Standstill Identification of an Induction Motor Model Including Deep-Bar and Saturation Characteristics

Abstract

This paper deals with standstill identification of an induction motor drive for sensorless self-commissioning purposes. The proposed identification method is based on an advanced model of a squirrel-cage induction motor. The model includes the deep-bar effect and the magnetic saturation characteristics. The excitation signals are fed to the stator using a standard inverter without compensating for its nonlinearities. The saturable stator inductance is first identified by means of a robust flux-integration test, where unknown voltage disturbances are canceled with suitably selected current pulses. Then, the deep-bar characteristics are identified by means of a DC-biased sinusoidal excitation using different frequencies. Finally, the cross-saturation characteristics of the rotor leakage inductance are identified by altering the DC bias of the excitation signal. The identified characteristics are transformed to the parameters of the advanced motor model taking into account the interrelations of the above-mentioned phenomena. Since the physical phenomena affecting the standstill identification process are properly included in the identified model, less approximations are needed and more accurate parameter estimates are obtained. The identification procedure is validated by means of experiments using two different induction motors (5.6 kW and 45 kW).