Pengju Wang

In this paper, a mechanical model of the deflection dual-stator switched reluctance generator (DDSRG) is developed, and the advantages of the dual-stator structure for the deflecting motion are analyzed. Secondly, the spatio-temporal and spatial distribution characteristics of the inhomogeneous electromagnetic force are derived analytically and further verified by fast Fourier transform (FFT).Thirdly, the spatial and temporal distributions of electromagnetic forces of DDSRG are calculated based on finite element software, and the distributions of electromagnetic forces under different motion states are analyzed. By combining the analysis of modal analysis and harmonic response analysis, the free mode and vibration response acceleration variation laws of the internal and external stator are determined. The results show that the order of electromagnetic forces on the stator at rated speed is mainly 8 times the fundamental frequency, and the modal vibration order is more violent in the order of 2–7. Finally, the experimental platform of DDSRG is built, and the vibration characteristics are tested to verify the validity and accuracy of the proposed simulation results.

In allusion to the phenomenon that the extended Kalman filter is easy to diverge in the mover position estimation of permanent magnet synchronous linear motor, a linear motor extended Kalman filter speed estimation method based on attenuation memory is designed. By setting the attenuation factor, α, the extended Kalman filter is introduced to increase the weight of the latest speed data and restrain the divergence of the filter, so as to achieve a better speed tracking effect. In the simulation experiment of the sensorless control of a linear motor, the AMEKF algorithm can significantly improve the speed estimation accuracy of standard EKF, and the speed estimation error is reduced by 0.75%. At the same time, it still maintains a good speed tracking effect and good dynamic performance under variable speed and different load conditions.