Energy optimisation of sensorless induction motor drives using a novel robust-adaptive flux simulator

Abstract

Modern drive systems should have improved reliability and one solution is the reduction or elimination of the number of speed sensors while maximizing the efficiency of motor and drive systems. The paper presents the development of a novel robust-adaptive-flux simulator which is used for the energy optimisation of sensorless induction motor drives. The closed loop system contains a predictive current controller and an observer which is robust against parameters variation. The estimated values of the rotor magnetic flux are used to determine the motor core losses by the robust-adaptive observer. Particle Swarm Optimisation (PSO) algorithm is used for the optimization of rotor speed so the motor losses are minimized and so the motor efficiency is increased. The simulated results show that the proposed sensorless control strategy ensures that the drive system has high dynamic performance for a wide range of rotor speeds and leads to a significant energy saving under different load operating conditions.

Loss minimization of induction machines during torque transients

“…3 Other methods have used the same strategy but by tracking directly the optimal flux using the particle swarm optimization (PSO) algorithm to track the loss minimization via the rotor flux expression. 8,9…”