Torque Quality Improvement in Induction Motor for Electric Vehicle Application Based on Teamwork Optimization

Abstract

The tailpipe emission caused by the vehi- cles using internal combustion engines is a significant source of air pollution. To reduce the health hazards caused by air pollution, advanced countries are now adopting the use of Electric Vehicles (EVs). Due to the advancement of electric vehicles, research and devel- opment efforts are being made to improve the perfor- mance of EV motors. With a nominal reference sta- tor flux, the classical induction motor drive generates significant flux, torque ripple, and current harmon- ics. In this work, a Teamwork Optimization Algorithm (TOA)-based optimal stator flux strategy is suggested for torque ripple reduction applied in a Classical Direct Torque Controlled Induction Motor (CDTC-IM) drive. The suggested algorithm’s responsiveness is investi- gated under various steady-state and dynamic operat- ing conditions. The proposed Direct Torque Controlled Induction Motor (DTC-IM) drive’s simulation results are compared to those of the CDTC-IM and Fuzzy Di- rect Torque Controlled Induction Motor (FDTC-IM) drives. The proposed system has been evaluated and shown to have reduced torque ripple, flux ripple, cur- rent harmonics, and total energy consumption by the motor. Further, a comparative simulation study of the above methods at different standard drive cycles is presented. Experimental verification of the proposed algorithm using OPAL-RT is presented. The results represent the superiority of the proposed algorithm compared to the CDTC- and FDTC-IM drive. The torque ripple reduction approach described in this study can also be applied to all types of induction motors, not only those for electric vehicles or Hybrid Electric Vehicles (HEVs).