Pub Date : 2024-03-13DOI: 10.1109/JESTIE.2024.3377165
Rahul Patil;Saravana Prakash P
An improved boost-packed E-cell-based nine-level (9L) buck power factor correction (PFC) (BPFC) rectifier is proposed in this article. The multilevel operation of the proposed 9L-BPFC rectifier lessens harmonic content in the supply current and reduces voltage stress on the power devices. In addition, it can supply single/multiple dc loads at the same time. The series–parallel switching of the capacitors autobalances its voltages for possible load configurations. Hence, it reduces the need for complicated control to balance capacitor voltages and resolve the issue of rectifier instability during dynamic conditions. Moreover, it supports open-circuit fault tolerant operation for middle switches and maintains the same output power under fault conditions as in healthy mode. The operating principle, modulation strategy, device ratings, and capacitor sizing of the proposed rectifier are presented in this article. Finally, the performance of the proposed 9L buck PFC (9L-BPFC) rectifier is examined and verified using experimental results. The results revealed an optimal efficiency of 97.02%, a total harmonic distortion of 2.64%, and a power factor of 0.9978.
{"title":"An Ameliorated Boost Packed E-Cell Nine-Level Single/Multiple Output Buck PFC Rectifier","authors":"Rahul Patil;Saravana Prakash P","doi":"10.1109/JESTIE.2024.3377165","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3377165","url":null,"abstract":"An improved boost-packed E-cell-based nine-level (9L) buck power factor correction (PFC) (BPFC) rectifier is proposed in this article. The multilevel operation of the proposed 9L-BPFC rectifier lessens harmonic content in the supply current and reduces voltage stress on the power devices. In addition, it can supply single/multiple dc loads at the same time. The series–parallel switching of the capacitors autobalances its voltages for possible load configurations. Hence, it reduces the need for complicated control to balance capacitor voltages and resolve the issue of rectifier instability during dynamic conditions. Moreover, it supports open-circuit fault tolerant operation for middle switches and maintains the same output power under fault conditions as in healthy mode. The operating principle, modulation strategy, device ratings, and capacitor sizing of the proposed rectifier are presented in this article. Finally, the performance of the proposed 9L buck PFC (9L-BPFC) rectifier is examined and verified using experimental results. The results revealed an optimal efficiency of 97.02%, a total harmonic distortion of 2.64%, and a power factor of 0.9978.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1625-1633"},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-12DOI: 10.1109/JESTIE.2024.3376299
Minglei Yang;Yeqin Wang;Xiusen Wang;Zaimin Zhong
In this article, a design method of equal inner and outer flux applicable to radial flux dual-rotor permanent magnet synchronous machine (RFDR-PMSM) with a modular stator is proposed. Based on this design method, the power equation of the RFDR-PMSM with the modular stator is derived, which reveals the theoretical relationship between the main sizes and the power. In order to simplify the winding process of the modular stator, a fractional-slot concentrated winding is selected for RFDR-PMSM with the modular stator. Then, a 24-slots and 20-poles RFDR-PMSM with a modular stator is designed using the proposed design methodology. Through finite element analysis (FEA), it is found that the design RFDR-PMSM with the modular stator has higher power density and efficiency compared with the traditional RFDR-PMSM with a stator yoke. Moreover, a modular stator structure with a pin connection is proposed to solve the problem that the stator loses effective support after removing the stator yoke. Finally, a prototype of the RFDR-PMSM with the modular stator is manufactured. The back electromotive force (EMF), current-torque curve, and the efficiency map up to 10 kW of the RFDR-PMSM with the modular stator are tested, and the correctness of the finite element model and theoretical design is verified by comparing the experimental results with the FEA results.
