Online Identification Strategy of Secondary Time Constant and Magnetizing Inductance for Linear Induction Motors

In this article, an online dual-parameter identification strategy for linear induction motors (LIMs) is investigated. Considering the influence of unique end effects in LIMs and the critical impact on control system performance, the magnetizing inductance and secondary time constant are chosen as the targets of estimation. Compared with rotary induction motors, the influence factors in LIMs are much more complex, which can heavily affect the parameter value especially for the high-speed condition. As a result, the online identification is vital for high performance applications. Based on the model reference adaptive system with magnetizing current as state variable, this article starts from the adaptive law of secondary time constant derived by Popov's criterion for hyperstability. Then, the physical significance and stable range are analyzed in details, based on which a handy magnetizing inductance identification method is combined. To further ensure the precision of estimation, one simplification scheme is specially designed. Besides, to eliminate the pure integrator, the derivatives of magnetizing current are chosen as the state variables. Finally, the dual-parameter identification system that utilizes only one PI controller and has low coupling property is constructed. Comprehensive simulation and experiments have fully demonstrated the effectiveness and superiorities of the proposed method.