Examples of the use of the embedded systems for the long-term collection of slowly-changing parameters in the traction of a car

• Autorzy: Wołczyński Zbigniew

Identyfikatory

DOI

10.19206/CE-142028

• Języki publikacji: EN

Abstrakty

EN

The article presents how embedded systems can be used to collect data in the long-term traction of a car. It is assumed that the long period is the time of a travelled distance, e.g. a few thousands of kilometres, or a time, e.g. a month. Such data can be used to optimize the control systems and to diagnose unusual faults in mechatronic systems. The research paper presents how, with the use of very cheap devices, it is possible to collect data that quite often could not be collected even with the use of very expensive measuring devices. The possibility of simple analysis of signals in real time was also pointed out.

Słowa kluczowe

EN

embedded system; collecting data; archiving data; software; signal matching systems; real time analysis

PL

system wbudowany; gromadzenie danych; archiwizacja danych; oprogramowanie; układy dopasowania sygnałów; analiza w czasie rzeczywistym

• Wydawca: Polskie Towarzystwo Naukowe Silników Spalinowych
• Czasopismo: Combustion Engines
• Rocznik: 2021
• Tom: R. 60, nr 4
• Strony: 106--112
• Opis fizyczny: Bibliogr. 9 poz., fot. kolor., rys., wykr.

Twórcy

autor

Wołczyński Zbigniew

• Faculty of Mechanical Engineering, Kazimierz Pulaski University of Technology and Humanities in Radom

• https://orcid.org/0000-0002-7560-1770

Bibliografia

• [1] LOIS, D., WANG, Y., BOGGIO-MARZET, A. et al. Multi-variate analysis of fuel consumption related to eco-driving: Interaction of driving patterns and external factors. Transportation Research Part D: Transport and Environment. 2019, 72, 232-242. https://doi.org/10.1016/j.trd.2019.05.001
• [2] HUERTAS, J.I., DÍAZ, J., GIRALDO, M. et al. Eco-driving by replicating best driving practices. International Journal of Sustainable Transportation. 2018, 12, 107-116. https://doi.org/10.1080/15568318.2017.1334107
• [3] PUCHALSKI, A., KOMORSKA, I. Driving style analysis and driver classification using OBD data of a hybrid electric vehicle. Transport Problems. 2020, 15(4), 83-94. https://doi.org/10.21307/tp-2020-050
• [4] FAFOUTELLIS, P., MANTOUKA, E.G., VLAHOGIANNI, E.I. Eco-driving and its impacts on fuel efficiency: An overview of technologies and data-driven methods. Sustainability. 2021, 13(1), 226. https://doi.org/10.3390/su13010226
• [5] RIBBENS, W.B. Understanding automotive electronics: an engineering perspective. Butterworth-Heinemann an imprint of Elsevier. 2017, Paperback ISBN: 9780128104347, eBook ISBN: 9780128104354.
• [6] MCROBERTS, M. Begining Arduino. Apress 2011.
• [7] CICOLANI, J. Beginning Robotics with Raspberry Pi and Arduino. Apress 2018.
• [8] ISERMANN, R. Mechatronic systems - Innovative products with embedded control. Control Engineering Partice. 2008, 16(1), 14-29. https://doi.org/10.1016/j.conengprac.2007.03.010
• [9] Gage. Egmont Instruments. http://www.egmont.com.pl/gage/techn/dso_PCI.html

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).