Intelligent Flux Predictive Control Through Online Stator Inter-Turn Fault Detection for Fault-Tolerant Control of Induction Motor

Inter-turn insulation failure in induction motor results in complete or developing winding short circuit. Stator winding fault leads to an unbalance in the three phases of the motor leading to a faulty induction motor with increased time and space harmonics of flux. This can lead to uneven distribution of air gap flux and increase in torque ripple. The condition is worsened due to an unbalance in the voltage supply depreciating the optimal performance of the drive-based It is of primary importance that the aforementioned discrepancies are taken care of while modelling a more fault tolerant motor drive system with faster processing and lower response time. This paper proposes a novel control technique to reduce the unbalance in the motor due to stator fault by taking into account the air-gap flux developed in the motor and harmonics generated. An improved swarm optimization algorithm has been used in order to efficiently predict the flux reference for the stator-flux controlled motor drive. The proposed detection scheme has been implemented on an aluminum-rotor induction motor with incipient stator interfault with the help of online monitoring of unhealthy conditions and using it as a feedback for the drive system, thereby a robust online detection of fault and a stable fault control system.