Combined Electrical-Thermal Gray-Box Model and Parameter Identification of an Induction Motor

Abstract

Precise modeling and identification of induction motors is becoming increasingly important due to the extensive use of these motors in torque-controlled applications, e.g., electric vehicles. To achieve high precision, several nonideal motor characteristics including thermal effects have to be modeled and identified. Most thermal models in the literature utilize a loss model which is separated from the motor model considered in the control task leading to inconsistencies between these models. In this contribution, a combined electrical-thermal model is developed and its identification is addressed. Hence, the achieved universal drive model delivers flux, torque, loss and temperature estimations. Thus, the model provides information for three main drive tasks: general control, operating strategy and condition monitoring. With a comprehensive data set recorded at the test bench, the model parameters are optimally identified. On a separate test set, the proposed model is validated to estimate the torque generated by the motor with a root-mean-square error of 0.4 % related to nominal torque as well as the temperatures in the stator and rotor with root-mean-square errors of 1.0 K and 1.1 K, respectively.