State Estimation for Cascaded Hybrid Multi-level Inverter Fed Induction Motor Drive Using Derivative-free Extended Kalman Filter

Induction machines are extensively used electrical machines in industrial applications. Now-a-days, energy efficient high power rated electrical drives are attracted by industries. Multi-level inverter fed induction motor drives provide a good solution for energy efficient drives. In multilevel inverters due complexity of switching patterns, there is more chance of fault occurring situations. For incipient fault detection, model based methods are gaining importance now-a days. In this paper, state estimation for cascaded hybrid Multilevel inverter fed induction motor using derivative-free extended Kalman filter is presented. With ready available current sensors, the proposed method is very effective for estimating dynamic behaviour of the induction motor drive. Additionally, the technique is very effective for accurate fault detection. Extensive simulation studies are performed on 3.7 kW induction motor using Matlab/Simulink 2016a environment. The presented results validates that proposed methodology can be used in realistic applications.