Publication

Abstract : Brushless DC motor is used in variety of applications. It is one of the popular motors in the industry and automotive. This motor is often used in an electric vehicle due to its high efficiency and high torque to weight ratio. For any vehicle, speed control is a crucial part as speed cannot remain constant throughout the ride. Electric motor is the major part of propulsion system in an electric vehicle. Various control methods like PWM control, Direct torque Control, Field oriented control are used for speed control of any motor. But these methods suffer from high ripples in torque as well as in current. Model Predictive control is proven to be a great control strategy in various application such as high-end CNC machines, Robotics, Converter control etc. In this paper, Model Predictive Control of Brushless DC Motor is presented with the aim of minimizing torque ripples. Performance analysis of BLDC motor using MPC is tested under Indian Driving Cycle. The results are further compared with Hysteresis Current Controlled BLDC motor. This comparative analysis is done using MATLAB Simulink and tested using dSPACE 1104. Results show that the MPC technique gives significant reduction in torque ripples as well as current ripples with better speed regulation.