Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things
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 a frequency converter. The authors proved that using the proposed solution, it is possible to specify the relation between the control...
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MDPI AG
2021
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oai:doaj.org-article:988664aff8ac4273a98a2181c2dfd4272021-11-11T14:56:49ZFrequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things10.3390/app112197842076-3417https://doaj.org/article/988664aff8ac4273a98a2181c2dfd4272021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/9784https://doaj.org/toc/2076-3417The 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 a 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 the 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 energy efficiency was determined for various control modes.Mariusz Piotr HetmańczykJulian MalakaMDPI AGarticleenergy efficiencyelectric driveelectric motor controlfrequency converterindustrial Internet of Thingsedge computingTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 9784, p 9784 (2021) |
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energy efficiency electric drive electric motor control frequency converter industrial Internet of Things edge computing Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
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energy efficiency electric drive electric motor control frequency converter industrial Internet of Things edge computing Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Mariusz Piotr Hetmańczyk Julian Malaka Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things |
description |
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 a 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 the 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 energy efficiency was determined for various control modes. |
format |
article |
author |
Mariusz Piotr Hetmańczyk Julian Malaka |
author_facet |
Mariusz Piotr Hetmańczyk Julian Malaka |
author_sort |
Mariusz Piotr Hetmańczyk |
title |
Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things |
title_short |
Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things |
title_full |
Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things |
title_fullStr |
Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things |
title_full_unstemmed |
Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things |
title_sort |
frequency converter as a node for edge computing of big data, related to drive efficiency, in industrial internet of things |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/988664aff8ac4273a98a2181c2dfd427 |
work_keys_str_mv |
AT mariuszpiotrhetmanczyk frequencyconverterasanodeforedgecomputingofbigdatarelatedtodriveefficiencyinindustrialinternetofthings AT julianmalaka frequencyconverterasanodeforedgecomputingofbigdatarelatedtodriveefficiencyinindustrialinternetofthings |
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1718437912465375232 |