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Reconstruction Method of Stator Magnetomotive Force of High-Speed Fault-Tolerant Permanent Magnet Synchronous Motor with Single Winding Independent Control Structure 27

Reconstruction Method of Stator Magnetomotive Force of High-...

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27th International Conference on electrical Machines and systems, ICEMS 2024

作者： Gao, Zhibai Cao, Jiwei Zhong, Chengbao Liu, Jiaxi Song, Yuchen Li, Liyi Harbin Institute of Technology Department of Electrical Engineering Harbin China Guangdong Provincial Key Laboratory of High-Performance Servo System Zhuhai China

ISBN: (纸本)9784886864406

Aiming at the reliability problem of permanent magnet synchronous motor system, a reconstruction method of stator magnetomotive force based on independent winding control structure is established in this paper. For the problem of stator magnetomotive force reconstruction after fault, the mathematical derivation based on current is carried out in this paper, and the current control target of reconstructing stator magnetomotive is obtained. Through this method, the current of each phase of the motor with independent winding control structure can be quickly obtained by formula, and the motor system can run at the same power, torque and speed before and after the fault. Finally, the prototype model based on this method is established by finite element simulation, which proves the effectiveness of this method. © 2024 The Institute of electrical Engineers of Japan.

关键词： Permanent magnets

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Abnormal Data Identification and Reconstruction Based on Wind Speed Characteristics

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CSEE Journal of Power and Energy systems 2025年第2期11卷 612-622页

作者： Mao Yang Tian Peng Wei Zhang Xin Su Chao Han Fulin Fan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin 132012China Department of Electronic and Electrical Engineering University of StrathclYdeGlasgow G11XWUnited Kingdom

High availability of wind power data is the basis for wind power research, but there are a large number of abnormal data in actual collected data, which seriously affects analysis of wind power law and reduces prediction accuracy. Measured power data of wind farm are analyzed, influence of wind speed fluctuation characteristics on wind power is discussed, and abnormal points are identified for data of different wind types. The Cluster-Based Local Outlier Factor (CLOF) algorithm based on K-means is used to identify outlier abnormal points, and conditional constraints based on physical background are used to identify accumulation abnormal points. Reconstructed data segment is divided according to fluctuation of wind speed. The Bidirectional Gate Recurrent Unit (BiGRU) model with wind speed as input reconstructs fluctuation segment data, and bi-directional weighted random forest model reconstructs stationary segment data. Based on analysis of measured data of a wind farm, results show the method can effectively identify various abnormal data, and complete high-quality reconstruction of data, thereby improving accuracy of wind power prediction.

关键词： Abnormal data bidirectional weighted random forest BiGRU CLOF reconstruction wind power prediction wind speed characteristics

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User-Centric Multi-Objective Predictive Control for Mixed Vehicular Platoon

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Wu, Yanhong Han, Qiaoni Zuo, Zhiqiang Wang, Yijing Li, Ji Zhou, Quan Xu, Hongming Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Tianjin China Department of Mechanical Engineering University of Birmingham Birmingham U.K School of Automotive Studies Tongji University Shanghai China

The penetration rate of automated vehicles (AVs) will remain unsaturated for a long period, leading to the coexistence of AVs and human-driven vehicles (HDVs), namely, mixed vehicular platoon (MVP). This paper proposes a novel user-centric multi-objective predictive control (UMPC) strategy to address dynamics uncertainty and multi-objective conflict for MVP. A data-driven model is established with subspace identification to alleviate the adverse effects of the non-ideal driving behavior and complex powertrain structure of electric vehicles. To provide a personalized driving experience, soft constraints and a user-centric multi-objective cost function are formulated. Based on this, a multi-objective optimization scheme in terms of data-driven model predictive sequence is designed. It aims to mitigate conflicts among multiple optimization objectives involving driving safety, driving comfort and energy economy. Then, a grey wolf optimizer (GWO) is devised to navigate the search process, striving for globally optimal trade-offs among conflicting objectives. With the above preparations, a UMPC strategy is suggested. Then, a hardware-in-the-loop experiment platform with CarMaker software and driving simulator is constructed, and twenty drivers participate in the experiment. The experimental results demonstrate the effectiveness of the proposed UMPC strategy. IEEE