{"title":"Design and Study of Radial Flux Dual-Rotor Permanent Magnet Synchronous Machine With Modular Stator","authors":"Minglei Yang;Yeqin Wang;Xiusen Wang;Zaimin Zhong","doi":"10.1109/JESTIE.2024.3376299","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3376299","url":null,"abstract":"In this article, a design method of equal inner and outer flux applicable to radial flux dual-rotor permanent magnet synchronous machine (RFDR-PMSM) with a modular stator is proposed. Based on this design method, the power equation of the RFDR-PMSM with the modular stator is derived, which reveals the theoretical relationship between the main sizes and the power. In order to simplify the winding process of the modular stator, a fractional-slot concentrated winding is selected for RFDR-PMSM with the modular stator. Then, a 24-slots and 20-poles RFDR-PMSM with a modular stator is designed using the proposed design methodology. Through finite element analysis (FEA), it is found that the design RFDR-PMSM with the modular stator has higher power density and efficiency compared with the traditional RFDR-PMSM with a stator yoke. Moreover, a modular stator structure with a pin connection is proposed to solve the problem that the stator loses effective support after removing the stator yoke. Finally, a prototype of the RFDR-PMSM with the modular stator is manufactured. The back electromotive force (EMF), current-torque curve, and the efficiency map up to 10 kW of the RFDR-PMSM with the modular stator are tested, and the correctness of the finite element model and theoretical design is verified by comparing the experimental results with the FEA results.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1409-1419"},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-12DOI: 10.1109/JESTIE.2024.3376291
Sai Bhargava Althurthi;Kaushik Rajashekara;Tutan Debnath
In this article, an ultrawide output voltage reconfigurable LLC resonant dc–dc converter is presented for electric vehicle fast charging application. The proposed LLC topology design uses six operating modes for providing a wide output voltage from 100 to 1100 V with a constant current output. The proposed circuit consists of a three-winding high-frequency transformer connected with a mosfet full bridge at the primary side and two voltage doubler diode rectifiers at the secondary side. In addition, two mosfet s and two diodes switch combinations at the output side reconfigure the two diode rectifiers outputs in three ways. Hence, with full-bridge and half-bridge operations from the primary side, the proposed circuit provides a total of six operating modes. The detailed step-by-step procedure is presented for designing a continuous output voltage range using six operating modes. The proposed converter has a low operation frequency range and high magnetization to series resonating inductance ratio of the LLC tank. The closed-loop operation of the converter is validated on PLECS for a 30-A CC output. The open-loop experimental results of a 700-W laboratory prototype are also presented to validate the six operating modes for ultrawide output voltage gain.
{"title":"A Novel Ultrawide Output Range DC–DC Converter for EV Fast Charging","authors":"Sai Bhargava Althurthi;Kaushik Rajashekara;Tutan Debnath","doi":"10.1109/JESTIE.2024.3376291","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3376291","url":null,"abstract":"In this article, an ultrawide output voltage reconfigurable \u0000<italic>LLC</i>\u0000 resonant dc–dc converter is presented for electric vehicle fast charging application. The proposed \u0000<italic>LLC</i>\u0000 topology design uses six operating modes for providing a wide output voltage from 100 to 1100 V with a constant current output. The proposed circuit consists of a three-winding high-frequency transformer connected with a \u0000<sc>mosfet</small>\u0000 full bridge at the primary side and two voltage doubler diode rectifiers at the secondary side. In addition, two \u0000<sc>mosfet</small>\u0000s and two diodes switch combinations at the output side reconfigure the two diode rectifiers outputs in three ways. Hence, with full-bridge and half-bridge operations from the primary side, the proposed circuit provides a total of six operating modes. The detailed step-by-step procedure is presented for designing a continuous output voltage range using six operating modes. The proposed converter has a low operation frequency range and high magnetization to series resonating inductance ratio of the \u0000<italic>LLC</i>\u0000 tank. The closed-loop operation of the converter is validated on PLECS for a 30-A CC output. The open-loop experimental results of a 700-W laboratory prototype are also presented to validate the six operating modes for ultrawide output voltage gain.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 2","pages":"586-596"},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140606187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study presents a neural network-based control method of dc–dc converter to realize fast transient response in coordination with the PID control. The neural network control effectively improves the transient response by modifying the reference value in the PID control dynamically using its predictions in the transient state. However, it causes an overcompensation phenomenon and the convergence property becomes worse. To suppress the overcompensation and obtain the faster convergence, neural network timing control and bias correction are also adopted simultaneously. In the presented method, to realize edge-level prediction computation processing of the neural network control, data acquisition and repetitive training of neural networks are proceeded offline and the prediction by repetitive trained neural networks is implemented online in a commercially available computation unit. Experimental results confirm that the presented method obtains the significantly faster transient response compared with the conventional PID control.
