Chinese Journal of Electrical Engineering最新文献_第9页

Designing an On-board Charger to Efficiently Charge Multiple Electric Vehicles 设计一种车载充电器，为多辆电动汽车高效充电

Chinese Journal of Electrical Engineering Pub Date : 2023-06-01 DOI: 10.23919/CJEE.2023.000019

Jyoti Gupta;Rakesh Maurya;Sabha Raj Arya

{"title":"Designing an On-board Charger to Efficiently Charge Multiple Electric Vehicles","authors":"Jyoti Gupta;Rakesh Maurya;Sabha Raj Arya","doi":"10.23919/CJEE.2023.000019","DOIUrl":"10.23919/CJEE.2023.000019","url":null,"abstract":"An on-board charger for efficiently charging multiple battery-operated electric vehicles (EVs) is introduced. It has evolved as a single-input dual-output (SIDO) integrated boost-single ended primary inductor converter (SEPIC) fly-back converter, offering cost-effectiveness, reliability, and higher efficiency compared to conventional chargers with equivalent specifications. The proposed system includes an additional regulated output terminal, in addition to an existing terminal for charging the EV battery of a 4-wheeler, which can be used to charge another EV battery, preferably a 2-wheeler. With the aid of control techniques, unity power factor operations are obtained during constant-voltage (CV)/constant-current (CC) charging for the grid-to-vehicle (G2V) operating mode. Using mathematical modelling analysis, the proposed system is developed in a Matlab/Simulink environment, and the results are validated in a real-time simulator using dSPACE-1104. The proposed system is employed for charging the batteries of two EVs with capacities of 400 V, 40 A · h and 48 V, 52 A · h for the 4-wheeler and 2-wheeler, respectively. Its performance is investigated under different operating modes and over a wide range of supply voltage variations to ensure safe and reliable operation of the charger.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 2","pages":"38-56"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10173479/10173695.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41848420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Current Status and Development Tendency of Wearable Cardiac Health Monitoring 佩戴式心脏健康监护的现状与发展趋势

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000016

Yifeng Wang;Zheng Zhao;Jiangtao Li

引用次数: 0

Review of Ex Vivo Cardiac Electrical Mapping and Intelligent Labeling of Atrial Fibrillation Substrates 心房颤动基质体外心脏电标测和智能标记研究进展

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000008

Yi Chang;Ming Dong;Bin Wang;Ming Ren;Lihong Fan

引用次数: 0

Short-term Photovoltaic Power Forecasting Using SOM-based Regional Modelling Methods 基于som的区域建模方法的短期光伏发电预测

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000004

Jun Li;Qibo Liu

{"title":"Short-term Photovoltaic Power Forecasting Using SOM-based Regional Modelling Methods","authors":"Jun Li;Qibo Liu","doi":"10.23919/CJEE.2023.000004","DOIUrl":"10.23919/CJEE.2023.000004","url":null,"abstract":"The inherent intermittency and uncertainty of photovoltaic (PV) power generation impede the development of grid-connected PV systems. Accurately forecasting PV output power is an effective way to address this problem. A hybrid forecasting model that combines the clustering of a trained self-organizing map (SOM) network and an optimized kernel extreme learning machine (KELM) method to improve the accuracy of short-term PV power generation forecasting are proposed. First, pure SOM is employed to complete the initial partitions of the training dataset; then the fuzzy c-means (FCM) algorithm is used to cluster the trained SOM network and the Davies-Bouldin index (DBI) is utilized to determine the optimal size of clusters, simultaneously. Finally, in each data partition, the clusters are combined with the KELM method optimized by differential evolution algorithm to establish a regional KELM model or combined with multiple linear regression (MR) using least squares to complete coefficient evaluation to establish a regional MR model. The proposed models are applied to one-hour-ahead PV power forecasting instances in three different solar power plants provided by GEFCom2014. Compared with other single global models, the root mean square errors (RMSEs) of the proposed regional KELM model are reduced by 52.06% in plant 1, 54.56% in plant 2, and 51.43% in plant 3 on average. Such results demonstrate that the forecasting accuracy has been significantly improved using the proposed models. In addition, the comparisons between the proposed and existing state-of-the-art forecasting methods presented have demonstrated the superiority of the proposed methods. The forecasts of different methods in different seasons revealed the strong robustness of the proposed method. In four seasons, the MAEs and RMSEs of the proposed SF-KELM are generally the smallest. Moreover, the \u0000<tex>$R^{2}$</tex>\u0000 value exceeds 0.9, which is the closest to 1.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"158-176"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093784.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47396863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wind Power Probability Density Prediction Based on Quantile Regression Model of Dilated Causal Convolutional Neural Network 基于扩展因果卷积神经网络分位数回归模型的风电概率密度预测

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/cjee.2023.000001

Yunhao Yang, Heng Zhang, Shurong Peng, Sheng Su, Bin Li

引用次数: 0

Interictal Electrophysiological Source Imaging Based on Realistic Epilepsy Head Model in Presurgical Evaluation: A Prospective Study 基于真实癫痫头部模型的发作间电生理源成像在术前评估中的前瞻性研究

