## 5 Conclusions  
The research showed that the most favourable combination in the unloaded state during acceleration is the VFC n-control mode. The drive then responds without overshooting, and according to the characteristics of proportional-integral (PI) control, there are no peaks in energy consumption, which helps to extend the service life of its components. However, this is also associated with a relatively long stabilisation period. For the same phase of motion under load, the conclusions are identical.  
When the speed setting stabilises and the motor is running without a load, then the V/f, VFC without encoder, and CFC modes show the highest energy efficiency. When a load is added, these are the VFC without encoder, VFC n-control, and CFC.  
The research provides a method of generating KPIs based on processing classical data, natively gathered in frequency converters. It may be useful for maintenance and management dashboards as well as in adaptive control in drive systems, which would apply an appropriate control algorithm depending on the circumstances of the drive operation. It minimises energy losses in technological processes.  
The authors introduced self-defined measures by which the quality of drive operation can be assessed in terms of two important criteria. By applying the studied computational formulas in the frequency converter, the operational Big Data is processed directly in the drive controller (on the edge), allowing it to be the IIoT smart sensor as well, producing data useful in Internet-based management systems.  
As an application of the research results, we proposed the control and indication system (shown in the Figure 12), in which remote access computed in the tested indicators as well as the remote drive configuration enable reaction to the drive conditions manually or automatically (e.g., using decision making algorithms, including artificial intelligence).  
Further research may lead to the determination of the influence of other factors (temperature, vibration, connection quality, etc.) on the KPIs related to control quality and  
Figure 12: Concept of the system where the elaborated edge computations are used in drive management with IIoT devices.  
energy efficiency of commonly used frequency-controlled drives. The application of the study results may improve the functionality of a classical frequency controller and make it a higher-level edge device for making the operational Big Data useful in the IIoT network of the Industry 4.0 plant.  
Conceptualization, M.P.H. and J.M.; data curation, M.P.H. and J.M.; formal analysis, J.M.; investigation, M.P.H. and J.M.; methodology, M.P.H. and J.M.; resources, M.P.H.; software, J.M.; supervision, M.P.H.; validation, M.P.H. and J.M.; visualization, M.P.H. and J.M.; writing--original draft, M.P.H.; writing--review and editing, M.P.H. and J.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the EUROPEAN UNION through the EUROPEAN SOCIAL FUND as a part of the SILESIAN UNIVERSITY OF TECHNOLOGY AS A CENTRE OF MODERN EDUCATION BASED ON RESEARCH AND INNOVATION project, grant number: POWR.03.05.00-00.z098/17-00.  
The authors declare no conflict of interest.