{"title":"Implementation of Neural Network and Bias Correction Controls for Fast Transient Response of DC–DC Converter","authors":"Hidenori Maruta;Yasuaki Ikeda;Shota Watanabe;Tomokazu Sakashita;Hiroyasu Iwabuki","doi":"10.1109/JESTIE.2024.3374205","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3374205","url":null,"abstract":"This study presents a neural network-based control method of dc–dc converter to realize fast transient response in coordination with the PID control. The neural network control effectively improves the transient response by modifying the reference value in the PID control dynamically using its predictions in the transient state. However, it causes an overcompensation phenomenon and the convergence property becomes worse. To suppress the overcompensation and obtain the faster convergence, neural network timing control and bias correction are also adopted simultaneously. In the presented method, to realize edge-level prediction computation processing of the neural network control, data acquisition and repetitive training of neural networks are proceeded offline and the prediction by repetitive trained neural networks is implemented online in a commercially available computation unit. Experimental results confirm that the presented method obtains the significantly faster transient response compared with the conventional PID control.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 2","pages":"392-401"},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140606190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A modern battery management system in electric vehicles plays a crucial role in enhancing battery pack safety, reliability, and performance, particularly in E-transportation applications. To achieve more accurate estimation methods, combining battery digital twinning with cloud computing for computational power and data storage capabilities proves beneficial. Over the last decade, various data-driven state-of-charge (SOC) estimation methods, such as machine learning and deep learning approaches, have been introduced to provide highly precise estimations. The widely used SOC estimation method in the industry is the extended Kalman filter (EKF). To explore and analyze the potential use of SOC estimation in a cloud platform, this article develops and conducts a comparative analysis of four SOC estimation methods: EKF, feedforward neural network, gated recurrent unit, and long short-term memory. These models are deployed in two cloud computing infrastructures, and their accuracy and computing time are thoroughly examined in this study. This study concludes that the EKF method is the fastest and most accurate among all considered methods. It boasts an average execution time of 54.8 ms and a mean absolute error of 2 × 10 −4 when measured over a physical distance of approximately 450 km via the mobile network long-term evolution.
{"title":"Comprehensive Comparative Analysis of Deep-Learning-Based State-of-Charge Estimation Algorithms for Cloud-Based Lithium-Ion Battery Management Systems","authors":"Dominic Karnehm;Akash Samanta;Latha Anekal;Sebastian Pohlmann;Antje Neve;Sheldon Williamson","doi":"10.1109/JESTIE.2024.3373267","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3373267","url":null,"abstract":"A modern battery management system in electric vehicles plays a crucial role in enhancing battery pack safety, reliability, and performance, particularly in E-transportation applications. To achieve more accurate estimation methods, combining battery digital twinning with cloud computing for computational power and data storage capabilities proves beneficial. Over the last decade, various data-driven state-of-charge (SOC) estimation methods, such as machine learning and deep learning approaches, have been introduced to provide highly precise estimations. The widely used SOC estimation method in the industry is the extended Kalman filter (EKF). To explore and analyze the potential use of SOC estimation in a cloud platform, this article develops and conducts a comparative analysis of four SOC estimation methods: EKF, feedforward neural network, gated recurrent unit, and long short-term memory. These models are deployed in two cloud computing infrastructures, and their accuracy and computing time are thoroughly examined in this study. This study concludes that the EKF method is the fastest and most accurate among all considered methods. It boasts an average execution time of 54.8 ms and a mean absolute error of 2 × 10\u0000<sup>−4</sup>\u0000 when measured over a physical distance of approximately 450 km via the mobile network long-term evolution.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 2","pages":"597-604"},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10460103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140606122","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}
