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A Comprehensive Review on Charging Topologies and Power Electronic Converter Solutions for Electric Vehicles

Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 675-694页

作者： Abdelfatah Ali Hossam H.H.Mousa Mostafa F.Shaaban Maher A.Azzouz Ahmed S.A.Awad the department of electrical engineering American University of Sharjah the department of electrical engineering South Valley University the department of electrical and Computer engineering University of Windsor electrical engineering department Qatar University the department of electrical and Computer engineering Sultan Qaboos University

Electric vehicles(EVs) are becoming more popular worldwide due to environmental concerns, fuel security, and price volatility. The performance of EVs relies on the energy stored in their batteries, which can be charged using either AC(slow) or DC(fast) chargers. Additionally, EVs can also be used as mobile power storage devices using vehicle-to-grid(V2G) technology. Power electronic converters(PECs) have a constructive role in EV applications, both in charging EVs and in V2G. Hence, this paper comprehensively investigates the state of the art of EV charging topologies and PEC solutions for EV applications. It examines PECs from the point of view of their classifications, configurations, control approaches, and future research prospects and their impacts on power quality. These can be classified into various topologies: DC-DC converters, AC-DC converters, DC-AC converters, and AC-AC converters. To address the limitations of traditional DC-DC converters such as switching losses, size, and high-electromagnetic interference(EMI), resonant converters and multiport converters are being used in high-voltage EV applications. Additionally, power-train converters have been modified for high-efficiency and reliability in EV applications. This paper offers an overview of charging topologies, PECs, challenges with solutions, and future trends in the field of the EV charging station applications.

关键词： Topology DC-DC power converters Vehicle-to-grid Electric vehicle charging Batteries Transportation Electromagnetic interference

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Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

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Digital communications and Networks 2024年第1期10卷 53-62页

作者： Zhipeng Cheng Minghui Liwang Ning Chen Lianfen Huang Nadra Guizani Xiaojiang Du department of Information and communication engineering Xiamen UniversityXiamen361005China School of electrical and Computer engineering University of Texas at ArlingtonArlingtonTX7619USA department of electrical and Computer engineering Stevens Institute of TechnologyHobokenNJ07030USA

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

关键词： UAV-user association Multi-connectivity Resource allocation Power control Multi-agent deep reinforcement learning

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An Improved Modulation Strategy for Single-phase Three-level Neutral-point-clamped Converter in Critical Conduction Mode

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 981-990页

作者： Ning Li Yujie Cao Xiaokang Liu Yan Zhang Ruotong Wang Lin Jiang Xiao-Ping Zhang School of electrical engineering Xi'an University of Technology the department of Electronics Information and Bioengineering Xi'an Jiaotong University the department of electrical engineering and Electronics University of Liverpool the department of Electronic Electrical and Systems Engineering University of Birmingham

Two-level totem-pole power factor correction(PFC) converters in critical conduction mode(CRM) suffer from the wide regulation range of switching frequency. Besides, in highfrequency applications, the number of switching times increases, resulting in significant switching losses. To solve these issues, this paper proposes an improved modulation strategy for the single-phase three-level neutral-point-clamped(NPC) converter in CRM with PFC. By optimizing the discharging strategy and switching state sequence, the switching frequency and its variation range have been efficiently reduced. The detailed performance analysis is also presented regarding the switching frequency, the average switching times, and the effect of voltage gain. A 2 k W prototype is built to verify the effectiveness of the proposed modulation strategy and analysis results. Compared with the totem-pole PFC converter, the switching frequency regulation range of the three-level PFC converter is reduced by 36.48% and the average switching times is reduced by 45.10%. The experimental result also shows a 1.2% higher efficiency for the three-level PFC converter in the full load range.

关键词： Switches Switching frequency Control systems Topology Bridge circuits Inductors Customer relationship management

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Attention-Based CNN Fusion Model for Emotion Recognition During Walking Using Discrete Wavelet Transform on EEG and Inertial Signals

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Big Data Mining and Analytics 2024年第1期7卷 188-204页

作者： Yan Zhao Ming Guo Xiangyong Chen Jianqiang Sun Jianlong Qiu School of communication engineering Hangzhou Dianzi UniversityHangzhou 310018China School of Automation and electrical engineering Linyi UniversityLinyi 276000China

