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The Structure Improvement Method and Analysis Based on the Characteristics of Motor Magnetic Field

IEEE Transactions on Magnetics 2025年

作者： Liang, Xiaoyu Wang, Mingqiao Liu, Yong Zheng, Ping Gao, Jialin Bai, Jingang School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

In order to further improve the performance of permanent magnet (PM) synchronous motors (PMSM) to meet various applications, it is necessary to compare and study the magnetic field characteristics of various motors from their distribution and slot/pole combination of PMSM. Based on this, the structure improvements can be realized. Firstly, the characteristics of various motors are compared and analyzed to identify issues for improvement. The relationship between structural adjustment and magnetic field are studied based on their respective characteristics. The methods of improving phase characteristics by shifting magnetic field in PMSM with integer-slot distributed winding (ISDW) and design guided by magnetic field to increase torque density in PMSM with true-fractional slot concentrated winding (TFSCW) are researched. Based on the influence of structural changes on magnetic field and performance, the structural improvement methods for different motors are proposed. Finally, the effect of performance improvement with the proposed method on different motors was verified by finite element analysis (FEA). 1965-2012 IEEE.

关键词： Permanent magnets

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A Diffusion Model for Traffic Data Imputation

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 606-617页

作者： Bo Lu Qinghai Miao Yahui Liu Tariku Sinshaw Tamir Hongxia Zhao Xiqiao Zhang Yisheng Lv Fei-Yue Wang the School of Artificial Intelligence University of Chinese Academy of Sciences Baidu Inc. IEEE the State Key Laboratory for Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Meituan Guangdong University of Technology the Department of Transportation Engineering School of Transportation Science and Technology Harbin Institute of Technology

Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems(ITS) in the real world. As a state-of-the-art generative model, the diffusion model has proven highly successful in image generation, speech generation, time series modelling *** now opens a new avenue for traffic data imputation. In this paper, we propose a conditional diffusion model, called the implicit-explicit diffusion model, for traffic data imputation. This model exploits both the implicit and explicit feature of the data simultaneously. More specifically, we design two types of feature extraction modules, one to capture the implicit dependencies hidden in the raw data at multiple time scales and the other to obtain the long-term temporal dependencies of the time series. This approach not only inherits the advantages of the diffusion model for estimating missing data, but also takes into account the multiscale correlation inherent in traffic data. To illustrate the performance of the model, extensive experiments are conducted on three real-world time series datasets using different missing *** experimental results demonstrate that the model improves imputation accuracy and generalization capability.

关键词： Data imputation diffusion model implicit feature time series traffic data

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Optimal Scheduling of Importance-Based DoS Attack in Multisystems

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IEEE Sensors Journal 2025年第9期25卷 15770-15779页

作者： Wang, Jiacheng Liu, Hanxiao Liu, Chun Ren, Xiaoqiang Wang, Xiaofan Shanghai University School of Future Technology Institute of Artificial Intelligence Shanghai200444 China Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China Shanghai Institute of Technology School of Electrical and Electronic Engineering Shanghai200235 China

This article is concerned with the security of remote state estimation in multisystems. Different from most works, we study a novel denial-of-service (DoS) attack, which we call an importance-based DoS attack. Here, subsystem importance is defined as the quantitative impact of each subsystem on the overall state estimation accuracy, which is critical for ensuring correct decision-making. This work assumes that there are N subsystems, and the DoS attacker can only target M out of N communication channels due to energy constraints. The attacker’s goal is to determine the optimal strategy to degrade the performance of remote state estimation. Two attack scenarios are considered: a model-based scenario where the attacker has knowledge of the overall dynamics and parameters of the system and a model-free scenario where the attacker lacks access to the wireless channel model. The problem is formulated as a Markov decision process (MDP) with an infinite time horizon. In addition, the optimal attack strategies corresponding to different importance function forms under various scenarios are considered, and solutions for some specific cases are provided. Numerical examples are presented to demonstrate the effectiveness of the proposed strategies. © 2001-2012 IEEE.