Bearing condition monitoring in the field of industrial machinery has increasingly relied on the incorporation of artificial intelligence techniques. This article introduces a fault detection and diagnosis methodology for bearing condition monitoring processes, utilizing the Mahalanobis squared distance (MSD). In the initial phase, a health index, namely MSD, is proposed to accurately indicate the health condition of the spherical bearing in an induction motor based on vibration signals. The MSD serves as a preclassification stage, effectively addressing the issue of data overlap and facilitating the identification of distinct data classes, particularly in cases where nonlinear and non-Gaussian data are prevalent. In the subsequent phase, a deep learning (DL)-based approach utilizing transfer learning is employed for the classification of the labeled dataset by MSD. Three established models, namely AlexNet, VGG19, and ResNet50, pretrained on the ImageNet dataset, are considered. These models are further fine-tuned using scalogram images generated through the application of continuous wavelet transform on the vibration signals obtained from spherical roller bearings. This integrated approach for fault detection and diagnosis is presented and validated using the intelligent maintenance systems bearing dataset. The results obtained demonstrate the reliability and efficacy of the proposed approach in accurately detecting and diagnosing bearing faults. Furthermore, the experimental findings indicate that the proposed approach surpasses existing state-of-the-art methods documented in the relevant literature.
{"title":"Exploring a Cutting-Edge Framework for Bearing Fault Detection: A Synergistic Approach Integrating Statistical Analysis and Deep Learning Methods","authors":"Nazanin Siavash-Abkenari;Ghazal Rahmani-Sane;Hossein Torkaman;Ghasem Alipoor","doi":"10.1109/JESTIE.2024.3373313","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3373313","url":null,"abstract":"Bearing condition monitoring in the field of industrial machinery has increasingly relied on the incorporation of artificial intelligence techniques. This article introduces a fault detection and diagnosis methodology for bearing condition monitoring processes, utilizing the Mahalanobis squared distance (MSD). In the initial phase, a health index, namely MSD, is proposed to accurately indicate the health condition of the spherical bearing in an induction motor based on vibration signals. The MSD serves as a preclassification stage, effectively addressing the issue of data overlap and facilitating the identification of distinct data classes, particularly in cases where nonlinear and non-Gaussian data are prevalent. In the subsequent phase, a deep learning (DL)-based approach utilizing transfer learning is employed for the classification of the labeled dataset by MSD. Three established models, namely AlexNet, VGG19, and ResNet50, pretrained on the ImageNet dataset, are considered. These models are further fine-tuned using scalogram images generated through the application of continuous wavelet transform on the vibration signals obtained from spherical roller bearings. This integrated approach for fault detection and diagnosis is presented and validated using the intelligent maintenance systems bearing dataset. The results obtained demonstrate the reliability and efficacy of the proposed approach in accurately detecting and diagnosing bearing faults. Furthermore, the experimental findings indicate that the proposed approach surpasses existing state-of-the-art methods documented in the relevant literature.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 3","pages":"1226-1233"},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141583571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Photovoltaic (PV) emulators are designed to reproduce the exact current-voltage characteristic of a PV module or array in different ambient conditions. PV emulators are essential for power converter testing in PV systems, particularly for grid-tied PV systems, which are among the most paramount inverter-based resources. Certain factors, such as real-time output and simple implementation with high accuracy, should be considered when designing a PV emulator. Conventional PV emulators utilize traditional PV mathematical models and controllers, like the Newton-Raphson (NR) method and PI controllers, respectively. This matter makes a PV emulator unable to reproduce the curve in different conditions because the PI controller is unable to tolerate changing operating points while drastically preserving robust performance with those alterations. Also, NR requires considerable iterations, leading to an intense computational burden. Accordingly, this article proposes a more effective and simple control methodology to optimize the performance of converter-based PV emulators. In this regard, the PV model is based on the single-diode model with five unknown parameters while considering a simple buck converter. This article utilizes the Lambert W method to solve the exponential equation of the PV model, thus changing an “ implicit ” function into an “ explicit ” one. It also reduces the number of iterations; therefore, the computational burden is diminished while maintaining the performance and accuracy of converter-based PV emulators. Also, this article introduces a novel adaptive intelligent fractional-order controller to control converter-based PV emulators. In this strategy, the proposed fuzzy inference system obtains the three coefficients of the controller using Harris hawks optimization and gradient descent algorithm. With an adaptation of the three controller parameters, the performance of the converter-based PV emulator is improved by reducing the tracking error while inducing closed-loop system stability. Comparative simulations and experimental results reveal the effectiveness of the proposed control methodology.
