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International Conference on Infrared and Millimeter Waves

作者： Shanshan Jia Zesen Zhou Fanqi Meng Zhilong Gan Lei Cao State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China Physikalisches Institut Johann Wolfgang Goethe-Universität Frankfurt am Main Germany

The sensitivity of terahertz refractive index sensors depends critically on the amplitude and spatial distribution of electric field where the analyte locates. A sensitive THz sensor was proposed based on metamaterials composed of two asymmetrically arranged C-shaped metallic structures. The resonance frequency is 758.6 GHz and the refractive index sensitivity is 128.2 GHz/RIU when the analyte thickness is 2 $\mu$m. Simulation results demonstrate that the proposed sensor is more sensitive than the traditional aDSRR structure. It serves as a new optimization method for the design of high-sensitivity metallic metamaterials, and has potential applications in trace materials detection and biosensing.

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Magnetostatic Field Assisted Tunability and Polarization Conversion in Patterned Graphene Terahertz Metamaterials

Magnetostatic Field Assisted Tunability and Polarization Con...

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International Conference on Infrared and Millimeter Waves

作者： Zesen Zhou Zhilong Gan Fanqi Meng Lei Cao State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China Physikalisches Institut Johann Wolfgang Goethe-Universität Frankfurt am Main Germany

Graphene metamaterials are ideal platforms for dynamically controlling THz waves due to their unique tunability and reconfigurability. However, most research focused on the electrostatic field based tuning method. Here, we numerically explored the distinct effect of external magnetostatic field on the transmission properties of patterned graphene metamaterials (SRR, H-shaped and eSRR-shaped resonators). Results show that magnetic tuning can serve as an effective method to modulate the properties of resonances. Additionally, polarization conversion and Faraday rotation in graphene metamaterials induced by magnetic field is analyzed. Our results will provide a new routine for the realization of tunable and functional graphene-based THz devices.

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Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1752-1762页

作者： Xianglei Zhu Wen Hu Zejian Deng Jinwei Zhang Fengqing Hu Rui Zhou Keqiu Li Fei-Yue Wang the College of Intelligence and Computing Tianjin UniversityTianjin 300350 the China Automotive Technology and Research Center Co.Ltd. Tianjin 300300China the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L3G1Canada the School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China the Macao University of Science and Technology MacaoChina the Waytous Inc. Qingdao 266000China IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by *** improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic *** integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and *** dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference *** on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax ***,the comparative analysis is performed to validate the proposed method using the naturalistic driving *** results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

关键词： Cut-in behavior interaction-aware mixed traffic risk assessment trajectory prediction

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A differential protection scheme with inverter power based on pearson similarity

A differential protection scheme with inverter power based o...

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Tsinghua University-IET Electrical engineering Academic Forum: Constructing Green and Sustainable Energy System 2021

作者： Yao, Hao Xiong, Yuwei Xi, Wei Chen, Wei Electric Power Research Institute of China Southern Power Grid Guangzhou China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China Electric Power Research Institute of China Southern Power Grid Guangzhou China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China

ISBN: (纸本)9781839536199

The connection of inverter-type power supply to the distribution network makes the fault characteristics of the system when a short circuit occurs quite different from that of the traditional distribution network. Traditional current protection is no longer suitable for the distribution network with inverter-type power supply. Therefore, this article firstly analyses the output characteristics of the inverter-type power supply when the power grid fails, and analyses the difference in the positive sequence current waveforms at both ends of the line when a single-phase ground fault occurs in the grid-connected system with the inverter-type power supply from the perspective of phase. This paper uses waveforms to propose a differential protection principle based on Pearson similarity. The simulation results show that the protection principle can reliably identify internal and external faults, has the ability to withstand strong transition resistance, and can still be accurate in isolated network operation Identify the fault. Compared with cosine similarity, the protection criterion based on Pearson similarity has a stronger ability to distinguish time series differences, and this protection scheme has stronger engineering application value. © 2021 Institution of engineering and technology. All rights reserved.

