Gray-Box Loss Model for Induction Motor Drives

Both high-precision and high-efficient torque control of induction motor drives is an important research field due to the extensive use of these motors in torque-controlled applications, e.g. electric vehicles. To achieve high precision, a gray-box rotor flux observer and inverter model have been lately introduced and validated to be effective. Gray-box models (GBMs) combine first-order principles from physics with data-driven identification enabling accurate model performances at low model complexity. Since the effectiveness of an operating strategy significantly depends on the accuracy of the underlying loss model, in this paper, the aforementioned GBMs’ scope is extended to estimate also the power losses in the motor and inverter. Hence, the achieved universal drive model delivers flux, torque, and loss estimations which are substantial for various control tasks, like torque control, operating strategy, or thermal models. In comprehensive test bench investigations, which take into account the entire drive operating range, the measured power losses are compared to the model estimations. This analysis validates that the GBMs can estimate the losses in the motor with a root-mean-square error of 0.47 % and in the inverter with 0.87 %, both related to the nominal mechanical power of the motor.