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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

IEEE Transactions on Transportation Electrification 2025年第3期11卷 7379-7388页

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering NSW2007 Australia University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multi-physical analysis and motor design optimization. This paper proposes a new method for thermal steady state modeling and analysis based on transfer learning, which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on transfer learning is developed: the model is pre-trained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R2 and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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power Quality Comprehensive Evaluation Method Based on Game Theory Combination Weighting and QUALIFLEX Algorithm 11th

Power Quality Comprehensive Evaluation Method Based on Game ...

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11th Frontier Academic Forum of electrical engineering, FAFEE 2024

作者： Yan, Guifu Zhang, Hongzhao Wang, Qing Wang, Liye Wang, Lifang Key Laboratory of High Density Electromagnetic Power and Systems Institute of Electrical Engineering Chinese Academy of Sciences Beijing100190 China School of Electronics Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China China Southern Power Grid Company New Smart City High-Quality Power Supply Joint Laboratory Shenzhen Power Supply Bureau Co. LTD Shenzhen China

ISBN: (纸本)9789819788279

In order to enhance the objectivity, accuracy and convenience of power quality comprehensive evaluation of distributed power supply, a new power quality comprehensive evaluation method is proposed with the increasing of large-scale new energy grid-connected and users’ demand for power quality. Firstly, the index system of power quality comprehensive evaluation is established. Secondly, in view of the one-sidedness of a single subjective and objective weighting, The subjective weight is determined by the relational analysis method, the objective weight is determined by the improved entropy method, and finally the game theory introduced into the Specific mode combination of the subjective and the objective weights to obtain the optimal combined weights of each index. Then the QUALIFLEX algorithm model is used to evaluate the power quality comprehensively. The traditional evaluation models such as radar map and cloud model are compared for reference. Finally, the power quality evaluation results obtained by this method are consistent with the actual situation, which proves the accuracy and feasibility of the proposed algorithm. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Comprehensive evaluation Game theory empowerment power quality QUALIFLEX algorithm

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Improved High-Speed Thermal Analysis Based on Two-Step Simulation for High-Frequency Transformers 14

Improved High-Speed Thermal Analysis Based on Two-Step Simul...

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14th Annual IEEE Applied power Electronics Conference and Exposition, APEC 2025

作者： Yi, Zheyuan Sun, Kai Li, Qiang Liu, Zengyang Tsinghua University State Key Laboratory of Power System Department of Electrical Engineering Beijing China Delta Electronics Shanghai Co. Ltd. Shanghai China University Blacksburg Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State BlacksburgVA United States

ISBN: (纸本)9798331516116

Thermal analysis is a crucial and time-consuming step in the optimization design process of high-frequency transformers (HFTs). This paper proposes an improved thermal analysis method based on heat dissipation-conduction two-step simulation, significantly reducing the computation time while ensuring the accuracy of thermal analysis. Simulation results validate the accuracy and of the proposed method and demonstrate that the proposed method saves 82% of computation time for a single thermal analysis case compared to direct CFD. Experimental results further verify the accuracy of the proposed method. An exemplary application of the proposed method in the optimization design of the HFT illustrates a 98% reduction in computation time for thermal analysis during the optimization process. © 2025 IEEE.

关键词： Thermal modeling

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Impact of Electric Vehicle Charging Loads on Distribution Networks 11th

Impact of Electric Vehicle Charging Loads on Distribution Ne...

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11th Frontier Academic Forum of electrical engineering, FAFEE 2024

作者： Wang, Guojun Yuan, Xiaodong Wang, Mingsheng Wang, Liye Yan, Guifu Liao, Chenglin Wang, Lifang Key Laboratory of High Density Electromagnetic Power and Systems Institute of Electrical Engineering Chinese Academy of Sciences Beijing100190 China School of Electronics Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China Electric Power Research Institute State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

ISBN: (纸本)9789819788279

Electric vehicle charging puts the stability of the grid to the test. In order to get the electric vehicle charging load distribution, the impact on the distribution network needs to be studied. In this paper, a vehicle-pile road network model is constructed to obtain the spatial and temporal distribution of EV charging loads. Finally, a simulation study is carried out using the data to obtain the impact of EV charging on the distribution network under different quantities. The results show that the proposed unified models of "road-vehicle-road-vehicle" and "road-electric vehicle" networks can accurately obtain the spatio-temporal distribution of charging loads. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： power distribution networks

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Edge-Driven Industrial Computing power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

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Current Balancing Method of a Multiphase Inverter for Inductive power Transfer System 11th

Current Balancing Method of a Multiphase Inverter for Induct...

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11th Frontier Academic Forum of electrical engineering, FAFEE 2024

作者： Yang, Jixin Shi, Liming Yin, Zhenggang Fan, Manyi Key Laboratory of High Density Electromagnetic Power and Systems Institute of Electrical Engineering Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819788231

Multiphase inverters are usually used to enhance the output power level of inductive power transfer system. However, inconsistencies in the input dc voltage, switch parameters or circuit layout may lead to large circulating currents, thereby reducing the system power level. Therefore, an effective current balancing method is needed to solve this problem. This paper proposes a current balancing method for inductive power transfer system. By dividing the compensating capacitor on the primary side into multiple sections and connecting them to the multiphase branches, circulating current can be effectively suppressed. Compared with the existing methods, the proposed method requires no additional devices or control strategies and effectively blocks the dc component of the circulating current. Simulation results of an inverter with four-phase half-bridge parallel topology are derived to validate the effectiveness of the proposed method. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Inductive power transmission

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Organic cation-supported layered vanadate cathode for high-performance aqueous zinc-ion batteries

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Carbon Energy 2025年第2期7卷 1-12页

