Pengju Wang

Mr. Pengju Wang

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 November 2022 in Heliyon
Verified
Journal Article
Open access
ZLZheng LI
Zheng LI
PWPengju Wang
Pengju Wang
LLLibo Liu
Libo Liu
QXQianqian Xu
Qianqian Xu
SCShuai Che
Shuai Che
HSHexu Sun
Hexu Sun
The ultra-high speed permanent magnet motor (UHSPM) for hydrogen fuel cell air compressor is characterized by high speed, high motor power density, small size, and high reliability. Compared to the conventional motor, the loss per unit volume is increased and therefore the calculation of the temperature field is more important than that of conventional motors. In this paper, a UHSPM with a rated speed of 90000 r/min is designed. Firstly, a finite element (FE) model of the UHSPM is established and the losses of each part of the high-speed motor are calculated, and the calculated losses are introduced into the fluid field in the form of a heat source for motor temperature analysis. The calculated losses were introduced into the fluid field in the form of a heat source and used in the motor temperature analysis. The temperature rise was then calculated for the unidirectional and bidirectional magneto-thermal coupling (MTC) respectively. The results show that the bidirectional magneto- thermal coupling (BMTC) simulation results are about 2-3 °C smaller than the experimental measured values, which can more accurately predict the motor temperature. The measurement results verify the accuracy of BMTC, and provide basic theoretical support for the subsequent cooling optimization scheme of high-speed motor.

23 January 2023 in Energy Reports
Verified
Journal Article
Open access
ZLZheng LI
Zheng LI
SCShuai Che
Shuai Che
HZHui Zhao
Hui Zhao
LZLucheng Zhang
Lucheng Zhang
PWPengju Wang
Pengju Wang
HSHexu Sun
Hexu Sun

8 September 2022 in Micromachines
Verified
Journal Article
Open access
PDF file
ZLZheng LI
Zheng LI
LLLi bo Liu
Li bo Liu
PWPengju Wang
Pengju Wang
YLYu Liu
Yu Liu
XWxiaopeng wei
xiaopeng wei
HSHexu Sun
Hexu Sun
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.

12 May 2022 in Electronics
Verified
Journal Article
Open access
PDF file
ZLZheng LI
Zheng LI
LZLucheng Zhang
Lucheng Zhang
WNWang jinsong Wang ning
Wang jinsong Wang ning
WSWeisong Sun
Weisong Sun
PWPengju Wang
Pengju Wang
HSHexu Sun
Hexu Sun
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.