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001-es BibID:	BIBFORM077793
Első szerző:	Menyhárt József (gépészmérnök, létesítménymérnök, lean szakmérnök)
Cím:	Battery Measurement Methods and Artificial Intelligence Applied in Energy Management Systems / J. Menyhárt, R. Szabolcsi
Dátum:	2019
ISSN:	2498-700X
Megjegyzések:	Diagnostics of batteries using advanced methods have gained remarkable roles in the past few years. This study focuses on the type of measurements, tests and methods to reveal and classify them. During manufacturing and operation several faults could emerge in batteries including non-optimal operation conditions, operators without experience, and finally, random changes in batteries under physical and nonphysical conditions. Improper handling of batteries and battery cells man cause operation failures or, in the worst case, accidents. To reveal these problems several methods are applied in industry and in scientific laboratories. For a comprehensive analysis of battery management, artificial intelligence and Industry 4.0 methods can be used very effectively. Big Data analysis in its standard form is not a new achievement, but other mathematical tools could be applied to control monitoring such as Fuzzy Logic or Support Vector Machine (SVM). They are efficient tools to analyse the deviation of batteries condition because it can detect sudden changes, parameter deviations and anomalies, and the user's behaviour and habits. This article gives a description about the most important battery testing methods and the connection between Big Data and Operation Management with Artificial Intelligent (AI) methods.
Tárgyszavak:	Műszaki tudományok Gépészeti tudományok idegen nyelvű folyóiratközlemény hazai lapban
Megjelenés:	International Journal of Engineering and Management Sciences. - 4 : 1 (2019), p. 428-436. -
További szerzők:	Szabolcsi Róbert (1965-) (gépészmérnök)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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