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Parametric Digital Twin of autonomous electric vehicle transmission

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Variable applications and methodologies are used in the Digital Twin technology. Digital Twin as a trending technology is also a general topic of many industry-oriented research projects. To develop and implement a novel technology, a detailed study of any single part of a system is required. This paper presents a development case study of the parametric Digital Twin of autonomous electric vehicle transmission. Digital Twin combines the advantages of software models and real equipment to reduce total test runs and safe maintenance. The primary duty of the Digital Twin is to allow complete synchronization and connectivity between virtual and real entities. The paper presents a detailed structural description of the virtual entity that considers the parametrization of the transmission.
Rocznik
Strony
131--140
Opis fizyczny
Bibliogr. 20 poz., rys., tab.
Twórcy
  • Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Estonia
  • Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Estonia
  • Department of Mechanical and Industrial Engineering, Tallinn University of Technology, Estonia
  • Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Estonia
  • Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Estonia
  • Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Estonia
  • Department of Mechanical and Industrial Engineering, Tallinn University of Technology, Estonia
Bibliografia
  • [1] GRIEVES M., VICKERS J., 2016, Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems Excerpt, Transdisciplinary Perspectives on Complex Systems, August, Springer International Publishing, 23, 889–896.
  • [2] ASAd B., VAIMANN T., RASSÕLKIN A., KALLASTE A., BELAHCEN A., 2019, A Survey of Broken Rotor Bar Fault Diagnostic Methods of Induction Motor, Electr. Control Commun. Eng., 14/2, 117–124, doi: 10.2478/ecce-2018-0014.
  • [3] IEEE Std 3006.3TM, 2017, Recommended Practice for Determining the Impact of Preventative Maintenance on the Reliability of Industrial and Commercial Power Systems, doi: 10.1201/9780429287015-5.
  • [4] BEVILACQUA M., 2020, Digital Twin Reference Model Development to Prevent Operators' Risk in Process Plants, Sustain, 12/3, 1–17, doi: 10.3390/su12031088.
  • [5] FLORKOWSKI M., SZARY D., MOGLESTUE A., 2019, Digital Twins and Simulations: World of Simulation, ABB Rev., 2, 8–13.
  • [6] RASSÕLKIN A., VAIMANN T., KALLASTE A., KUTS V., 2019, Digital Twin for Propulsion Drive of Autonomous Electric Vehicle, 60th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON).
  • [7] RASSÕLKIN A., SELL R., LEIER M., 2018, Development Case Study of the First Estonian Self-Driving Car, ISEAUTO, Electr. Control Commun. Eng., 14/1, 81–88, doi: 10.2478/ecce-2018-0009.
  • [8] RASSÕLKIN A., 2018, Propulsion Motor Drive Topology Selection for Further Development of ISEAUTO Self- Driving Car, 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), doi: 10.1109/RTUCON.2018.8659887.
  • [9] RASSÕLKIN A., 2020, Life Cycle Analysis of Electrical Motor Drive System Based on Electrical Machine Type, Proc. Est. Acad. Sci., 69/2, 162–177, doi: 10.3176/proc.2020.2.07.
  • [10] REVETRIA R., TONELLI F., DAMIANI L., DEMARTINI M., BISIO F., PERUZZO N., 2019, A Real-Time Mechanical Structures Monitoring System Based on Digital Twin, IOT and Augmented Reality, Simulation Series, 51/1, doi: 10.23919/SpringSim.2019.8732917.
  • [11] KUTS V., TAHEMAA T., OTTO T., SARKANS M., LEND H., 2016, Robot Manipulator Usage for Measurement in Production Areas, Journal of Machine Engineering, 16/1, 57–67.
  • [12] FERNANDES C.M.C.G., MARQUES P.M.T., MARTINS R., SEABRA J.H.O., 2015, Influence of Gear Loss Factor on the Power Loss Prediction, Mechanisms and Machine Science, 24, 799–806, doi: 10.1007/978-3-319- 09411-3_84.
  • [13] HINTERSTOIßER M., HÖHN B.R., MICHAELIS K., 2009, Optimization of Gearbox Efficiency, Goriva i Maz. Časopis. za Tribol. Teh. Pod. i Primjen, Tekućih i Plinovitih Goriva i Inžinjerstvo Izgaranja, 48/4, 462–480.
  • [14] MICHAELIS K., HÖHN B.R., HINTERSTOIßER M., 2011, Influence Factors on Gearbox Power Loss, Ind. Lubr. Tribol., 63/1, 46–55, doi: 10.1108/00368791111101830.
  • [15] WIMMER A., SALZGEBER K., HASLINGER R., 2003, WP1 – Analysis of Minimum Oil Requirements Considering Friction in Gears and Engines, Final Report Oil-free Powertrain, EU Project Contract No: IPS-2001-CT-98006.
  • [16] CHANGENET C., PASQUIER M., 2002, Power Losses and Heat Exchange in Reduction Gears: Numerical and Experimental Results, VDI Berichte, 2/1665, 603–613.
  • [17] Gear Research Centre (FZG), https://www.mw.tum.de/en/fzg/research/, (accessed Oct. 28, 2020).
  • [18] Simulation and Computer Programs – Department of Mechanical Engineering, https://www.mw.tum.de/en/fzg/research/simulation-and-computer-programs/, (accessed Oct. 28, 2020).
  • [19] LANGHART J., BAE I., 2014, How to Get Most Realistic Efficiency Calculation for Gearboxes? Int. Gear Conf. 26th–28th August, Lyon, 869–878, doi: 10.1533/9781782421955.869.
  • [20] RASSÕLKIN A., RJABTŠIKOV V., VAIMANN T., KALLASTE A., KUTS V., PARTYSHEV A., 2020, Digital Twin of an Electrica Motor Based on Empirical Performance Model (Accepted), Proceeding of XI International Conference on Electrical Power Drive Systems (ICEPDS).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-71444589-ba6d-4406-bb7b-13bb42d1d041
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