Performance analysis and enhancement of brain emotion-based intelligent controller and its impact on PMBLDC motor drive for electric vehicle applications

Abstract

Growing awareness of electric vehicles insists on the necessity of Permanent Magnet Brushless Direct Current Motor (PMBLDCM) worldwide. This paper involves building a simulation model of the complete PMBLDCM drive system using Matlab/Simulink to control the speed and Torque. Using the Simulink model, speed parameters with various controllers of the drive system are studied and analyzed. The conventional PI controller is capable of controlling the speed of the PMBLDC motor. H1owever, it cannot give assurance of the stability of the motor throughout the load variation. In a speed loop, Improved Brain Emotional Learning Based Intelligent Controller (IBELBIC) is proposed in this paper. The proposed IBELBIC-based PMBLDC motor drive system with a rating of 3 phase, 30 V, 400 W, 3000 RPM is implemented using Spartan 3 Field Programmable Gate Array (FPGA) from Xilinx. This paper presents an IBELBIC design for enhancing the speed performance of the drive system at various set speeds and different load conditions of 1.2 Nm load, 0.6 Nm load, and no load. The proposed PMBLDCM drive system is realized with the help of a Very high speed integrated circuit Hardware Description Language (VHDL) programming algorithm of digital Pulse Width Modulation (PWM) generator topology. Various test cases are evaluated under different operating conditions to demonstrate the learning capability and the applicability of the proposed controller. In this paper, simulation validation is done using hardware setup, and experimental results are monitored on a computer using a customized program developed using LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench). Instead of a Data Acquisition (DAQ) card, the Virtual Instrument Software Architecture (VISA) tool of LabVIEW software is used in this work and results in cost minimization of the experimental setup.