作者： Changding Wang Yingfang Li Sida Zhang Tian-Yi Sang|Yu Lei Ruiqi Liu Fu Wan Yuejiao Chen Weigen Chen|Yujie Zheng Shuhui Sun State Key Laboratory of Power Transmission Equipment Technology School of Electrical EngineeringNational Innovation Center for Industry-Education Integration of Energy Storage TechnologyChongqing UniversityChongqingChina Institute National de la Recherche Scientifique(INRS) CentreÉnergie Matériaux TélécommunicationsVarennesQuébecCanada MOE Key Laboratory of Low-grade Energy Utilization Technologies and Systems CQU-NUS Renewable Energy Materials&Devices Joint Laboratory School of Energy&Power EngineeringChongqing UniversityChongqingChina 4State Key Laboratory of Powder MetallurgyCentral South UniversityChangshaChina

Layered vanadates are ideal energy storage materials due to their multielectron redox reactions and excellent cation storage ***,their practical application still faces challenges,such as slow reaction kinetics and poor structural *** this study,we synthesized[Me_(2)NH_(2)]V_(3)O_(7)(MNVO),a layered vanadate with expended layer spacing and enhanced pH resistance,using a one-step simple hydrothermal gram-scale *** analyses and density functional theory(DFT)calculations revealed supportive ionic and hydrogen bonding interactions between the thin-layered[Me_(2)NH_(2)]+cation and[V_(3)O_(7)]-anion layers,clarifying the energy storage mechanism of the H^(+)/Zn^(2+)*** synergistic effect of these bonds and oxygen vacancies increased the electronic conductivity and significantly reduced the diffusion energy barrier of the insertion ions,thereby improving the rate capability of the *** an acidic electrolyte,aqueous zinc-ion batteries employing MNVO as the cathode exhibited a high specific capacity of 433 mAh g^(-1)at 0.1 A g^(-1).The prepared electrodes exhibited a maximum specific capacity of 237 mAh g^(-1)at 5 A g^(-1)and maintained a capacity retention of 83.5%after 10,000 *** work introduces a novel approach for advancing layered cathodes,paving the way for their practical application in energy storage devices.

关键词： [V_(3)O_(7)]-layers layered vanadates organic cations pH resistance zinc-ion batteries

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AI4EF: Artificial Intelligence for Energy Efficiency in the building sector

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SoftwareX 2025年 30卷

作者： Tzortzis, Alexandros Menelaos Kormpakis, Georgios Pelekis, Sotiris Michalitsi-Psarrou, Ariadni Karakolis, Evangelos Ntanos, Christos Askounis, Dimitris Decision Support Systems Laboratory School of Electrical and Computer Engineering Institute of Communications and Computer Systems National Technical University of Athens Greece

AI4EF (Artificial Intelligence for Energy Efficiency) is an advanced, user-centric tool designed to support decision-making in building energy retrofitting and efficiency optimization. Leveraging machine learning (ML) and data-driven insights, AI4EF (Artificial Intelligence for Energy Efficiency) enables stakeholders such as public sector representatives, energy consultants, and building owners—to model, analyze, and predict energy consumption, retrofit costs, and environmental impacts of building upgrades. Featuring a modular framework, AI4EF includes customizable building retrofitting, photovoltaic installation assessment, and predictive modeling tools that allow users to input building parameters and receive tailored recommendations for achieving energy savings and carbon reduction goals. Additionally, the service incorporates a Training Playground for data scientists to refine ML models used by said framework. Finally, AI4EF provides access to the Enershare Data Space to facilitate seamless data sharing and access within the ecosystem. AI4EF's compatibility with open-source identity management (Keycloak) enhances security and accessibility, making it adaptable for various regulatory and organizational contexts. This paper presents an overview of AI4EF's architecture, its application in energy efficiency scenarios, and its potential for advancing sustainable energy practices through artificial intelligence (AI). © 2025 The Authors

关键词： Energy efficiency

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Improved Feed-Forward Control of Active power Decoupler for PV Microinverter With Non-Sinusoidal power Decoupling Capability

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IEEE Transactions on power Electronics 2025年

作者： Shen, Yidi Hasnain, Arafat Zakzewski, Daniel Resalayyan, Rakesh Khaligh, Alireza University of Maryland Department of Electrical and Computer Engineering Maryland Power Electronics Laboratory Institute for Systems Research College ParkMD20742 United States

In single-phase power conversion systems, there is an inherent difference between the dc-side constant and ac-side oscillating power, and power decoupling is required especially in applications like photovoltaic (PV) inverters. Active power decoupling (APD) converters are often used to balance instantaneous power while reducing the size of dc link capacitors and improving the system reliability. Conventionally, APD converters are controlled to decouple only sinusoidal power at double-line frequency. However, the control is further complicated when non-sinusoidal power is delivered due to non-linear circuit components, non-linear loads, or grid distortions. This paper proposes an improved feed-forward APD control scheme with the capability of decoupling non-sinusoidal power, which has application in single-phase systems, particularly all types of PV microinverters. The proposed feed-forward control includes the capacitor voltage calculation under arbitrary power harmonics and a dead-time compensation to increase the accuracy of duty prediction. The proposed algorithm can work as open-loop control to eliminate APD sensors and can serve as a feed-forward term in closed-loop control to improve power decoupling performance, thereby simplifying the controller design. The proposed approach is experimentally verified using a dc-parallel APD prototype, a 50 V 250 W microinverter with non-linear ac capacitor, and a diode rectifier load. © 1986-2012 IEEE.

关键词： Closed loop control systems

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Resilient Cooperative Control of Multiple DC Microgrids With Interconnection Networks Against Cyber Attacks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

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