光伏（PV）仿真器旨在再现不同环境条件下光伏模块或阵列的精确电流-电压特性。光伏仿真器对于光伏系统中的功率转换器测试至关重要，特别是对于并网光伏系统，它是最重要的基于逆变器的资源之一。在设计光伏仿真器时，应考虑某些因素，如实时输出和高精度的简单实现。传统的光伏仿真器使用传统的光伏数学模型和控制器，如牛顿-拉斐森（NR）方法和 PI 控制器。这使得光伏仿真器无法再现不同条件下的曲线，因为 PI 控制器无法承受工作点的变化，同时在这些变化中大幅保持稳健的性能。此外，NR 需要大量的迭代，导致计算负担过重。因此，本文提出了一种更有效、更简单的控制方法，以优化基于转换器的光伏仿真器的性能。在这方面，光伏模型基于具有五个未知参数的单二极管模型，同时考虑了简单的降压转换器。本文利用 Lambert W 方法求解光伏模型的指数方程，从而将 "隐式 "函数变为 "显式 "函数。它还减少了迭代次数；因此，在保持基于转换器的光伏仿真器的性能和精度的同时，也减轻了计算负担。此外，本文还介绍了一种新型自适应智能分数阶控制器，用于控制基于转换器的光伏仿真器。在这一策略中，所提出的模糊推理系统利用 Harris Hawks 优化和梯度下降算法获得控制器的三个系数。对三个控制器参数进行调整后，基于转换器的光伏仿真器的性能得到了改善，在诱导闭环系统稳定性的同时减少了跟踪误差。模拟和实验结果的对比显示了所提控制方法的有效性。
{"title":"A Novel Converter-Based PV Emulator Control Using Lambert W Method and Fractional-Order Fuzzy Proportional-Integral Controller Trained by Harris Hawks Optimization for PV Inverter-Based Resources","authors":"Sadegh Esfandiari;Masoud Davari;Weinan Gao;Yongheng Yang;Kamal Al-Haddad","doi":"10.1109/JESTIE.2024.3396140","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3396140","url":null,"abstract":"Photovoltaic (PV) emulators are designed to reproduce the exact current-voltage characteristic of a PV module or array in different ambient conditions. PV emulators are essential for power converter testing in PV systems, particularly for grid-tied PV systems, which are among the most paramount inverter-based resources. Certain factors, such as real-time output and simple implementation with high accuracy, should be considered when designing a PV emulator. Conventional PV emulators utilize traditional PV mathematical models and controllers, like the Newton-Raphson (NR) method and PI controllers, respectively. This matter makes a PV emulator unable to reproduce the curve in different conditions because the PI controller is unable to tolerate changing operating points while drastically preserving robust performance with those alterations. Also, NR requires considerable iterations, leading to an intense computational burden. Accordingly, this article proposes a more effective and simple control methodology to optimize the performance of converter-based PV emulators. In this regard, the PV model is based on the single-diode model with five unknown parameters while considering a simple buck converter. This article utilizes the Lambert \u0000<italic>W</i>\u0000 method to solve the exponential equation of the PV model, thus changing an “\u0000<italic>implicit</i>\u0000” function into an “\u0000<italic>explicit</i>\u0000” one. It also reduces the number of iterations; therefore, the computational burden is diminished while maintaining the performance and accuracy of converter-based PV emulators. Also, this article introduces a novel adaptive intelligent fractional-order controller to control converter-based PV emulators. In this strategy, the proposed fuzzy inference system obtains the three coefficients of the controller using Harris hawks optimization and gradient descent algorithm. With an adaptation of the three controller parameters, the performance of the converter-based PV emulator is improved by reducing the tracking error while inducing closed-loop system stability. Comparative simulations and experimental results reveal the effectiveness of the proposed control methodology.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1493-1507"},"PeriodicalIF":0.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/JESTIE.2024.3395650
Hadi Ashraf Raja;Karolina Kudelina;Bilal Asad;Toomas Vaimann;Anton Rassõlkin;Ants Kallaste
