Notice: Undefined index: linkPowrot in C:\wwwroot\wwwroot\publikacje\publikacje.php on line 1275
Publikacje
Pomoc (F2)
[32194] Artykuł:

Genetic-fuzzy model of diesel engine working cycle

Czasopismo: Bulletin of the Polish Academy of Sciences: Technical Sciences   Tom: 58, Zeszyt: 4, Strony: 665-671
ISSN:  0239-7528
Wydawca:  POLISH ACAD SCIENCES DIV IV, PALAC KULTURY I NAUKI, PO BOX 20, PL DEFILAD1, WARSAW, 00-901, POLAND
Opublikowano: Grudzień 2010
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Procent
udziału
Liczba
punktów
Michał Kekez orcid logoWMiBMKatedra Mechaniki**504.50  
Leszek Radziszewski orcid logoWMiBMKatedra Mechaniki**504.50  

Grupa MNiSW:  Publikacja w recenzowanym czasopiśmie wymienionym w wykazie ministra MNiSzW (część B)
Punkty MNiSW: 9
Klasyfikacja Web of Science: Article; Proceedings Paper


Pełny tekstPełny tekst     DOI LogoDOI     Web of Science Logo Web of Science    
Keywords:

diesel engines  modeling  fuzzy systems  genetic algorithms  biofuels 



Abstract:

This paper concerns measurement and modeling of cylinder pressure in diesel engines. The aim of this paper is to build the empirical-analytical model of engine working cycle. The experiments on engine test bench were conducted. The new genetic-fuzzy system GFSm was proposed. By means of GFSm, the engine working cycle model was built. This model allows simulation of cylinder pressure for each allowable crankshaft speed, and loads and also for several biofuels. The model can be used to evaluate the quality of working cycles of piston engine with an accuracy required in practical technical applications.



B   I   B   L   I   O   G   R   A   F   I   A
1. T. Rychter and A. Teodorczyk, Theory of Piston Engines, Wydawnictwa Komunikacji i Łączności, Warszawa, 2006, (in Polish).
2. A. A. Amsden, KIVA-3V: a Block-Structured KIVA Program for Engines with Vertical or Canted Valves, Los Alamos National Laboratory, Los Alamos, 1997.
3. R. Gessing, "Whether the opinion about superiority of fuzzy controllers is justified", Bull. Pol. Ac.: Tech. 58 (1), 59-65 (2010).
4. T. Witkowski, P. Antczak, and A. Antczak, "Multi-objective decision making and search space for the evaluation of production process scheduling", Bull. Pol. Ac.: Tech. 57 (3), 195-208 (2009).
5. S. A. Kalogirou, "Artificial intelligence for the modeling and control of combustion processes: a review", Progress in Energy and Combustion Science 29, 515-566 (2003).
6. F. Kimmich, A. Schwarte, and R. Isermann, "Fault detection for modern Diesel engines using signal- and process modelbased methods", Control Eng. Practice 13, 189-203 (2005).
7. K. Brzozowski, and J. Nowakowski, "An application of artificial neural network to exhaust emission modelling from diesel engine", J. KONES 12 (1-2), 51-58 (2005).
8. S. Jakubek and N. Keuth, "A local neuro-fuzzy network for high-dimensional models and optimization", Eng. Applications of Artificial Intelligence 19, 705-717 (2006).
9. S. H. Lee, R. J. Howlett, S. D. Walters, and C. Crua, "Fuzzy logic and neuro-fuzzy modelling of diesel spray penetration: a comparative study", J. Intelligent and Fuzzy Systems 18 (1), 43-56 (2007).
10. D. Kurczyński, "Influence of vegetable fuels and its blends with diesel oil on parameters of work of compression ignition engine", PhD Thesis, Kielce University of Technology, Kielce, 2007.
11. M. Kekez, "Modeling of work of compression ignition internal combustion engine with use of artificial intelligence methods", PhD Thesis, Kielce University of Technology, Kielce, 2008.
12. O. Cordon, F. Gomide, F. Herrera, F. Hoffman, and L. Magdalena, "Ten years of genetic fuzzy systems: current framework and new trends", Fuzzy Sets and Systems 141, 5-31 (2004).
13. O. Cordon, F. Herrera, F. Hoffman, and L. Magdalena, Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases (Advances in Fuzzy Systems - Applications and Theory 19), World Scientific, Singapore, 2001.