Title: Sensorless DTC IM drive for an EV propulsion system using a neural network
Author: Bhim Singh, Pradeep Jain, Alok Prakash Mittal
Department of Electrical Engineering, IIT Delhi, Hauz Khas, New Delhi-110016, India.
Department of Instrumentation and Control Engineering, NSIT, Dwarka, New Delhi-110075, India.
Department of Instrumentation and Control Engineering, NSIT, Dwarka, New Delhi-110075, India
Abstract: This paper deals with a sensorless direct torque control (DTC) of an induction motor (IM) for an electric vehicle (EV) propulsion system using a neural network. The drawback of conventional DTC is the generation of relatively large torque ripple. In the proposed scheme, first the traditional switching lookup table of a three-level torque controller DTC is replaced with a neural network controller. For further reducing the torque ripples, a three-level torque controller is replaced by the five-level torque controller and then the switching lookup table of the five-level torque controller DTC is replaced with a neural network controller. These sensorless DTC schemes of an IM drive are simulated using Matlab/Simulink. The simulated results are compared with conventional DTC and it is found that the ripples in the torque, as well as in stator current, are reduced drastically.
Keywords: sensorless DTC; electric vehicles; induction motors; neural networks; direct torque control; vehicle control; simulation; torque ripples; stator current.
Int. J. of Electric and Hybrid Vehicles, 2008 Vol.1, No.4, pp.403 - 423
Available online: 24 Dec 2008