Sensorless control of a permanent magnet machine/gasoline engine using an extended Kalman filter

Author(s):  
T. O'Gorman
2013 ◽  
Vol 834-836 ◽  
pp. 1240-1245 ◽  
Author(s):  
Wei Min Yang ◽  
Li Jiao Pan ◽  
Peng Fei Zheng ◽  
Yong Qiang He

Control system with position sensor is susceptible to the severe environment such as high temperature, humidity and vibration, which reduce the stability of control system. Position sensorless control of permanent magnet linear synchronous motor need not position sensor so that it can use in abominable environment. According to three phases voltage and two phases current measured from motor, the position and speed of motors mover can be estimated directly based on extended Kalman filter algorithm which is a kind of recursive algorithm. So position sensorless close loop control of PMLSM can be realized.


2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Yong Zhang ◽  
Xu-Feng Cheng

This paper concerns the parameter tuning and the estimated results postprocessing of the extended Kalman filter for the sensorless control application of permanent magnet synchronous motors. At first an extended Kalman filter parameter tuning method is proposed based on the theoretical and simulation analysis of extended Kalman filter parameters. Furthermore, a sensorless control system is proposed based on the parameter tuning method and the simulation analysis of extended Kalman filter estimation results in different reference speeds and different load torques. The proposed sensorless control system consists of two parts. The first one is a module to self-regulate extended Kalman filter parameters. The second part can correct the estimated speed and the estimated rotation angle based on the reference speed and the electromagnetic torque. Finally, simulation results are presented to verify the feasibility and validity of the proposed sensorless control system.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3491
Author(s):  
Justas Dilys ◽  
Voitech Stankevič ◽  
Krzysztof Łuksza

This paper addresses the implementation and optimization of an Extended Kalman Filter (EKF) for the Permanent Magnet Synchronous Motor (PMSM) sensorless control using an ARM Cortex-M3 microcontroller. A various optimization levels based on arithmetic calculation reduction was implemented in ARM Cortex-M3 microcontroller. The execution time of EKF estimator was reduced from 260.4 μs to 37.7 μs without loss of accuracy. To further reduce EKF execution time, the separation of a Kalman gain and covariance matrices calculation from prediction and measurement state update, a novel method was proposed, and the performance of it an EKF estimator with separation of a Kalman gain and covariance matrices calculation from prediction and measurement state update was analyzed. Simulation and experiments results validate that the proposed technique could provide the same accuracy with less computation time. A tendency of minimum Kalman gain and covariance matrices calculation frequency from rotor electrical frequency was analyzed and are presented in the paper.


Sign in / Sign up

Export Citation Format

Share Document