Diagnosing the automobile starting system
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Faculty of Mechanical Engineering at Lublin University of Technology, Poland.
Publication date: 2017-08-01
Combustion Engines 2017,170(3), 19-23
This article presents a new method for analysing the torque of an internal combustion engine using registered electromechanical runs and magnetic field distribution in a starter. The aim of the study was to develop a model of the starting current of an internal combustion engine and carry out verification tests on real objects. The developed model allows to simulate the shutdown of individual cylinders. Experimental research was conducted using the Bosch FSA 740 equipment for four internal combustion engines under variable operating conditions. During testing, the starting current and relative compression in cylinders were recorded. Simulating the variable load of the starter, the magnetic induction distribution of the magnetic induction was recorded in the feed slot. The research will be used to develop a method of diagnosing the starter and determining the torque of the internal combustion engine.
BAY, O., BAYIR, R. A fault diagnosis of engine starting system via starter motors using fuzzy logic algorithm. Gazi Journal University of Science. 2011, 24(3), 437-440.
BURCAN, J., SICZEK K. The durability and reliability of bearing of car starter. Tribology. 2003, 4, 69-78.
DUDZIKOWSKI, I., JANISZEWSKI, S. Analysis of car rmanent-magnet starters. Scientific Papers of The Institute of Electrical Machines, Drives and Measurements of the Wrocław University of Science and Technology Series: Studies and Research. 2000, 20, 167-174.
DZIUBIŃSKI, M., DROZD, A., ADAMIEC, M., SIEMIONEK, E. Simulation tests of the starting system. Poznań University of Technology Academic Journals. Electrical Engineering. 2016, 88, 89-100.
DZIUBIŃSKI, M. Modeling and experimental testing of starting system in means of transport. Monograph, Lublin University of Technology, ISBN 978-83-7947-205-5, Lublin 2016.
EBRAHAMI, E., MOLLAZDADE, K. Intelligent fault classification of a tractor starter motor using vibration monitoring and adaptive neuro fuzzy inference system. InsightNon-Destructive Testing and Condition Monitoring. 2010, 52(10), 561-566.
FUVESI, V., KOVACS, E. Diagnoses of additive faults of serial wounded motor using artificial intelligence methods. Recent Innovations in Mechatronics. 2014, 1(1).
GAD, S., PAWLAK, M. The artificial neural networks as the tool for diagnostics of automotive vehicles. Electrotechnical Review. 2004, 7(8), 693-697.
PSZCZÓŁKOWSKI, J., TRAWIŃSKI, G. Engine crankshaft driving with the help of electric and pneumatic starter. Logistics. 2011, 6, 3499-3508.
ZENG, S., SUN, B., TONG, CH. A modified model of electronic device reliability protection. Maintenance and reliability. 2009, 4, 4-9.
Modeling of failures of the starter electric motor
Andrey Puzakov, S. Bratan
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