Neural Networks Models Usage in Methods for Combustion Process Information Extraction in IC Engines
Апстракт
The In-cylinder pressure profile contains valuable information on the combustion process and its availability is greatly desirable in closed loop IC Engine control systems. The low lifetime and high costs of the currently available sensors are still preventing high-volume production of in-cylinder based engine control system. This paper deals with the potentials of Artificial Neural Networks (ANN) and their application in combustion features extraction, based solely on the crankshaft angular speed measurements. The focus of this paper is put on two concepts of ANN, based on a radial basis function (RBF) and a local linear Neuro-fuzzy models (LLNFM) and their applicability in virtual sensing of crucial combustion process parameters. Training and validation of the suggested ANN models is based on comprehensive engine test bed data set.
Кључне речи:
engine combustion analysis / neural networks / combustion features extractionИзвор:
Proceedings of the 11th International Conference on Accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2013), 2013, 917-922Издавач:
- University of Banja Luka, Faculty of Mechanical Engineering
Финансирање / пројекти:
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Miljić, Nenad AU - Popović, Slobodan AU - Tomić, Miroljub V. AU - Kitanović, Marko AU - Mrđa, Predrag D. PY - 2013 UR - https://machinery.mas.bg.ac.rs/handle/123456789/4690 AB - The In-cylinder pressure profile contains valuable information on the combustion process and its availability is greatly desirable in closed loop IC Engine control systems. The low lifetime and high costs of the currently available sensors are still preventing high-volume production of in-cylinder based engine control system. This paper deals with the potentials of Artificial Neural Networks (ANN) and their application in combustion features extraction, based solely on the crankshaft angular speed measurements. The focus of this paper is put on two concepts of ANN, based on a radial basis function (RBF) and a local linear Neuro-fuzzy models (LLNFM) and their applicability in virtual sensing of crucial combustion process parameters. Training and validation of the suggested ANN models is based on comprehensive engine test bed data set. PB - University of Banja Luka, Faculty of Mechanical Engineering C3 - Proceedings of the 11th International Conference on Accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2013) T1 - Neural Networks Models Usage in Methods for Combustion Process Information Extraction in IC Engines EP - 922 SP - 917 UR - https://hdl.handle.net/21.15107/rcub_machinery_4690 ER -
@conference{ author = "Miljić, Nenad and Popović, Slobodan and Tomić, Miroljub V. and Kitanović, Marko and Mrđa, Predrag D.", year = "2013", abstract = "The In-cylinder pressure profile contains valuable information on the combustion process and its availability is greatly desirable in closed loop IC Engine control systems. The low lifetime and high costs of the currently available sensors are still preventing high-volume production of in-cylinder based engine control system. This paper deals with the potentials of Artificial Neural Networks (ANN) and their application in combustion features extraction, based solely on the crankshaft angular speed measurements. The focus of this paper is put on two concepts of ANN, based on a radial basis function (RBF) and a local linear Neuro-fuzzy models (LLNFM) and their applicability in virtual sensing of crucial combustion process parameters. Training and validation of the suggested ANN models is based on comprehensive engine test bed data set.", publisher = "University of Banja Luka, Faculty of Mechanical Engineering", journal = "Proceedings of the 11th International Conference on Accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2013)", title = "Neural Networks Models Usage in Methods for Combustion Process Information Extraction in IC Engines", pages = "922-917", url = "https://hdl.handle.net/21.15107/rcub_machinery_4690" }
Miljić, N., Popović, S., Tomić, M. V., Kitanović, M.,& Mrđa, P. D.. (2013). Neural Networks Models Usage in Methods for Combustion Process Information Extraction in IC Engines. in Proceedings of the 11th International Conference on Accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2013) University of Banja Luka, Faculty of Mechanical Engineering., 917-922. https://hdl.handle.net/21.15107/rcub_machinery_4690
Miljić N, Popović S, Tomić MV, Kitanović M, Mrđa PD. Neural Networks Models Usage in Methods for Combustion Process Information Extraction in IC Engines. in Proceedings of the 11th International Conference on Accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2013). 2013;:917-922. https://hdl.handle.net/21.15107/rcub_machinery_4690 .
Miljić, Nenad, Popović, Slobodan, Tomić, Miroljub V., Kitanović, Marko, Mrđa, Predrag D., "Neural Networks Models Usage in Methods for Combustion Process Information Extraction in IC Engines" in Proceedings of the 11th International Conference on Accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2013) (2013):917-922, https://hdl.handle.net/21.15107/rcub_machinery_4690 .