On-line losses minimization of induction motor vector control

Abstract

On-line losses minimization of induction motor vector controlConventional field-orientated Induction motor drives operate at rated flux even at low load. To improve the efficiency of the existing motor it is important to regulate the flux of the motor in the desired operating range. In this paper a loss model controller (LMC) based on the real coded genetic algorithm is proposed, it has the straightforward goal of maximizing the efficiency for each given load torque. In order to give more accuracy to the motor model and the LMC a series model of the motor which consider the iron losses as a resistance connected in series with the mutual inductance is considered. Digital computer simulation demonstrates the effectiveness of the proposed algorithm and also simulation results have confirmed that this algorithm yields the optimal efficiency.

Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer

“…Variable selection is therefore essential for optimizing motor designs. An example of a common nonlinear programming problem is shown in the following, identifying a large set of motor variables that can be decreased or maximized depending on the desired reduction in complexity or improvement in performance [1][2][3][4][5].…”