Abstract
In this paper, a simple extended Kalman Filter (EKF) controller for direct torque control (DTC) of a six-phase induction machine in all speed ranges is proposed. The aim of this paper is to decrease the execution time of EKF modeling of a six-phase induction motor. The proposed method is fast and can operate online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find parameters used for controlling the motor. In low speed, not only the motor speed measurement but also the DTC of machine is difficult. The EKF model can estimate speed, flux, load torque, and stator resistance in low speed; thus, optimization can be performed in all loads and speed range. The proposed method increases the accuracy of DTC of the six-phase induction machine and decreases the computation cost of the system using the simplified algorithm. The simulation and experimental results verify the effectiveness and the robustness of the proposed method against parameter variations.
Highlights
Six-phase and five-phase machines are two usual types of multiphase machines that are used in several applications [1,2,3,4]
If stator resistance change is not considered in the direct torque control (DTC) method, it causes an error in controller outputs [13,14,15,16]. us, to increase the accuracy of the DTC method, it needs a suitable method to estimate stator resistance [14]
A suitable method to estimate the stator resistance based on the mechanical loss and torque is proposed in the study by Salomon et al [18]. is method is suitable to offline estimate of resistance and in service applications of the induction motor. is paper uses a particle swarm optimization (PSO) algorithm based on flux equations with minimizing the torque error
Summary
Six-phase and five-phase machines are two usual types of multiphase machines that are used in several applications [1,2,3,4]. Extended Kalman filter (EKF) is a powerful estimator to estimate the stator resistance and to load torque and flux of the machine [23,24,25,26,27,28,29]. A simple extended Kalman filter (EKF) loss model controller (LMC) for efficiency improvement of a six-phase induction machine in all speed ranges is proposed [36]. E temperature-dependent variation of the stator and rotor resistances, which induce a large estimation error on speed and flux, has been a critical issue for the speed-sensorless control. To estimate simultaneous variations of the stator and rotor resistances in the speed-sensorless control of IMs under different operating conditions, an estimator is developed based on the extended Kalman filter (EKF) technique. Simulation results of proposed methods are shown, and experimental results validate the correctness of proposed methods in all speed ranges
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