关键词： Model predictive control

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Multi-granularity feature enhancement network for maritime ship detection

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CAAI Transactions on Intelligence technology 2024年第3期9卷 649-664页

作者： Li Ying Duoqian Miao Zhifei Zhang Hongyun Zhang Witold Pedrycz Department of Computer Science and Technology Tongji UniversityShanghaiChina Project Management Office of China National Scientific Seafloor Observatory Tongji UniversityShanghaiChina Department of Electrical and Computer Engineering AlbertaEdmontonCanada System Research Institute Polish Academy of SciencesWarsawPoland

Due to the characteristics of high resolution and rich texture information,visible light images are widely used for maritime ship ***,these images are suscep-tible to sea fog and ships of different sizes,which can result in missed detections and false alarms,ultimately resulting in lower detection *** address these issues,a novel multi-granularity feature enhancement network,MFENet,which includes a three-way dehazing module(3WDM)and a multi-granularity feature enhancement module(MFEM)is *** 3WDM eliminates sea fog interference by using an image clarity automatic classification algorithm based on three-way decisions and FFA-Net to obtain clear image ***,the MFEM improves the accuracy of detecting ships of different sizes by utilising an improved super-resolution reconstruction con-volutional neural network to enhance the resolution and semantic representation capa-bility of the feature maps from *** results demonstrate that MFENet surpasses the other 15 competing models in terms of the mean Average Pre-cision metric on two benchmark datasets,achieving 96.28%on the McShips dataset and 97.71%on the SeaShips dataset.

关键词： object classification object recognition rough sets rough set theory

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Characterization of Embedded and Thinned RF Chips 24

Characterization of Embedded and Thinned RF Chips

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24th European Microelectronics and Packaging Conference, EMPC 2023

作者： Yin, Ran Morath, Helmuth P. E. Hoyer, Christian Nieweglowski, Krzysztof Meier, Karsten Wagner, Jens Ellinger, Frank Bock, Karlheinz Institute of Electronic Packaging Technology Technische Universität Dresden Germany Chair of Circuit Design and Network Theory Dresden Germany Technische Universität Chair of Circuit Design and Network Theory Department of Electrical and Computer Engineering Dresden Germany Institute of Electronic Packaging Technology Department of Electrical and Computer Engineering Technische Universität Dresden Germany

ISBN: (纸本)9780956808691

This work studies the effect of thinning down chips with transmission line structures for flexible embedding technology. Test chips with 90 Ω grounded coplanar waveguide (G-CPW) transmission lines have been designed and manufactured to characterize the high-frequency performance before and after embedding in sheet molding compound (SMC), and thinning down from 300 μm to 20 μm, Molding first technology enables single-die or multiple-die thinning with the embedding material while being held in the exact position, where the subsequent fan-out copper (Cu) redistribution layer (RDL) structuring realizes the direct contacts to the embedded chip, followed by semi-Additive manufacturing of traces. The embedded and thinned chips are characterized by S-parameter measurements in the frequency range from 20 MHz to 65 GHz using a vector network analyzer (VNA). The results show the feasibility of the examined embedding and thinning processes which are suitable for millimeter wave (mmWave) components as shown by the example of a G-CPW transmission line without degrading its RF performance in terms of characteristic impedance and attenuation. © 2023 IMAPS-Europe.