Walking as a unique biometric tool conveys important information for emotion recognition.Individuals in different emotional states exhibit distinct walking patterns.For this purpose,this paper proposes a novel approach to recognizing emotion during walking using electroencephalogram(EEG)and inertial signals.Accurate recognition of emotion is achieved by training in an end-to-end deep learning fashion and taking into account multi-modal fusion.Subjects wear virtual reality head-mounted display(VR-HMD)equipment to immerse in strong emotions during walking.VR environment shows excellent imitation and experience ability,which plays an important role in awakening and changing emotions.In addition,the multi-modal signals acquired from EEG and inertial sensors are separately represented as virtual emotion images by discrete wavelet transform(DWT).These serve as input to the attention-based convolutional neural network(CNN)fusion model.The designed network structure is simple and lightweight while integrating the channel attention mechanism to extract and enhance features.To effectively improve the performance of the recognition system,the proposed decision fusion algorithm combines Critic method and majority voting strategy to determine the weight values that affect the final decision results.An investigation is made on the effect of diverse mother wavelet types and wavelet decomposition levels on model performance which indicates that the 2.2-order reverse biorthogonal(rbio2.2)wavelet with two-level decomposition has the best recognition performance.Comparative experiment results show that the proposed method outperforms other existing state-of-the-art works with an accuracy of 98.73%.

关键词： walking multi-modal fusion virtual reality emotion recognition discrete wavelet transform attention mechanism

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Maximum correntropy-based pseudolinear Kalman filter for passive bearings-only target tracking

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Control Theory and Technology 2024年第2期22卷 269-281页

作者： Asfia Urooj Rahul Radhakrishnan department of electrical engineering SVNITSuratGujarat395007India department of electrical engineering NIT CalicutKozhikodeKerala673601India

This paper proposes a new approach for solving the bearings-only target tracking (BoT) problem by introducing a maximum correntropy criterion to the pseudolinear Kalman filter (PLKF). PLKF has been a popular choice for solving BoT problems owing to the reduced computational complexity. However, the coupling between the measurement vector and pseudolinear noise causes bias in PLKF. To address this issue, a bias-compensated PLKF (BC-PLKF) under the assumption of Gaussian noise was formulated. However, this assumption may not be valid in most practical cases. Therefore, a bias-compensated PLKF with maximum correntropy criterion is introduced, resulting in two new filters: maximum correntropy pseudolinear Kalman filter (MC-PLKF) and maximum correntropy bias-compensated pseudolinear Kalman filter (MC-BC-PLKF). To demonstrate the performance of the proposed estimators, a comparative analysis assuming large outliers in the process and measurement model of 2D BoT is conducted. These large outliers are modeled as non-Gaussian noises with diverse noise distributions that combine Gaussian and Laplacian noises. The simulation results are validated using root mean square error (RMSE), average RMSE (ARMSE), percentage of track loss and bias norm. Compared to PLKF and BC-PLKF, all the proposed maximum correntropy-based filters (MC-PLKF and MC-BC-PLKF) performed with superior estimation accuracy.

关键词： Bearings-only target tracking Pseudolinear Kalman filter Maximum correntropy criterion Non-Gaussian noise

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An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

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Computer Modeling in engineering & Sciences 2024年第8期140卷 1689-1710页

作者： Md.Abdur Rahim Fahmid Al Farid Abu Saleh Musa Miah Arpa Kar Puza Md.Nur Alam Md.Najmul Hossain Sarina Mansor Hezerul Abdul Karim department of Computer Science and engineering Pabna University of Science and TechnologyPabna6600Bangladesh Faculty of engineering Multimedia UniversityCyberjaya63100Malaysia department of Computer Science and engineering Bangladesh Army University of Science and TechnologySaidpur5311Bangladesh department of Mathematics Pabna University of Science and TechnologyPabna6600Bangladesh department of electrical Electronic and Communication EngineeringPabnaUniversity of Science and TechnologyPabna6600Bangladesh department of electrical and communication engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Handwriting is a unique and significant human feature that distinguishes them from one another.There are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through verification.However,such systems are susceptible to forgery,posing security risks.In response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or symbols.In response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or symbols.Our innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and classification.One key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive approach.Post-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite features.This meticulous amalgamation resulted in a robust set of 91 features.To enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent features.In the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting characteristics.Moreover,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual classifications.Crucially,our experimental results underscore the superiority of our approach.The CNN,B

关键词： Bengali handwriting(BHW) person identification convolutional neural network(CNN) BiLSTM

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Extension of Distribution Transformer Life in the Presence of Smart Inverter-based Distributed Solar Photovoltaic Systems

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 88-95页

作者： Kanhaiya Kumar Saran Satsangi Ganesh Balu Kumbhar department of electrical and Electronics engineering Motihari College of EngineeringMotihariBiharIndia department of electrical engineering National Institute of Technology(NIT)PatnaPatnaBiharIndia department of electrical engineering Indian Institute of Technology(IIT)RoorkeeRoorkeeUttarakhandIndia

