Efficiency Optimization in a Pump-Induction Motor Drive, Under Flow Variation, Using Fuzzy Search Controller

This paper presents a fuzzy search controller approach along with the look-up tables, to optimize the efficiency of a pump-induction motor drive. The induction motor and the converter are modeled based on thermal loss; and for modeling the pump and the hydraulic system, which are non-linear and relatively complicated, the neural network is used. In the designed system, in order to optimize the efficiency of the pump and the hydraulic system, the amount of outflow is controlled by adjusting the pump’s rotating speed. Meanwhile by choosing the suitable switching frequency of the inverter and feeding the motor by proper amount of voltage and frequency, the loss amount of the drive system is minimized. Simulation results show that the proposed controller improving the efficiency of the drive system under flow-changing conditions, as well as it has improved the problems that existed in some of the classical efficiency optimization approaches, such as the slowness of the converging, and the oscillation around the optimal point.