关键词： Millimeter waves

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A Dual-Core Dual-Mode Class-F VCO With Wide Frequency Tuning Range Using Wide Inductance-Switching-Range Inductor

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IEEE Microwave and Wireless technology Letters 2025年第4期35卷 460-463页

作者： Hou, Yaru Li, Runlong Chi, Pei-Ling Yang, Tao University of electronic Science and Technology of China Chengdu610036 China Sichuan Province Engineering Research Center for Broadband Microwave Circuit High Density Integration Chengdu610036 China University of Electronic Science and Technology of China School of Electronic Science and Engineering Sichuan Chengdu610054 China National Yang Ming Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan

A novel dual-core dual-mode class-F voltage-controlled oscillator (VCO) with wide frequency tuning range (TR) is proposed in this letter. It consists of two coupled parallel "8"-shaped inductor and two crossed-coupled VCO cores. To increase the TR of the proposed VCO without adding additional footprint size, a single-turn common-mode inductor is embedded inside the "8"-shaped inductor. By controlling the mode switches, the inductor can work in different modes with large inductance difference, realizing large VCO TR consequently. Then, the two coupled inductors were engineered to form the fundamental and third harmonic resonances, respectively, thereby producing a pseudo-square wave output waveform and realizing class-F operation. With the proposed configuration, the phase noise (PN) of the proposed VCO can be significantly reduced without increasing VCO core size. To demonstrate the proposed idea, a VCO prototype is fabricated in a 65-nm CMOS process with a core size of 1.235×0.8mm. It achieves a wide frequency TR from 2.84 to 7.04 GHz. The measured PN at 1-MHz offset is from -123.9 to -113.1 dBc/Hz, demonstrating an FOMT of 196.0-201.3 dBc/Hz. © 2023 IEEE.

关键词： Variable frequency oscillators

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Output Performance Evaluation of Modified Electrodes for Microbial Batteries 5

Output Performance Evaluation of Modified Electrodes for Mic...

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5th IEEE Eurasia Conference on IOT, Communication and engineering, ECICE 2023

作者： Ishibashi, Daikaku Tojo, Tomohiro Shizuoka Institute of Science and Technology Graduate School of Science and Engineering Department of System Engineering Shizuoka Japan Shizuoka Institute of Science and Technology Faculty of Science and Technology Department of Electrical and Electronic Engineering Shizuoka Japan

ISBN: (纸本)9798350314694

Recently, microbial batteries have attracted attention as a new power generation method. A microbial battery obtains power from the action of power-generating bacteria and generates power without electrochemical reactions or electrical conversion using solar or wind energy. Since it obtains electricity from the soil, it generates electricity regardless of the weather and does not emit harmful substances. However, currently available microbial batteries generate only a small amount of electric energy, and there are many problems in the operation of mobile batteries and small sensors. In addition, although research on power-generating bacteria and the improvement of electrode materials are progressing, there are currently few reports that combine electrodes and electricity-generating bacteria as microbial batteries. In this study, we produced a microbial battery to charge smartphones, laptop computers, and electric vehicles by extracting power from the soil under circumstances where it is difficult to secure a power source such as a disaster. Therefore, after confirming that it is possible to generate electricity with familiar soil, we explored the conditions for the improvement of power generation efficiency. In particular, we modified the electrodes so that power-generating bacteria could efficiently decompose organic molecules in soil and convert them into electrical energy. To evaluate the performance of the microbial battery, we applied the diffusion equation used to determine the reaction rate of lithium-ion batteries. © 2023 IEEE.

关键词： Diffusion Equation Microbial Batteries Output Performance Reaction Rate

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Inter-Agent Collision Avoidance for Decentralized 3D Fixed-Wing Flocking 10

Inter-Agent Collision Avoidance for Decentralized 3D Fixed-W...