A transformer is an essential but expensive power delivery equipment for a distribution utility.In many distribution utilities worldwide,a sizable percentage of transformers are near the end of their designed life.At the same time,distribution utilities are adopting smart inverter-based distributed solar photovoltaic(SPV)systems to maximize renewable generation.The central objective of this paper is to propose a methodology to quantify the effect of smart inverter-based distributed SPV systems on the aging of distribution transformers.The proposed method is first tested on a modified IEEE-123 node distribution feeder.After that,the procedure is applied to a practical distribution system,i.e.,the Indian Institute of Technology(IIT)Roorkee campus,India.The transformer aging models,alongside advanced control functionalities of grid-tied smart inverter-based SPV systems,are implemented in MATLAB.The open-source simulation tool(OpenDSS)is used to model distribution networks.To analyze effectiveness of various inverter functionalities,time-series simulations are performed using exponential load models,considering daily load curves from multiple seasons,load types,current harmonics,etc.Findings show replacing a traditional inverter with a smart inverter-based SPV system can enable local reactive power generation and may extend the life of a distribution transformer.Simulation results demonstrate,simply by incorporating smart inverter-based SPV systems,transformer aging is reduced by 15%to 22%in comparison to SPV systems operating with traditional inverters.

关键词： Distribution transformer loss of life smart inverter functions solar photovoltaic systems thermal models Volt-VAr control

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Revisiting non-linear Thomson scattering with metamaterials

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National Science Review 2024年第1期11卷 71-72页

作者： Natalia M.Litchinitser department of electrical and Computer engineering Duke University

Non-linear optics is a branch of optics that studies the intriguing and sometimes unexpected ways in which light and matter interact at high intensities, when the polarization density does not respond linearly to the electric field of the light. The pursuit of the perfect non-linear optical material has been ongoing ever since the pioneering experiment on second harmonic generation carried out by Franken in 1961 [1]. Indeed,

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Online Demand Response Characterization Based on Variability in Customer Behavior

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 936-946页

作者： Lester Marrero Daniel Sbárbaro Luis García-Santander the department of electrical engineering University of Concepción IEEE

This paper proposes an online framework to characterize demand response(DR) over time. The proposed framework facilitates obtaining and updating the daily consumption patterns of customers. The essential concept of response profile class(RPC) is introduced for characterization and complemented by the measure of the variability in customer behavior. This paper uses a modified version of the incremental clustering by fast search and find of density peaks(CFSFDP) algorithm for daily profiles, considering the multivariate normal kernel density estimator and incremental forms of the Davies-Bouldin(i DB) and Xie-Beni(i XB) validity indices. Case studies conducted using real-world and simulated daily profiles of residential and commercial Chilean end-users have demonstrated how the proposed framework can continuously characterize DR. The proposed framework is proven to achieve realistic customer models for effective energy management by estimating the customer response to price signals at the distribution system operator(DSO) level.

关键词： Clustering algorithms Behavioral sciences Streams Pricing Feature extraction Monitoring Kernel

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Research on the flow stability and noise reduction characteristics of quasi-periodic elastic support skin

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Defence Technology（防务技术） 2024年第3期33卷 222-236页

作者： Lu Chen Shao-gang Liu Dan Zhao Li-qiang Dong Kai Li Shuai Tang Jin Cui Hong Guo department of Mechanical and electrical engineering Harbin Engineering UniversityHarbin150001China

To enhance flow stability and reduce hydrodynamic noise caused by fluctuating pressure,a quasiperiodic elastic support skin composed of flexible walls and elastic support elements is proposed for fluid noise reduction.The arrangement of the elastic support element is determined by the equivalent periodic distance and quasi-periodic coefficient.In this paper,a dynamic model of skin in a fluid environment is established.The influence of equivalent periodic distance and quasi-periodic coefficient on flow stability is investigated.The results suggest that arranging the elastic support elements in accordance with the quasi-periodic law can effectively enhance flow stability.Meanwhile,the hydrodynamic noise calculation results demonstrate that the skin exhibits excellent noise reduction performance,with reductions of 10 dB in the streamwise direction,11 dB in the spanwise direction,and 10 dB in the normal direction.The results also demonstrate that the stability analysis method can serve as a diagnostic tool for flow fields and guide the design of noise reduction structures.

关键词： Flow stability Quasi-period Flexible wall Elastic support element Hydrodynamic noise

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