关键词： Markov processes

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Influence of Six Degrees of Freedom Motion on the Cavitation Characteristics of a Floating Horizontal-Axis Tidal Current Turbine

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China Ocean engineering 2025年第2期39卷 303-315页

作者： JIANG Jin ZHAO Mu-yu ZHENG Xiong-bo School of Mechanical and Electrical Engineering Jinling Institute of Technology School of Mechanical Engineering Yancheng Institute of Technology School of Mathematics Science Harbin Engineering University

A floating horizontal-axis tidal current turbine(HATT) is an underwater power generation device where cavitation inevitably occurs on blade surfaces, severely affecting a turbine's lifespan. Under wave action, these floating turbines exhibit six degrees of freedom motion, potentially intensifying the cavitation on the blade surfaces. This study selects three types of oscillatory motions from the six degrees of freedom: roll, yaw, and pitch. Computational fluid dynamics(CFD) methods are used for numerical calculations, and transient simulations of multiphase flow are conducted on the basis of the Reynolds-Averaged Navier-Stokes(RANS) model. Research has revealed strong correlations between flow velocity, the blade tip speed ratio, and cavitation. During oscillatory motion, the motion period and amplitude also significantly impact cavitation. In roll motion, the cavitation rate can increase by up to 59% with decreasing period, whereas in pitch and yaw motions, the increases are 7.57 times and 36% larger, respectively. With an increase in amplitude during roll motion, the cavitation rate can increase by up to 1.08 times, whereas in pitch and yaw motions, the increases are 3.49 times and 45%, respectively. The cavitation rate on the blade surfaces is the highest in pitch motion, followed by roll and yaw motions.

关键词： cavitation effect CFD simulation horizontal-axis turbine multiphase flow six degrees of freedom motion tidal current energy

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Research on Fault-Tolerant Dual Active Bridge Converter Based on Half-Bridge Multiplexing

Research on Fault-Tolerant Dual Active Bridge Converter Base...

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2025 International Conference on electrical automation and Artificial Intelligence, ICEAAI 2025

作者： Guo, Yufei Yuan, Baihui Wu, Qian Li, Yiliang Wang, Yijie Xu, Dianguo Harbin Institute of Technology Electrical Engineering and Automation Harbin China Company Limited Economic Research Institute State Grid Heilongjiang Electric Power Supply Harbin China

ISBN: (纸本)9798331506797

In this paper, based on the research background of the voltage instability phenomenon generated by the possible device failures and the serious imbalance of sunshine in the high-latitude cold region of photovoltaic power generation, a topology study of fault-tolerant dual active bridge converter based on half-bridge multiplexing is proposed, which can realize the stable output in the wide range of voltage inputs and part of the device failures, and has the effect of maintaining the stability of grid voltage and improving the power quality of DC power grid. The proposed converter can realize stable output even under a wide range of voltage inputs and some device failures to maintain the stability of grid voltage and improve the power quality of DC network. In this paper, the modal analysis of the proposed converter is carried out, and the fault conditions are analyzed, and the circuit characterization and simulation verification are completed to prove the accuracy of the theoretical analysis. © 2025 IEEE.

关键词： Dual Active Bridge Converter fault-tolerant converter High Latitude Extreme Cold Photovoltaics

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An SPH model reconstruction framework with fragment mapping method for multiplate structure hypervelocity impact simulation

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Advances in Space Research 2025年第11期75卷 8140-8157页

作者： Cao, Xu Zhou, Jianqiu Xu, Huadong Song, Di Miao, Changqing National Key Laboratory of Science and Technology on Advanced Composites in Special Environment Harbin Institute of Technology Harbin150001 China School of Basic Medical Sciences Harbin Medical University Harbin150001 China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China

Smoothed Particle Hydrodynamics (SPH) method is widely used in hypervelocity impact analysis, but it is computationally inefficient for common multiplate structures, such as multi-shock, mesh double-bumper, and stuffed shields. To improve the efficiency and accuracy of the SPH method, a reconstruction framework is proposed, including a fragment identification method, a fragment mapping method, and a sequential modeling and simulation approach. In the reconstruction framework, the total impact simulation of a multiplate structure consisting of n plates is decomposed into n individual impacts on each plate. To reduce the computation for each impact, a fragment identification method and a fragment mapping method are developed. Fragments generated from the impact with the i-th plate (i © 2025 COSPAR

关键词： 3D reconstruction

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Performance Analysis of Hydrogen Storage Insulation System in Lunar Base

Performance Analysis of Hydrogen Storage Insulation System i...

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International Conference of electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Li, Jing Fan, Fulin Li, Heran Fei, Teng Sun, Chuanyu Jiang, Jinhai Yang, Wenying Song, Kai School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150001 China Suzhou Research Institute Harbin Institute of Technology Suzhou215104 China Complex Environment Architecture Research Institute Harbin Institute of Technology Harbin150001 China State Key Laboratory of Hydro-Power Equipment Harhin150001 China

