Version 1
: Received: 10 May 2021 / Approved: 11 May 2021 / Online: 11 May 2021 (09:29:10 CEST)
Version 2
: Received: 6 September 2021 / Approved: 8 September 2021 / Online: 8 September 2021 (13:15:18 CEST)
Hetmańczyk, M.P.; Malaka, J. Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things. Appl. Sci.2021, 11, 9784.
Hetmańczyk, M.P.; Malaka, J. Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things. Appl. Sci. 2021, 11, 9784.
Hetmańczyk, M.P.; Malaka, J. Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things. Appl. Sci.2021, 11, 9784.
Hetmańczyk, M.P.; Malaka, J. Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things. Appl. Sci. 2021, 11, 9784.
Abstract
The article presents a method of generating Key Performance Indicators related to electric motor energy efficiency on the basis of Big Data gathered and processed in frequency converter. The authors proved that using the proposed solution it is possible to specify the relation between the control mode of an electric drive and the control quality-energy consumption ratio in the start-up phase as well as in the steady operation with various mechanical loads. The tests were carried out on a stand equipped with two electric motors (one driving, the other used to apply the load by adjusting the parameters of the built-in brake). The measurements were made in two load cases, for motor control modes available in industrially applied frequency converters (scalar V/f, vector Voltage Flux Control without encoder, vector Voltage Flux Control with encoder, vector Current Flux Control and Vector Current Flux Control with torque control). During the experiments values of current intensities (active and output), the actual frequency value, IxT utilization factor, relative torque and the current rotational speed were measured and processed. Based on the data the level of the energy efficiency was determined for various control modes.
Keywords
energy efficiency; electric drive; electric motor control; frequency converter; Industrial Internet of Things; edge computing; Big Data; Key Performance Indicators; KPI; dashboard
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Julian Malaka
Commenter's Conflict of Interests: Author