| Issue |
E3S Web Conf.
Volume 638, 2025
International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 9 | |
| Section | Energy Efficiency and Applied Thermodynamics | |
| DOI | https://doi.org/10.1051/e3sconf/202563801007 | |
| Published online | 16 July 2025 | |
Software-based methodology for investigating the performance of an adapted model for improving the energy efficiency of induction motor drives
University of Ruse, Department of Electrical Power Engineering, 7017 Ruse, Bulgaria
* Corresponding author: pdinolova@uni-ruse.bg
This paper presents a software-based methodology for evaluating the performance and practical applicability of an adapted theoretical model aimed at improving the energy efficiency of induction motor drives. The methodology includes stages for data acquisition, processing, and analysis using specially developed and existing software tools. Applying the developed tool to an induction motor drive in a metal cutting machine shows an average current of 4.07 A under no-load conditions and 4.44 A under load, with corresponding standard deviations of 0.0253 A and 0.177 A. The results indicate potential annual energy savings of over 5400 kWh by increasing load utilization. The methodology is justified as universal and easily adaptable for various industrial applications, demonstrating a high degree of automation and an analysis tailored for energy managers.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.