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10th Indian Control Conference, ICC 2024

作者： Gupta, Archit Tak, Ajay Kumar, Shashi Ranjan Vachhani, Leena The Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India The Department of Aerospace Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India The System & Control Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India

ISBN: (纸本)9798331517212

UAV swarms have gained prominence due to their reliability, agility, and cooperative capabilities. This paper addresses the challenges of devising algorithms for fixed-wing UAVs posed by non-holonomic kinematics and actuator constraints. While existing works explored optimal control, artificial potential fields, and biologically inspired methods, these often overlook 3-dimensional non-holonomic constraints and actuator saturation. This work contributes to a decentralized 3D fixed-wing flocking algorithm that ensures inter-agent collision avoidance and effective flock formation. Moreover, using a leader-follower model, the agents track a virtual leader while communicating only with neighbors, keeping the motion constraints of fixed-wings. We establish safe initial conditions to guarantee collision avoidance. Numerical simulations validate the proposed algorithm’s robustness, demonstrating its effectiveness in solving the flocking problem for non-holonomic fixed-wing agents and advancing UAV swarm coordination. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Improving the ductility of laser directed energy deposited borated stainless steel by increasing laser power

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Journal of Manufacturing Processes 2025年 145卷 494-507页

作者： Huang, Sheng Li, Qingyu Zhang, Xiaoyu Cui, Bin Li, Dichen Zhang, Anfeng Miao, Kai State Key Laboratory for Manufacturing Systems Engineering School of Mechanical Engineering Xi'an Jiaotong University Xi'an710049 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China Department of Mechanical and Electrical Engineering Yuncheng University Yuncheng044000 China Co. Ltd. Chengdu610091 China

Borated stainless steels (BSSs) are extensively applied in the nuclear energy industry due to boron's excellent thermal neutron absorption capacity, but large and brittle borides formed during casting result in a low ductility. Here, a BSS was produced by laser directed energy deposition, and an investigation was conducted to analyze the impact of laser power on both the microstructure and mechanical properties of the deposited material. Fibrous borides with relatively low volume fraction in the overlapping zone resulted in higher ductility, while lamellar borides with relatively large volume fraction in the non-overlapping zone led to higher strength. As the laser power increased from 180 W to 330 W, the size of fibrous and lamellar eutectic borides and austenite increased significantly, the width of the soft overlapping zone increased by 2.27 times, and the elongation increased by 2.03 times, although yield strength and ultimate tensile strength decreased by 46.3 % and 31.7 %, respectively. As a result, these findings confirmed the feasibility of significantly improving the ductility of the as-deposited BSS by increasing the laser power. The work here provides a way to tailoring the mechanical properties of BSS produced by laser additive manufacturing. © 2025 The Society of Manufacturing Engineers

关键词： Ductility

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Predicting CO2 Emission of Gas Turbine Using Hybrid GRNN-GA Machine Learning Approach 4

Predicting CO2 Emission of Gas Turbine Using Hybrid GRNN-GA ...

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4th International Conference on Electronic and electrical engineering and Intelligent system, ICE3IS 2024

作者： Winarto, Rudy Purnomo, Mauridhi Hery Anggraeni, Wiwik School of Interdisciplinary Management and Technology Sepuluh Nopember Institute of Technology Surabaya Indonesia Sepuluh Nopember Institute of Technology Department of Electrical Engineering Surabaya Indonesia Sepuluh Nopember Institute of Technology Department of Information System Surabaya Indonesia

ISBN: (纸本)9798350378368

The RB211 gas turbine, extensively utilized in the oil and gas industries, generates significant CO2 emissions during its combustion process. Optimizing turbine operation and reducing emissions can be achieved through predictive maintenance and monitoring using advanced analytics and machine learning. Artificial neural networks (ANNs) have become the most typical machine learning technique used in Predictive Emissions Monitoring systems (PEMS). This research will employ GRNN-GA model configuration that utilizes a 32-unit hidden layer with ReLU activation for processing 16 input parameters to predict a single output value, leveraging Adam optimizer and genetic algorithm for optimal configuration. A GRNN-GA hybrid method is expected to combine GRNNs' strong nonlinear regression with GAs' optimization for fine-tuning, boosting prediction accuracy in prediction tasks. The GRNN-GA method achieves strong performance, especially with population sizes of 2,000 and 500, demonstrating high accuracy and reliability through very low error metrics and perfect R2 scores. Its model maintains excellent effectiveness, solidifying the potential for general regression tasks that benefit from genetic algorithm optimization. © 2024 IEEE.

关键词： Gas industry

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