Abstract
This paper presents an inverse thermal modeling technique to determine the core losses from the temperature rise inside the transformer core. For this purpose, initially, a customized printed circuit board (PCB) with thermal sensors is used to measure the temperature rise. Afterward, a 3D magneto-thermal forward model is developed to validate the temperature rise. The accuracy of the forward model is checked by comparing the simulated core losses and temperature rise of the transformer with experimental measurements for different supply conditions. The results show that the forward model can accurately estimate the core losses with a maximum relative error of less than 2.7% and predict the temperature rise in the core with a maximum relative error of less than 6.2%. Lastly, after ensuring the accuracy of the forward model, an inverse modeling technique is applied to the 3D thermal model to predict the core losses of the transformer directly from the measured temperature rise. The accuracy of the inverse model in estimating the core losses is checked by comparing the results with experimental measurements. The novel approach for the PCB design besides the inverse model shows that the technique can be applied to estimate the core losses directly from the measured temperature rise inside the core with a relative error of 2.7% compared to experiments.
Highlights
T HE increasing use of electrical machines in transportation and rapid industrialization has created the need for designing more efficient electrical machines
FORWARD MODELING This section describes the electromagnetic loss model and thermal model used for simulating the temperature rise of the transformer that occurs in the real situation
The flux density and core loss density are calculated from the measured no-load current i1 and open-circuit voltage u2 (see Fig. 1(a)) by using (1)-(3)
Summary
T HE increasing use of electrical machines in transportation and rapid industrialization has created the need for designing more efficient electrical machines. By measuring the temperature rise at any point in a machine, the losses can be inversely determined This principle was applied in [8]–[12] to estimate the power losses and thermal parameters of electrical machine. Using the lumped parameter thermal network (LPTN) in combination with the experimental measured temperature rise, the net power losses in an induction machine were segregated in [12] by inverse thermal method This approach was used in [10], [13], [14] to identify the thermal parameters used in real time prediction of stator and rotor temperature variations for condition motoring of electrical machine. We present a method to estimate the core losses in a transformer from the measured temperature rise inside the core by inverse modeling technique.
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