Xiaopeng Wei
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Xiaopeng Wei has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Libo Liu
School of Electrical Engineering, Hebei University of Science and Technology, 26 Yuxiang Street, Shijiazhuang 050018, China
2 shared publications - Zheng Li
School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang, China
2 shared publications - Hexu Sun
School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
1 shared publication - Hexu Sun
School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang, China
1 shared publication - Jinsong Wang
School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
1 shared publication - Pengju Wang
School of Electrical Engineering, Hebei University of Science and Technology, 26 Yuxiang Street, Shijiazhuang, 050018, China
1 shared publication
Latest Publications
- Open Access
- 8 September 2022
- Published by MDPI AG in Micromachines
- Vol. 13 (9) , 1494
Modeling and Analysis of Radial Electromagnetic Force and Vibration Characteristics Based on Deflection Dual-Stator Switched Reluctance Generator
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.
- 8 September 2022
- Published by MDPI AG in Micromachines
- Vol. 13 (9) , 1494
Open AccessModeling and Analysis of Radial Electromagnetic Force and Vibration Characteristics Based on Deflection Dual-Stator Switched Reluctance Generator
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.
- Open Access
Design of a Deflection Switched Reluctance Motor Control System Based on a Flexible Neural Network
Deflection switched reluctance motors (DSRM) are prone to chattering at low speeds, which always affects the output efficiency of the DSRM and the mechanical loss of the motor. Combining the characteristics of a traditional reluctance motor with the strong nonlinear and high coupling of the DSRM, a control system for a DSRM based on a flexible neural network (FNN) is proposed in this paper. Based on the better robustness and fault tolerance of fuzzy PI control, the given speed signal is adjusted and converted into a torque control signal. As a result, the FNN control module possesses the strong self-learning ability and adaptive adjustment ability necessary to obtain the control voltage signal. Through simulations and experiments, it was verified that the control system can run stably on DSRM and shows good dynamic performance and anti-interference ability.
Open AccessDesign of a Deflection Switched Reluctance Motor Control System Based on a Flexible Neural Network
Deflection switched reluctance motors (DSRM) are prone to chattering at low speeds, which always affects the output efficiency of the DSRM and the mechanical loss of the motor. Combining the characteristics of a traditional reluctance motor with the strong nonlinear and high coupling of the DSRM, a control system for a DSRM based on a flexible neural network (FNN) is proposed in this paper. Based on the better robustness and fault tolerance of fuzzy PI control, the given speed signal is adjusted and converted into a torque control signal. As a result, the FNN control module possesses the strong self-learning ability and adaptive adjustment ability necessary to obtain the control voltage signal. Through simulations and experiments, it was verified that the control system can run stably on DSRM and shows good dynamic performance and anti-interference ability.