This paper presents a modeling of the Brushless DC motor based on the system identification method. The input and output data were collected and simulated based on the real-time experiment. Taking a continues time form for the system model, a transfer function was selected in this work. The potentiometer has been used to send Pulse Width Modulation (PWM) signals as input signal to the Brushless DC motor to determine the open-loop model of brushless DC motor (BLDC). LM2907 Tachometer attached with Brushless DC motor driver to measure the output speed. The input signal and measured output data were interfaced to plant by C code generation Matlab/Simulink through Arduino Mega controller. System identification toolbox was used for collecting data to obtain the estimates model. The best fit found for the system was 90.2%. The PID controller was developed to control the desired speed based on the given speed to demonstrate the feasibility of the given method.
Modeling and Speed Control for Sensorless DC Motor BLDC Based on Real Time Experiement
2019-12-04
International Journal of Integrated Engineering; Vol 11 No 8 (2019); 55-64 ; 2600-7916 ; 2229-838X
Article (Journal)
Electronic Resource
English
DDC: | 629 |
Sensorless-BLDC motor speed control with ensemble Kalman filter and neural network
BASE | 2019
|BLDC eVTOL The eVTOL aircraft using sensorless BLDC motor and control method thereof
European Patent Office | 2023
|BLDC eVTOL The eVTOL aircraft using sensorless BLDC motor and control method thereof
European Patent Office | 2023
Bi-directional Position and Speed Estimation Algorithm for Sensorless Control of BLDC Motor
BASE | 2019
|