Dynamic Modeling and Standstill Identification for Induction Motor Drives

This dissertation deals with dynamic modeling and standstill self-commissioning of a three-phase induction motor drive. Induction motor is the most popular rotating electrical machine, whose main benefits are simplicity and robustness. A variable-speed induction motor drive is not only suitable for for almost all fields of industry, but also for technologies including electric vehicles. An accurate and efficient control improves the overall efficiency of the drive and its application. High-performance control methods are often based on the dynamic model of the machine. As the electrical machines highly saturate during normal operation, the dynamic model must include the magnetic saturation. Objective of this dissertation is to develop a robust and reliable standstill identification method, which can be implemented into the standard frequency converter. A majority of the induction machines are low-power machines (< 100 kW). These machines are often equipped with closed rotor slots and deep rotor bars. The thin bridges closing the rotor slots saturate highly as a function of the rotor current. The impedance of the rotor bars also varies much as a function of the rotor current frequency due to the deep-bar effect. The standstill identification requires to use high-frequency excitations moving through the rotor. If this kind of excitations are used, the effects of slot-bridge saturation and deep rotor bars must be compensated for. To be able to develop a robust and reliable identification method, an extended dynamic model, which takes into account the above mentioned effects, is first developed. The model extensions can be plugged into a standard machine model and parametrized easily. The proposed model can also be applied to time-domain simulations, real-time control, and identification. 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, during which 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 accounting for 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 designed model and the identification method are experimentally evaluated using 2.2-kW, 5.6-kW and 45-kW induction machines.