关键词： Electric grounding

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Green and Facile Synthesis of Carbon Encapsulated Fe3n Nanospheres Grown on N-Doped Porous Carbon Nanosheet as an Excellent Anode Material

SSRN

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SSRN 2023年

作者： Zhang, Dan Zhang, Chunyan Shi, Xinyu Xu, Huishi Shi, Shukui Li, Yuzhu Luo, Baomin Liu, Guangyin Liu, Xiaodi Yu, Chuang Li, Xin College of Chemistry and Pharmaceutical Engineering Nanyang Normal University Nanyang473061 China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

The development of iron nitride anode materials is greatly impeded by their traditional synthesis methods. In this work, carbon encapsulated Fe3N nanospheres grown on N-doped porous carbon nanosheet is successfully prepared by a green, facile and controllable approach. Only a small nitrogen source is needed in the synthesis process by in-situ nitrogenization. The Fe3N nanospheres are coated by carbon and uniformly adhered to N-doped porous carbon nanosheet, which prominently mitigates the variation of volume and elevates the electrochemical reaction kinetics. The feature is conducive to realizing long life and brilliant rate performance. As an anode for lithium-ion batteries, a high discharge capacity of 484 mA h g-1 is delivered after 600 cycles at 2 A g-1. Extensive impact is brought by this study for the preparation and application of metal nitride materials. © 2023, The Authors. All rights reserved.

关键词： Anodes

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Model Predictive Thrust Control for Linear Induction Machine: A Fuzzy Optimization Approach

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IEEE Transactions on Industry Applications 2022年第2期59卷 1-14页

作者： Tang L. Xu W. Tang Y. Ge J. Yang K. Islam M.R. Li W. Su S. School of Management School of Electrical Engineering Xi&#x0027 State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan Hubei China School of Electrical Computer and Telecommunications Engineering University of Wollongong NSW Australia Xiangyang CRRC Motor Technology Co. Ltd. Xiangyang China CRRC Zhuzhou Motor Co. Ltd. Zhuzhou China

Model predictive thrust control (MPTC) is one of the most effective approaches for linear induction machine (LIM) drive system. It can achieve the optimization of multiple objectives with suitable weighting factors, such as low ripples and fast dynamic performance. Due to the longitudinal end effect, the selection of weighting factor becomes particularly important in LIM. However, the process of tuning the weighting factors in the objective function is very long and tedious. In this paper, a dynamic fuzzy MPTC approach is proposed to solve the multi-objective problem for minimizing the flux and thrust ripples. Based on the fuzzy optimization technique, the tuning process of weighting factors can be transformed into a discrete membership function. A 1C;max-min 1D; objective function of voltage vectors is employed to select a more balanced switch combination on the Pareto optimal-frontier for LIM. Furthermore, this approach can adapt to different operating conditions by adjusting objective priority of membership function. At last, comprehensive simulation and experimental results are conducted to demonstrate the effectiveness and feasibility of the proposed method. IEEE

关键词： fuzzy optimization Linear induction machine (LIM) model predictive thrust control (MPTC) optimization methods weighting factors

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Calculation and analysis of electromagnetic vibration of transverse flux linear oscillation motor with moving stator 13

Calculation and analysis of electromagnetic vibration of tra...

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13th International Symposium on Linear Drives for Industry Applications, LDIA 2021

作者： Yue, Feihong Sun, Zhaolong Xu, Wei Li, Xiang School of Electrical Engineering Naval University of Engineering Wuhan430032 China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781728172101

The transverse flux linear oscillation motor with moving stator is taken as the research object, and the vibration characteristics of the motor are analyzed and calculated. Firstly, the influence of rotor eccentricity on the magnetic field distribution in the air gap is analyzed and calculated. Moreover, by establishing the equivalent vibration model of the motor stator, the modal shapes of the motor stator and the mover are calculated respectively. In addition, the response spectrum of the eccentric mover is analyzed through the coupling calculation of electromagnetic field and mechanical field. Finally, the modal combination principle is used to calculate the resonant frequency range when the rotor axis deviates from the stator axis. This study laid a foundation for the subsequent optimization design. © 2021 IEEE