The industrial revolution has opened up more paths with the integration of information technology with industrial applications. Similarly, most industrial processes can be streamlined by combining the Internet of Things and artificial intelligence. Artificial intelligence has a significant role in this development, whether it is related to real-time condition monitoring of electrical machines or switching of the industry from scheduled maintenance to predictive maintenance. One of the main challenges for artificial intelligence is the quality and quantity of data used for training models, as it requires big datasets to train more accurate and efficient models. This article presents a data acquisition system with real-time condition monitoring of electrical machines. A comparison between trained models from real signals and synthetic signals, generated through the equation, is also covered in this article. This is to help identify whether utilizing synthetic signals for the training of fault diagnostics models can be a good alternative in the long run or not.
{"title":"Development and Utilization of Synthetic Signals for Fault Diagnostics of Electrical Machines","authors":"Hadi Ashraf Raja;Karolina Kudelina;Bilal Asad;Toomas Vaimann;Anton Rassõlkin;Ants Kallaste","doi":"10.1109/JESTIE.2024.3395650","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3395650","url":null,"abstract":"The industrial revolution has opened up more paths with the integration of information technology with industrial applications. Similarly, most industrial processes can be streamlined by combining the Internet of Things and artificial intelligence. Artificial intelligence has a significant role in this development, whether it is related to real-time condition monitoring of electrical machines or switching of the industry from scheduled maintenance to predictive maintenance. One of the main challenges for artificial intelligence is the quality and quantity of data used for training models, as it requires big datasets to train more accurate and efficient models. This article presents a data acquisition system with real-time condition monitoring of electrical machines. A comparison between trained models from real signals and synthetic signals, generated through the equation, is also covered in this article. This is to help identify whether utilizing synthetic signals for the training of fault diagnostics models can be a good alternative in the long run or not.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1447-1454"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-28DOI: 10.1109/JESTIE.2024.3371350
Rahul Patil;Saravana Prakash P
This research proposes a bridgeless (BL) Cuk converter cell derived power factor correction (PFC) voltage doubler rectifier (VDR). The proposed BL-PFC VDR employs two Cuk converter cells. The inputs of Cuk cells are connected in parallel, and the outputs are connected in series. Thus, makes the voltage gain twice. Compared to a classical Boost BL-PFC rectifier, the proposed rectifier either lowers the voltage burden on the switches or twice the output voltage gain. Since each Cuk cell works for a alternative half cycle, this VDR provides better thermal management. The proposed Cuk VDR employs an affordable single voltage sensor-based voltage control method. Further, the rectifier is intended to operate in discontinuous inductor current mode for improved power quality operation. In addition, the steady-state analysis of the proposed Cuk VDR, as well as its design, and small signal analysis are detailed thoroughly. A 1-kW experimental prototype is developed to validate the performance of proposed Cuk VDR. Furthermore, its effectiveness has been validated using analytical outcomes.
