Performance Analysis of BLDC Motor Drive using Enhanced Neural Based Speed Controller for Electric Vehicle Applications

Abstract

This paper deals with Brushless DC (BLDC) motor drive mathematical model with hysteresis current controlled based Voltage Source Inverter (VSI) which operates using Neural Network (NN). The developed simulation model is applied with the artificial neuro speed controller which is based on Least Mean Square (LMS) and Adaptive Linear Neuron (ADALINE) to improve the performance of BLDC motor drive. Under dynamic operating conditions, the NN speed controller is trained by the data obtained from closed loop speed controller of BLDC motor drive system. The developed conventional and proposed simulation models are simulated using MATLAB/Simulation software. The proposed neural based speed controller is important for tracking of motor speed as well as torque with their reference values with minimum transient time. In this paper ADALINE network model is developed for update of weights in NN. Here, a comparative study has been done for PI and NN controller for BLDC drive. The simulation results show that the NN based speed controller is more effective controller compared to classical PI based speed controller during most of the dynamic operating conditions.