ARTICLE
Volume 10,Issue 7
6 June 2025
Research on Low-Speed Performance Optimization of BLDC without Position Sensors Based on EKF
Wei Liu ,
Yakun Wang
Show Less
1
School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin 132022, Jilin, China,
JERA 2025 , 9(3), 332–341;
https://doi.org/10.26689/jera.v9i3.10814
© 2025 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract
To obtain real-time rotor information of the brushless DC motor, improve the low-speed performance and anti-interference ability of the motor, a sensorless vector control system model of the brushless DC motor was established. A motor control system based on the EKF algorithm was designed. By combining the EKF observer with the brushless DC motor, a simulation model of the EKF motor control system was built based on Simulink. The simulation results show that the motor control system with the EKF observer operates well. The motor’s low-speed operation performance and rotor position detection are very fast, and the motor’s anti-interference ability is significantly enhanced, effectively improving the dynamic performance of the control system [1].
References
Yu B, 2021, Research on Sensorless Control Technology for Brushless DC Motors at Full Speed Range, dissertation, Harbin Institute of Technology.
Inan R, 2024, An Improved Model Predictive Current Control of BLDC Motor with a Novel Adaptive Extended Kalman Filter–Based Back EMF Estimator and a New Commutation Duration Approach for Electrical Vehicle. International Journal of Circuit Theory and Applications, 53(2): 1135–1150.
Li D, 2021, Low-speed Performance Improvement of Induction Motor Without Speed Sensor based on EKF Vector Control, dissertation, Xi’an University of Technology.
Zheng X, 2021, Research on Sensorless Control Algorithm for BLDC based on Improved Kalman Filtering, dissertation, Harbin Institute of Technology.
Hooshmand M, Yaghobi H, Jazaeri M, 2023, Speed and Rotor Position Estimation for Sensorless Brushless DC Motor Drive based on Particle Filter. Electrical Engineering, 105(3): 1797–1810.
Matyuschenko A, 2015, Mathematical Field Models of Brushless DC Motors with Permanent Magnets and Their Comparative Analysis. Electrical Engineering & Electromechanics, (1): 25–28.
Yingjun S, Zhenglong W, Yuanyuan F, 2025, An Adaptive Extended Kalman Filter Observer for Permanent Magnet Synchronous Motor Position Sensorless Control Systems. Scientific Reports, 15(1): 11605.
Meysam H, Hamid Y, Mostafa J, 2023, Speed and Rotor Position Estimation for Sensorless Brushless DC Motor Drive based on Particle Filter. Electrical Engineering, 105(3): 1797–1810.
Shao J, 2025, Dual-vector model predictive current control for brushless DC motors. Journal of Physics: Conference Series, 2963(1): 012020.
Wang J, 2023, Research on Key technologies for Drive Control of Integrated Brushless DC motors, dissertation, University of Electronic Science and Technology of Xi’an.
Shin Y, Kim K, Cho Y, et al., 2025, Rotor Position Estimation Error Compensation Using Back-EMF Based Sensorless Control for Low-Speed Operation in Washing Machines. Journal of Electrical Engineering & Technology, 20(4): 2497–2507.
Yan X, 2020, Design and Implementation of FOC Control System for Sensorless BLDCM, dissertation, University of Electronic Science and Technology of China.
Share
Back to top
Bio-Byword Scientific Publishing Pty. Ltd.
We are committed to supporting the scientific community by publishing impactful research and fostering effective communication among scientists. We continuously seek ways to accelerate scientific progress while upholding transparency and open dialogue. Our goal is to make knowledge freely and barrier‑free accessible to all.
Contact us: info@bbwpublisher.com
Level 10, 50 Clarence Street Sydney, NSW 2000 Australia