Mateo Bašić

Stator resistance identification based on neural and fuzzy logic principles in an induction motor drive

This paper presents a method for stator resistance identification of an induction motor in an indirect rotor field-oriented control system. This method is based on a simple artificial neural network, in which the rotor time constant is no longer considered to be a constant parameter, but is instead identified using an adaptive model reference system-based procedure. The neural network outputs the estimated rotor speed. The difference between the actual and the estimated rotor speed is used as a signal for either manual or automated fuzzy logic stator resistance identification. Simulations and experiments show the effectiveness of the described approach.

A STAND-ALONE INDUCTION GENERATOR WITH IMPROVED STATOR FLUX ORIENTED CONTROL

A Stand-Alone Induction Generator with Improved Stator Flux Oriented Control This paper presents an improved stator flux oriented (SFO) control system for a stand-alone induction generator. The induction generator supplies a variable resistive dc load. In order to provide an essentially constant terminal voltage, the product of the rotor speed and the stator flux reference should remain constant. However, in this case the control system is not able to function properly at different loads and dc-link voltages. In this paper, we introduce a new algorithm in which this product is constant at certain dc-load and dc-link voltage references. The dependence of the stator flux reference on the dc load and dc voltage reference is mapped using an artificial neural network (ANN). We also present an analysis of the efficiency of the SFO control system, as well as its performance during transients, over a wide range of both dc-link voltage references and loads. The validity of the proposed approach is verified by realistic simulation in a Matlab-Simulink environment.

Online Efficiency Optimization of a Vector Controlled Self-Excited Induction Generator

This paper presents a search-based approach to efficiency optimization of a vector controlled self-excited induction generator (SEIG). The main parts of the control system, besides the SEIG, are a prime mover, a three-phase power converter, and a dc load. The optimization algorithm is executed online and it relies on fuzzy logic (FL) to minimize the internal losses of the SEIG. This is done by adjusting the rotor flux reference. As opposed to existing strategies, additional effort is made to ensure stable operation of the SEIG while the optimization is put on hold and also to avoid the optimization-induced detuning. The iron losses of the SEIG are accounted for in the proposed vector control algorithm as dependent on both the operating flux and frequency. The simulation model of the control system is developed in the MATLAB/Simulink for the purpose of FL controller design, followed by experimental validation. The control algorithm is experimentally implemented using dSpace DS1104 board.

Stator Resistance Tuning Based on a Neural Network in an Indirect Rotor Field Oriented Control System of an Induction Motor

This paper presents an ANN-based (artificial neural network-based) method of stator resistance tuning in an IRFO (indirect rotor field oriented) control system of an induction motor. This method is based on the conventional two-layer ANN in which the rotor time constant is not a constant parameter and is identified using a model reference adaptive system (MRAS) - based procedure. During the training, rotor speed estimation of the induction motor is enabled. The difference between the actual and the estimated rotor speed is used as a signal for manual stator resistance tuning. Computer simulations and experimental results show the effectiveness of the described approach in a low rotor speed region.

Analysis of Power Converter Losses in Vector Control System of a Self–Excited Induction Generator

Abstract This paper provides analysis of losses in the hysteresis-driven three-phase power converter with IGBTs and free-wheeling diodes. The converter under consideration is part of the self-excited induction generator (SEIG) vector control system. For the analysis, the SEIG vector control system is used in which the induction generator iron losses are taken into account. The power converter losses are determined by using a suitable loss estimation algorithm reported in literature. The chosen algorithm allows the power converter losses to be determined both by type (switching/conduction losses) and by converter component (IGBT/diode losses). The overall power converter losses are determined over wide ranges of rotor speed, dc-link voltage and load resistance, and subsequently used for offline correction of the overall control system’s losses (efficiency) obtained through control system simulations with an ideal power converter. The control system’s efficiency values obtained after the correction are compared with the measured values.

Small-Size Induction Machine Equivalent Circuit Including Variable Stray Load and Iron Losses

The paper presents the equivalent circuit of an induction machine (IM) model which includes fundamental stray load and iron losses. The corresponding equivalent resistances are introduced and modeled as variable with respect to the stator frequency and flux. Their computation does not require any tests apart from those imposed by international standards, nor does it involve IM constructional details. In addition, by the convenient positioning of these resistances within the proposed equivalent circuit, the order of the conventional IM model is preserved, thus restraining the inevitable increase of the computational complexity. In this way, a compromise is achieved between the complexity of the analyzed phenomena on the one hand and the model’s practicability on the other. The proposed model has been experimentally verified using four IMs of different efficiency class and rotor cage material, all rated 1.5 kW. Besides enabling a quantitative insight into the impact of the stray load and iron losses on the operation of mains-supplied and vector controlled IMs, the proposed model offers an opportunity to develop advanced vector control algorithms since vector control is based on the fundamental harmonic component of IM variables.

Stray Load and Iron Losses in Small Induction Machines Under Variable Operating Frequency and Flux: A Simple Estimation Method

In this paper, an engineering approach to estimation of the fundamental stray load and iron losses in small induction machines (IMs) is proposed. This approach consists of experimental testing carried on several IMs of different efficiency class and rotor cage material, all rated 1.5 kW, followed by the derivation of simple empirical formulas for estimation of these two types of losses. The iron losses are evaluated as variable with respect to the operating frequency and flux, whereas the stray load losses are evaluated as variable with respect to the operating frequency, flux, and torque. Application of the proposed formulas does not require any additional tests other than those imposed by international standards, and, equally important, they do not include any constructional details of the IM. The validity of the formulas is verified by comparison of the estimated and measured losses in wide ranges of the operating frequency, flux, and torque. The proposed methods of estimation offer possibilities for application in the analysis of small IMs under various operating conditions with sinusoidal supply, as well as in developing advanced IM models and vector control algorithms.

Dynamic simulation model of a quasi-Z-Source inverter with parasitic resistances and saturable inductor

In this paper, an advanced simulation model of a quasi-Z-Source inverter (qZSI) is presented. The model has been built in MATLAB-Simulink by using only standard blocks. It is based upon the qZSIs nonlinear differential equations, i.e., without resorting to state-space averaging and small-signal analysis. In the proposed model, the equations for the non-shoot-through state and those for the shoot-through state are alternately executed, depending on the qZSI state. The parasitic resistances of the qZSI capacitors/inductors as well as the magnetic saturation of the qZSI inductors are all accounted for. The impact of these factors on the qZSIs transient and steady-state performance is evaluated and analyzed both on the simulation and experimental level.

Experimental Method of Determining the Equivalent Circuit Parameters of a Switched Reluctance Machine

This paper presents an equivalent-circuit-based method to experimentally determine the phase inductance and the iron-loss resistance of a switched reluctance machine (SRM). The propose ...