Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter

Abstract

This paper proposes a simple extended Kalman filter (EKF) loss model controller (LMC) for efficiency improvement of a six-phase induction machine in all speed ranges. The proposed method is fast and can be operated online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find the parameters to ensure optimal efficiency operation. Not only is the motor speed measurement difficult at low speeds but it is also difficult to calculate the machine efficiency at the same speeds. Thus, the EKF model can estimate speed, load, and motor efficiency at low speed ranges so that optimization can be done in all loads and speed ranges. Unlike the conventional LMC method, the proposed method is independent of parameter variations. Because of the independency of this method against the parameter variations, it works similarly to the search based efficiency control methods. Two DSP boards including estimator and controller are used to achieve high accuracy and speed in estimating and controlling machines. The simulation and experimental results verify the robustness of the sensorless method against parameter variations.