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000012

Ruowei Qu;Zhaonan Wang;Shifeng Wang;Le Wang;Alan Wang;Guizhi Xu

{"title":"Interictal Electrophysiological Source Imaging Based on Realistic Epilepsy Head Model in Presurgical Evaluation: A Prospective Study","authors":"Ruowei Qu;Zhaonan Wang;Shifeng Wang;Le Wang;Alan Wang;Guizhi Xu","doi":"10.23919/CJEE.2023.000012","DOIUrl":"10.23919/CJEE.2023.000012","url":null,"abstract":"Invasive techniques are becoming increasingly important in the presurgical evaluation of epilepsy. Adopting the electrophysiological source imaging (ESI) of interictal scalp electroencephalography (EEG) to localize the epileptogenic zone remains a challenge. The accuracy of the preoperative localization of the epileptogenic zone is key to curing epilepsy. The T1 MRI and the boundary element method were used to build the realistic head model. To solve the inverse problem, the distributed inverse solution and equivalent current dipole (ECD) methods were employed to locate the epileptogenic zone. Furthermore, a combination of inverse solution algorithms and Granger causality connectivity measures was evaluated. The ECD method exhibited excellent focalization in lateralization and localization, achieving a coincidence rate of 99.02% (\u0000<tex>$p < 0.05$</tex>\u0000) with the stereo electroencephalogram. The combination of ECD and the directed transfer function led to excellent matching between the information flow obtained from intracranial and scalp EEG recordings. The ECD inverse solution method showed the highest performance and could extract the discharge information at the cortex level from noninvasive low-density EEG data. Thus, the accurate preoperative localization of the epileptogenic zone could reduce the number of intracranial electrode implantations required.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"61-70"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093783.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48470531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wind Power Probability Density Prediction Based on Quantile Regression Model of Dilated Causal Convolutional Neural Network 基于扩展因果卷积神经网络分位数回归模型的风电概率密度预测

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000001

Yunhao Yang;Heng Zhang;Shurong Peng;Sheng Su;Bin Li

{"title":"Wind Power Probability Density Prediction Based on Quantile Regression Model of Dilated Causal Convolutional Neural Network","authors":"Yunhao Yang;Heng Zhang;Shurong Peng;Sheng Su;Bin Li","doi":"10.23919/CJEE.2023.000001","DOIUrl":"https://doi.org/10.23919/CJEE.2023.000001","url":null,"abstract":"Aiming at the wind power prediction problem, a wind power probability prediction method based on the quantile regression of a dilated causal convolutional neural network is proposed. With the developed model, the Adam stochastic gradient descent technique is utilized to solve the cavity parameters of the causal convolutional neural network under different quantile conditions and obtain the probability density distribution of wind power at various times within the following 200 hours. The presented method can obtain more useful information than conventional point and interval predictions. Moreover, a prediction of the future complete probability distribution of wind power can be realized. According to the actual data forecast of wind power in the PJM network in the United States, the proposed probability density prediction approach can not only obtain more accurate point prediction results, it also obtains the complete probability density curve prediction results for wind power. Compared with two other quantile regression methods, the developed technique can achieve a higher accuracy and smaller prediction interval range under the same confidence level.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"120-128"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093777.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49939763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Editorial for Special Issue on Bioelectromagnetics 生物电磁学特刊编辑

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000015

引用次数: 0

Bioeffects of Microgravity and Hypergravity on Animals 微重力和超重力对动物的生物效应

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000011

Guofeng Cheng;Biao Yu;Chao Song;Vitalii Zablotskii;Xin Zhang

{"title":"Bioeffects of Microgravity and Hypergravity on Animals","authors":"Guofeng Cheng;Biao Yu;Chao Song;Vitalii Zablotskii;Xin Zhang","doi":"10.23919/CJEE.2023.000011","DOIUrl":"10.23919/CJEE.2023.000011","url":null,"abstract":"Gravity alterations in space cause significant adaptive effects on the human body, including changes to the muscular, skeletal, and vestibular systems. However, multiple factors besides gravity exist in space; therefore, it is difficult to distinguish gravity-related bioeffects from those of the other factors, including radiation. Although everything on the Earth surface is subject to gravity, gravity-induced effects are not explicitly clear. Here, different research methods that have been used in gravity alterations, including parabolic flight, diamagnetic levitation, and centrifuge, are reviewed and compared. The bioeffects that are reported to be associated with altered gravity in animals are summarized, and the potential risks of hypergravity and microgravity are discussed, with a focus on microgravity, which has been studied more extensively. It should be noted that although various microgravity and hypergravity research methods have their limitations, such as the inevitable magnetic field effects in diamagnetic levitation and short duration of parabolic flight, it is evident that ground-based clinical, animal, and cellular experiments that simulate gravity alterations have served as important and necessary complements to space research. These researches not only provide critical and fundamental biological information on the effects of gravity from biomechanics and the biophysical perspectives, but also help in developing future countermeasures for astronauts.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"29-46"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093809.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41642785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Magnetic Actuation Systems and Magnetic Robots for Gastrointestinal Examination and Treatment 用于胃肠检查和治疗的磁驱动系统和磁机器人

Chinese Journal of Electrical Engineering Pub Date : 2023-03-01 DOI: 10.23919/CJEE.2023.000009

Hongbo Sun;Jianhua Liu;Qiuliang Wang

引用次数: 0