关键词： Modal analysis

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Detection and Imputation based Two-Stage Denoising Diffusion Power System Measurement Recovery under Cyber-Physical Uncertainties

arXiv

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arXiv 2023年

作者： Pei, Jianhua Wang, Jingyu Shi, Dongyuan Wang, Ping State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China Department of Electrical Engineering and Computer Science Lassonde School of Engineering York University Toronto Canada

Power system cyber-physical uncertainties, including measurement ambiguities stemming from cyber attacks and data losses, along with system uncertainties introduced by massive renewables and complex dynamics, reduce the likelihood of enhancing the quality of measurements. Fortunately, denoising diffusion models exhibit powerful learning and generation abilities for the complex underlying physics of the real world. To this end, this paper proposes an improved detection and imputation based two-stage denoising diffusion model (TSDM) to identify and reconstruct the measurements with various cyber-physical uncertainties. The first stage of the model comprises a classifier-guided conditional anomaly detection component, while the second stage involves diffusion-based measurement imputation component. Moreover, the proposed TSDM adopts optimal variance to accelerate the diffusion generation process with subsequence sampling. Extensive numerical case studies demonstrate that the proposed TSDM can accurately recover power system measurements despite renewables-induced strong randomness and highly nonlinear dynamics. Additionally, the proposed TSDM has stronger robustness compared to existing reconstruction networks and exhibits lower computational complexity than general denoising diffusion models. Copyright © 2023, The Authors. All rights reserved.

关键词： Electric power system measurement

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An Approach to Identify VLF/LF Cloud-to-ground Return Stroke Electric Field Waveform Based on Convolutional Neural Network

An Approach to Identify VLF/LF Cloud-to-ground Return Stroke...

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2022 IEEE International Conference on High Voltage engineering and Applications, ICHVE 2022

作者： Xiao, Lilang Chen, Weijiang Wang, Yu Fu, Zhong Cheng, Yang Chen, Shen Bian, Kai He, Hengxin Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China Wuhan Nari Limited Liability Company State Grid Electric Power Research Institute Wuhan430074 China State Grid Corporation of China Beijing China State Grid Electric Power Research Institute State Grid Corporation Anhui Hefei China

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407502

The identification of lightning return stroke waveform plays an important role in the accurate location of lightning. Very low frequency/low frequency (VLF/LF) electromagnetic signals are widely used in lightning detection systems. The signals in this frequency band have a long propagation distance and are prone to attenuation distortion, which makes it more possible to misclassify the return stroke waveforms when using methods based on some specific waveform characteristic. The convolutional neural network is robust enough and performs well at discovering hidden patterns in images. In this paper, the residual convolutional neural network model is trained to obtain the waveform classifier. The lightning waveform data dataset is collected by lightning electric field measuring meters deployed in various provinces. After training, the classification accuracy of this classifier reaches 97.2% in the test set, and the accuracy reaches 86.75% using the traditional method based on waveform characteristics. The result proves the superior performance of the residual convolutional neural network model. By exploring the interpretability of the model, it is also proved that the better performance of the convolution network model comes from making full use of waveform information. © 2022 IEEE.

关键词： Neural network models

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Design of Consequent Pole Permanent Magnet Vernier Motor for Downhole Electric Drilling System 4

Design of Consequent Pole Permanent Magnet Vernier Motor for...

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4th IEEE Student Conference on Electric Machines and Systems, SCEMS 2021

作者： Chen, Zheng Wang, Jin Hu, Zhijian Xiao, Jianqiu Zhou, Libing Wang, Hu Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan China Cnpc Engineering Technology Rd Company Limited Drilling Mechanical Department Beijing China

ISBN: (纸本)9781665436816

The downhole electric drilling tool can realize the high-efficiency and low-cost development of oil and gas resources in deep wells. As its core component, the downhole motor needs to have high torque density and high reliability. Permanent magnet vernier motor (PMVM) has simple structure and high torque density, but the traditional surface mounted permanent magnet vernier motor (SPMVM) has low power factor and poor reliability of structure. This paper proposes a consequent pole permanent magnet vernier motor (CPMVM) as the motor of downhole electric drilling system. The results show that the proposed CPMVM can improve the power factor and structural reliability. © 2021 IEEE.

关键词： Permanent magnets

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