{"title":"A Bridgeless Cuk-Derived Voltage Doubler-Based Power Factor Correction Rectifier","authors":"Rahul Patil;Saravana Prakash P","doi":"10.1109/JESTIE.2024.3371350","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3371350","url":null,"abstract":"This research proposes a bridgeless (BL) Cuk converter cell derived power factor correction (PFC) voltage doubler rectifier (VDR). The proposed BL-PFC VDR employs two Cuk converter cells. The inputs of Cuk cells are connected in parallel, and the outputs are connected in series. Thus, makes the voltage gain twice. Compared to a classical Boost BL-PFC rectifier, the proposed rectifier either lowers the voltage burden on the switches or twice the output voltage gain. Since each Cuk cell works for a alternative half cycle, this VDR provides better thermal management. The proposed Cuk VDR employs an affordable single voltage sensor-based voltage control method. Further, the rectifier is intended to operate in discontinuous inductor current mode for improved power quality operation. In addition, the steady-state analysis of the proposed Cuk VDR, as well as its design, and small signal analysis are detailed thoroughly. A 1-kW experimental prototype is developed to validate the performance of proposed Cuk VDR. Furthermore, its effectiveness has been validated using analytical outcomes.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 3","pages":"985-993"},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141561035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1109/JESTIE.2024.3370531
Anil Jakhar;N. Sandeep;Arun Kumar Verma
Transformerless multilevel inverters with boosting features are widely used in residential and commercial photovoltaic applications due to their advantages, such as compact size, low cost, high voltage gain, and higher efficiency. However, they suffer from ground leakage current, which degrades power quality and poses safety issues. In this article, a nine-level quadruple-boost inverter with common ground is proposed using the concept of switched capacitor (SC). Due to the common ground, the proposed topology eliminates the leakage current. The voltages of SC are self-balancing without the need for external dedicated circuits or sensors. The operating principle of the proposed topology is described in detail, followed by the design guidelines for sizing SC. The comparative summary highlights the advantageous features of the proposed topology, including fewer components, high gain, self-balancing capability of SCs, lower conduction and switching losses, and near-zero leakage current. In addition, through a detailed volume and cost-based comparison, it will be shown that the proposed topology has the lowest volume (278.95 cm $^{3}$ ) and cost (114.81 $) amongst its counterparts. Further, the performance of the proposed topology is validated through several experiments on a 1 kW laboratory prototype, and the results are presented for grid-connected and stand-alone modes.
{"title":"Common-Ground-Type Quadruple Boosting Nine-Level Inverter","authors":"Anil Jakhar;N. Sandeep;Arun Kumar Verma","doi":"10.1109/JESTIE.2024.3370531","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3370531","url":null,"abstract":"Transformerless multilevel inverters with boosting features are widely used in residential and commercial photovoltaic applications due to their advantages, such as compact size, low cost, high voltage gain, and higher efficiency. However, they suffer from ground leakage current, which degrades power quality and poses safety issues. In this article, a nine-level quadruple-boost inverter with common ground is proposed using the concept of switched capacitor (SC). Due to the common ground, the proposed topology eliminates the leakage current. The voltages of SC are self-balancing without the need for external dedicated circuits or sensors. The operating principle of the proposed topology is described in detail, followed by the design guidelines for sizing SC. The comparative summary highlights the advantageous features of the proposed topology, including fewer components, high gain, self-balancing capability of SCs, lower conduction and switching losses, and near-zero leakage current. In addition, through a detailed volume and cost-based comparison, it will be shown that the proposed topology has the lowest volume (278.95 cm\u0000<inline-formula><tex-math>$^{3}$</tex-math></inline-formula>\u0000) and cost (114.81 $) amongst its counterparts. Further, the performance of the proposed topology is validated through several experiments on a 1 kW laboratory prototype, and the results are presented for grid-connected and stand-alone modes.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1593-1600"},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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