Performance Analysis of Different Controllers of BLDC Motor Suitable for EV

Research on enhancing the performance of a brushless DC Motor (BLDC) in an Electric Vehicle (EV) is one of the interesting areas in the automobile sector. Integration of BLDC motor with power converters and intelligent controllers implementation in EV optimizes its efficiency and performance. In this paper, an inverter-based brushless DC motor is designed and a closed-loop control system is developed with different controllers to control the speed and torque characteristics of the motor. Proportional Integral Derivative (PID) controller. Fuzzy Logic Controller (FLC) and Artificial Neural Network (ANN) controller are used in this work. The VSI operation is carried out with the help of all the controllers separately along with the switching logic circuit. The objective of the controllers is to regulate the speed of the rotor so that it can reach the level of reference speed. Reference speed and actual speed error are fed to the controller, based on the type of controller, input variables are chosen so that optimal control can be obtained for the VSI. Finally, a comparative analysis is presented to justify the suitable controller of the motor that can be fitted to an EV to improve its performance in this aspect. The above work model is designed and simulated with the help of the MATLAB/Sımulınk platform.