THE IDENTIFICATION OF INDUCTION MOTOR INTERNAL QUANTITIES

In the presented work a new identification method of difficult measured internal quantities of IM, such as components of magnetic flux vector and electromagnetic torque, is proposed. Commonly measurable quantities of IM like stator currents, stator voltage frequency and mechanical angular speed are used for identification to determine a feedback effect of the rotor flux vector on vector of stator currents of IM. Based on this feedback it is also possible to identify actual value of the rotor resistance, which can alter during IM operation. This has a significant impact on precision of identified quantities as well as on master control of IM. Stability of the identification structure is guaranteed by position of roots of characteristic equation of its linear transfer function. Results obtained from simulation measurements confirm quality, effectivity, feasibility, and robustness of the proposed identification method.

Analysis of Slip Ring Induction Motor Drive Using Slip Power Recovery Scheme with Inverter and Chopper Control for Id Fan in Power Plant

Induction motors are used as industrial drive and for various applications in power plant due to their rugged, robust and simple construction as well as low cost. The speed control of SRIM is dexterous by slip power recovery scheme consisting of inverter control, chopper control, and rotor resistance control techniques. This paper presents the boost in the performance characteristics and energy saving of SRIM drive by inverter and buck-boost chopper based slip power recovery scheme (SPRS). The simulation model of a WRIM drive using inverter and based buck-boost chopper control has been executed in the Simulink platform. The simulation results using inverter and chopper control have been studied. The active power and reactive power have been taken as parameter for analyzing the energy saving by the drive. The simulation result has shown that inverter chopper control SPRS large amount of energy saving.

Influence of Selected Non-Ideal Aspects on Active and Reactive Power MRAS for Stator and Rotor Resistance Estimation

Mathematical models of induction motor (IM) used in direct field-oriented control (DFOC) strategies are characterized by parametrization resulting from the IM equivalent circuit and model-type selection. The parameter inaccuracy causes DFOC detuning, which deteriorates the drive performance. Therefore, many methods for parameter adaptation were developed in the literature. One class of algorithms, popular due to their simplicity, includes estimators based on the model reference adaptive system (MRAS). Their main disadvantage is the dependence on other machines’ parameters. However, although typically not considered in the respective literature, there are other aspects that impair the performance of the MRAS estimators. These include, but are not limited to, the nonlinear phenomenon of iron losses, the effect of necessary discretization of the algorithms and selection of the sampling time, and the influence of the supply inverter nonlinear behavior. Therefore, this paper aims to study the effect of the above-mentioned negative aspects on the performance of selected MRAS estimators: active and reactive power MRAS for the stator and rotor resistance estimation. Furthermore, improved reduced-order models and MRAS estimators that consider the iron loss phenomenon are also presented to examine the iron loss influence. Another merit of this paper is that it shows clearly and in one place how DFOC, with the included effect of iron losses and inverter nonlinearities, can be modeled using simulation tools. The modeling of the IM and DFOC takes place in MATLAB/Simulink environment.

Induction Machine On-Line Parameter Identification for Resource-Constrained Microcontrollers Based on Steady-State Voltage Model

This paper presents a new, computationally modest on-line identification method for the simultaneous estimation of the rotor resistance and magnetizing inductance of an induction machine suitable for electric drives that use an indirect field-oriented control strategy (IFOC), and their control hardware is equipped with a resource-constrained microcontroller. Such drives can be found both in the manufacturing industry and railway traction vehicles in the thousands, having either older control hardware that cannot cope with computationally excessive identification methods or being in cost-sensitive applications, thus being equipped with a low-cost microcontroller. IFOC is a very common control strategy for such drives due to its good dynamic properties and comparatively simple implementation. However, it is sensitive to inaccuracies of rotor resistance and magnetizing inductance. These two parameters change during the operation of the drive, being influenced by the temperature, frequency, and saturation of the magnetic circuit. Improper values of parameters in the controller can degrade the performance of IFOC, resulting in slower acceleration or unnecessary oversaturation of the machine. Respecting these changes can therefore bring significant benefits such as the good dynamic properties of the drive, which can shorten operations in the manufacturing industry or travel times of vehicles. A number of on-line identification methods for monitoring the parameter changes have been published so far, but the majority of them are demanding on microcontroller time or its memory. The proposed method, on the contrary, is comparatively simple and thus easy for implementation with low requirements to the microcontroller. Therefore, it is suitable for both upgrades of existing drives or new low-cost applications. Derivation of the method from the mathematical model and the final algorithm for the microcontroller are presented. The performance of the proposed method is validated with experimental results obtained with a 3.5 kW induction machine drive with an industrial microcontroller during a warming test and under various loads and frequencies.