ANN Based High Performance Induction Motor Drive for EV

This paper presents an improved direct torque control (DTC) algorithm using an artificial neural network (ANN) for open-end winding induction motor (OEWIM) drives. A look-up table (LUT) selects the voltage vectors in conventional direct torque control (CDTC). The dwell time of these vectors depends on the hysteresis bands. The ANN gives the flexibility of dividing this band into smaller levels. In this paper, ANN is used to improve the performance of DTC. An attempt is made to apply ANN-based DTC to an electric vehicle (EV) powertrain with an OEWIM configuration. The performance of the powertrain is validated through simulations and a laboratory experimental setup, and comparative results are presented.