Magnetization Curve Identification of Vector-Controlled Induction Motor at Low-Load Conditions

Abstract

In many drives the induction motor torque is transferred to the load through complex mechanical connections which produce an initial load. In such cases, to identify the magnetization curve by the no-load test it is necessary to decouple the motor from the transfer gear what is expensively and time-consuming. In an attempt to avoid the motor mechanical decoupling in the case of hoist crane systems, in this paper a method is proposed for the magnetization curve identification of the indirect rotor flux oriented (IRFO) induction machine at low-load conditions. Two flux controllers with estimated feedback quantities are added to the basic structure of the IRFO control drive. One of these controllers is used to control desired operating point on the magnetization curve and the other for on-line adaption of the reference frame position. The proposed algorithm is implemented in a commercial drive as a part of the self-commissioning module. Afterward, the magnetization curve of the 22 kW induction motor was identified and compared with the one obtained by the no-load test. The method sensitivity to the load torque and the transient inductance has also been considered.

Božo Terzić

Full Professor | Department of Electrical Drives and Industrial Control

Full professor at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split, with significant contributions in the field of industrial development projects including the design of prototypes of electronic converters used in industrial plants around the world. His research interests are focused on the application of electronic converters in electric drives and renewable energy sources.

Marin Despalatović

Full Professor | Department of Electrical Drives and Industrial Control

Full professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, where he teaches courses Electric Machines, Electric Drive Systems, and Electromechanical System Modeling. His research focuses on power systems, energy storage, and smart grid technologies, with active participation in multiple national and international projects aimed at advancing energy infrastructure and improving system stability.