. Dobrolyubov I.P., Savchenko O.F. Optimal set of indirect diagnostic variables for engine measuring expert system. Dvigatelestroyeniye. 2012; (2):30–33. (In Russ.)
7. Dobrolyubov I.P., Savchenko O.F., Olshevskiy S.N. Optimization for determining and measurement of the ICE parameters by an expert system for measurements. Polzunovskiy Vestnik. 2011; (2/2):275–279. (In Russ.)
8. Dobrolyubov I.P., Savchenko O.F., Alt V.V., Olshevskiy S.N., Klimenko D.N. Modeling the process of optimal determination for the parameters of the conditions of internal combustion engine by measuring expert system. Computational Technologies. 2015; 20(6):22–35. (In Russ.)
9. Savchenko O.F., Dobrolyubov I.P. Modeling the process for identification of tractor engine states. Problems of Computational and Applied Mathematics. 2016; 4(6):4–12. (In Russ.)
10. Alt V.V., Dobrolyubov I.P., Savchenko O.F., Olshevskiy S.N. Tekhnicheskoe obespechenie izmeritel’nykh ekspertnykh sistem mashin i mekhanizmov v APK [Technical support for measuring expert systems in agricultural machinery and devices]. Novosibirsk: Rossel’khozakademiya. Sibirskoe regional’noe otdelenie. GNU SibFTI; 2013: 523. (In Russ.)
11. Krogerus T.R., Hyvonen 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):081501. DOI:10.1115/1.4032417.
12. Krivtsov S.N. Methodological approach to the formation of a dynamic model of a diesel car with a battery fuel supply system. Automotive Industry. 2016; (10):10–14. (In Russ.)
13. Kalachin S.V. Increasing the efficiency of research on the basis of the linear mathematical model of machine and tractor unit [Improving the efficiency of research on the basis of a linear mathematical model of a machine-tractor unit]. Niva Povolzhya. 2017; 1(42):72–76. (In Russ.)
14. Panchenko M.N., Grachev V.V., Grishchenko A.V. Analysis of instantaneous turn rate of diesel crank shaft. Transport of the Russian Federation. 2018; 4(77):59–62. (In Russ.)
15. Tormos B., Mart´ın J., Carre˜no R., Ram´ırez L. A general model to evaluate mechanical losses and auxiliary energy consumption in reciprocating internal combustion engines. Tribology International. 2018; (123):161–179. DOI:10.1016/j.triboint.2018.03.007.
16. Grebennikov S.A., Grebennikov A.S., Kiselev G.O., Rogozhin A.V., Usov A.N. Methodology of formless diagnosis of crank mechanism of internal combustion engine. Technical Regulation in Transport Construction. 2020; 3(42):147–155. (In Russ.)
17. Gritsenko A.V., Shepelev V.D., Grakov F.N., Lukomskiy K.I., Salimonenko G.N. Diagnostics of the fuel supply system of auto ices by the test method. Bulletin of the South Ural State University. Series: Mechanical Engineering Industry. 2020; 20(4):71–83. (In Russ.)
18. Dzhalolov U.H., Yunusov N.I., Tursunbadalov U.A., Ziyoev Sh.Sh., Khasanov Dzh.R. Parameters’ identification of acceleration characteristic of internal combustion engine. Bulletin of Perm National Research Polytechnic University. Electrotechnics, Informational Technologies, Control
Systems. 2020; (35):43–56. (In Russ.)
19. Veyts V.A., Kochura A.Å. Dinamika mashinnykh agregatov s dvigatelyami vnutrennego sgoraniya [The dynamics of machinery with internal combustion engines]. Leningrad: Mashinostroenie; 1976: 384. (In Russ.)
20. Eykhoff P. System identification: Parameter and state estimation. London: Wiley-Interscience; 1974: 555
Bibliography link:
Dobrolubov I.P., Savchenko O.F., Alt V.V., Elkin O.V., Klimenko D.N. Accuracy of identification of the state of the internal combustion engine with the customized model using the measuring expert system // Computational technologies. 2021. V. 26. ¹ 6. P. 54-67
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