Data to support the assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring.
Datos para respaldar la evaluación de los métodos de estimación de eficiencia energética en motores de inducción considerando monitoreo en tiempo real.
Date
2020-03-23
2020-03-23
Author
Sousa Santos, Vladimir
Cabello Eras, Juan José
Sagastume, Alexis
Cabello Ulloa, Mario Javier
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Abstract
The data presented in this article was used to assess and compare the most important methods used to estimate the efficiency during the operation of induction motors at different loads and power supply conditions. The experiment was developed in a test bench including a three-phase induction motor of 1.1 kW (De Lorenzo DL 1021). In addition, an adjustable voltage source, a variable-frequency drive, a resistor, and a magnetic powder brake control unit to regulate the load were used during the experiments. A power quality and energy analyzer (Fluke 435 series 6) was used to measure the electric variables during the experiments. Moreover, for the mechanical measures, the sensors of the brake control unit (De Lorenzo DL 1054TT) and a magnetic powder brake (De Lorenzo DL 1019P) were used. In total, 11 load factors were measured at different operation conditions, including balanced sinusoidal voltage, balanced harmonic voltage, unbalanced sinusoidal voltage and unbalanced harmonic voltage. A total of 10 measures were taken for each load factor at each operation condition. The data presented in this paper can be useful in the development and evaluation of new efficiency estimation methods for induction motors, considering different operation conditions and load factors. Moreover, it can serve to assess the impact of the energy quality on the efficiency of induction motors. The data is related to the manuscript “Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring”
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Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring
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