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Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor
Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor
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Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor
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Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor
Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor

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Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor
Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor
Journal Article

Evaluation of the Effects of Increasing Standard Uncertainty on the Combined Uncertainties: Case of an IE2 5.5 kW Induction Motor

2026
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Overview
Developing electric motors with higher efficiencies for energy savings and environmental protection is crucial. The efficiency of grid-connected induction motors can be measured using various approaches; the preferred method is the indirect approach, which evaluates the separate losses from the additional losses due to residual losses. This approach follows the traditional approach to efficiency determination, introducing experimental procedures to assess additional losses by measuring the torque delivered by the motors. As noted in previous articles, the procedure is complex and requires numerous direct measurements. One area of interest is the determination of measurement uncertainty. This work aims to quantify the sensitivity of the combined uncertainties of losses and efficiency to variations in directly measured input variables: power frequency, rotational speed, torque, power, current, voltage, resistance, coolant temperature, and cold frame temperature. The results presented here help select measurement instrumentation, depending on whether the tests are aimed solely at determining efficiency or whether it is necessary to analyze the trend of the various types of loss, as occurs in optimization and experimental verification processes with high-performance materials, based on a comprehensive analysis of all standard and combined uncertainties, and with experimental data to assign a realistic value to the uncertainties themselves.