Hybridized Genetic Algorithm Based Machine Parameters Estimation for Direct Torque Control of 3 Phase Motor for Wind Energy Systems

Abstract

It is generally aware that real-time parameter estimation of A.C. induction machine is very important for the efficient operation of vector-controlled drives. However, most existing methods have not taken into account of the four imperfections within the system, i.e. the existence of severe power harmonics due to the PWM inverter drive, the imbalancing of the 3-phase supply from the inverter, the variation of supply frequency under load changing and acceleration/deceleration, and changes in resistance. In this example, we have developed a new method of parameter estimation based on real time data sampling of voltages and currents, no matter they are sinusoidal or not. Here, the assumption of a synchronous rotating speed of the stator flux is not critical. With the aid of hybrid genetic algorithm techniques, the model has been found useful for on-line speed/torque control in most field orientation control schemes as it is much easier to achieve a global minimum during the optimization process.