ISBN: (纸本)9789819618637

In-situ resource utilization (ISRU) is one of the critical technologies for achieving long-term sustainable construction of lunar bases. Utilizing the extremely low temperatures in the permanently shadowed regions of the Moon to store liquid hydrogen is an essential energy storage method during the initial phases of lunar base construction. Multilayer insulation (MLI) structures can maintain the low-temperature state of liquid hydrogen without the need for additional active control equipment such as refrigeration units or circulation pumps, relying on the excellent thermal resistance properties of the materials themselves to ensure stable system operation. This research builds upon the existing MLI structures, taking into comprehensive consideration the impact of different structural forms and interlayer materials on thermal insulation performance in the lunar context. By conducting performance simulations on various configurations of hollow glass microspheres coupled with multilayer insulation (HGMs-MLI), the study identifies the optimal hydrogen storage insulation structures for the lunar shadowed regions, providing crucial guidance and reference for future liquid hydrogen storage research in lunar exploration. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Thermal insulation

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Deadbeat Predictive Current Control Strategy for Permanent Magnet-Assisted Synchronous Reluctance Motor Based on Adaptive Sliding Mode Observer

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World Electric Vehicle Journal 2025年第4期16卷

作者： Gao, Bo Zhang, Guoqiang Wang, Gaolin Xu, Dianguo School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150000 China

To suppress current and torque ripples, this paper proposes a novel deadbeat predictive current control strategy based on an adaptive sliding mode observer for permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) drives. The parameter sensitivity of predictive current control is analyzed, and a sliding mode observer is employed to calculate the parameter disturbances for voltage compensation. The predicted current is utilized instead of the sampled current to address the one-step delay issue, effectively suppressing the adverse effects of parameter mismatch in predictive control. The adaptive control parameter module suppresses the chattering phenomenon in sliding mode control and enhances the observer’s adaptability under varying load conditions. The effectiveness of the proposed strategy is validated on a 2.2 kW PMa-SynRM platform. This strategy can suppress current and torque fluctuations under complex operating conditions, which has significant implications for electric vehicle drive control. © 2025 by the authors.

关键词： Predictive control systems

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Electric Thermal Balance Control Method of Plant Level Integrated Energy Systems Based on Robust Linear Optimization With Probability Density Bias Prediction Characteristics

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IET Generation, Transmission and Distribution 2025年第1期19卷

作者： Shi, Jiakui Li, Menghui Fan, Shuangshuang Yao, Kun Wan, Jie Peng, E. School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China School of Energy Science and Engineering Harbin Institute of Technology Harbin China

The rapid development of renewable energy has promoted the research of the integrated energy system. In particular, the joint optimal scheduling of renewable energy and traditional thermal power units is the key technology to solve the current renewable energy integration and the source network load balance. At present, the total installed capacity of cogeneration units is huge, which hinders the integration of renewable energy and the flexibility of the power grid regulation. Therefore, this paper proposes a robust optimal scheduling strategy for the plant-level integrated energy system considering electricity-heat balance. The wind power and solar energy are connected in parallel with the heating network of cogeneration units to decouple heat and power in a more economical and flexible way, while improving the integration of renewable energy. Based on the principle of Kang's robust optimization, robust optimization, a linear robust optimization probability density bias prediction optimization method for the plant-level integrated energy system considering the electric-heat balance is proposed in this paper. The dynamic nonlinear constraints in the output process of thermal and electrical loads are transformed into linear, which takes into account the conservatism of robust optimization and the economy of the objective function. The proposed optimization algorithm facilitates the integration of a high proportion of renewable energy into the power grid and is also applicable to other integrated energy systems with nonlinear constraint characteristics. © 2025 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of engineering and technology.

关键词： Wind power integration

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1-Hour Ahead Wind Power Prediction Based on Multi-model Fusion Strategy 19th

1-Hour Ahead Wind Power Prediction Based on Multi-model Fusi...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Zhang, Tengyu Di, Shuai Wang, Xu Zhu, Deyu Ren, Xiaochen School of Electrical Engineering and Automation Harbin Institute of Technology Heilongjiang Harbin China Institute of Thermal Control Technology Datang Northeast Electric Power Test and Research Institute Co. Ltd. Jilin Changchun China

ISBN: (纸本)9789819613861

The accuracy of wind power prediction is of great significance for optimizing power system scheduling and improving power output stability. In order to solve the established difficulties in wind prediction, a prediction method combining multiple models is proposed with the aim of realizing a high-precision wind prediction strategy up to 1 hour in advance. Firstly, the raw wind power data is preprocessed. Secondly, the comprehensive feature se-lection (CFS) algorithm is used to calculate the sum of the importance of each feature variable, and the input set of asynchronous eldest child models corresponding to the target feature is selected. Then, the adaptive noise complete set empirical mode decomposition algorithm (CEEMDAN) is used to decompose the wind power sequence, and each component after decomposition is modeled separately. The comparative analysis of a series of experimental methods shows that the method proposed in this study demonstrates excellent prediction accuracy and stable performance in the field of multi-step wind energy prediction. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Wind forecasting

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