Pub Date : 2024-07-11DOI: 10.1109/JESTIE.2024.3426494
Xiaohong Ran;Bo Xu;Kaipei Liu;Yangsheng Liu
The previous studies examined the relationship between traditional complex power (TCP) and extended complex power (ECP)-based direct power controls (DPCs). A novel complex power (NCP) is modeled, and we then study the relationship between the NCP and existing complex powers. The frameworks of TCP-, ECP-, and NCP-based model predictive DPC (MPDPC) are established and studied using mathematical models and tools. Under slightly unbalanced grid voltages, we perform a comparative analysis of the above three methods. The inherent equivalence or relationship between the three methods is described in terms of power variations. Under extremely unbalanced grids, the existing TCP- and ECP-based MPDPCs cannot work well, resulting in nonsinusoidal grid currents and larger power ripples. However, the NCP-MPDPC achieves the better steady-state performance. To reveal their inherent relationships, we conduct a comparative study from their output reference voltages. Finally, we are stimulated to design an NCP-based MPDPC. The MPDPC method is realized by selecting one extended active vector and a zero vector. The duty cycles of all voltage vectors are redesigned to achieve sinusoidal grid current and minimize total harmonic distortion (THD). Both the simulations and experiments validate the effectiveness of their inherent relationships of three methods.
{"title":"Relationship and Comparative Analysis of Three Complex Power Vectors-Based Model Predictive Control Under Unbalanced Networks","authors":"Xiaohong Ran;Bo Xu;Kaipei Liu;Yangsheng Liu","doi":"10.1109/JESTIE.2024.3426494","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3426494","url":null,"abstract":"The previous studies examined the relationship between traditional complex power (TCP) and extended complex power (ECP)-based direct power controls (DPCs). A novel complex power (NCP) is modeled, and we then study the relationship between the NCP and existing complex powers. The frameworks of TCP-, ECP-, and NCP-based model predictive DPC (MPDPC) are established and studied using mathematical models and tools. Under slightly unbalanced grid voltages, we perform a comparative analysis of the above three methods. The inherent equivalence or relationship between the three methods is described in terms of power variations. Under extremely unbalanced grids, the existing TCP- and ECP-based MPDPCs cannot work well, resulting in nonsinusoidal grid currents and larger power ripples. However, the NCP-MPDPC achieves the better steady-state performance. To reveal their inherent relationships, we conduct a comparative study from their output reference voltages. Finally, we are stimulated to design an NCP-based MPDPC. The MPDPC method is realized by selecting one extended active vector and a zero vector. The duty cycles of all voltage vectors are redesigned to achieve sinusoidal grid current and minimize total harmonic distortion (THD). Both the simulations and experiments validate the effectiveness of their inherent relationships of three methods.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"6 1","pages":"338-349"},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905871","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 : 2024-07-10DOI: 10.1109/JESTIE.2024.3426034
Daiki Sodenaga;Issei Takeuchi;Daswin De Silva;Seiichiro Katsura
There are two main contributions in this article. One of them is to have generated the interpretable model about the relationship between sEMG and force. The other is to have conducted on estimating force from sEMG with the same level accuracy as the conventional method. As the above, we proposed the effective modeling method to estimate the human force from surface-electromyography (sEMG) in this article. A sEMG is one of the human biological signal and it indicates muscle contractions. In the conventional research, the force estimation from sEMG has been conducted. However, the calculation process between sEMG and force is unclear because those methods are the machine learning such as the DNN, etc. From the above, it could not be considered about the relationship between input and output based on the model. Then, we proposed the element description method (EDM) which can generate the model whose calculation process is not black box for the force estimation from sEMG in this article. We compared the conventional method (DNN) with the EDM in this article. As the result, the root mean square error with an EDM was same degree with the DNN. Moreover, the model with an EDM was more effective than the DNN because the calculating process of the model by an EDM was interpretable. From the above, we could show the effectiveness of the proposed method in this article.
{"title":"Force Estimation From Surface-EMG Using Element Description Method","authors":"Daiki Sodenaga;Issei Takeuchi;Daswin De Silva;Seiichiro Katsura","doi":"10.1109/JESTIE.2024.3426034","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3426034","url":null,"abstract":"There are two main contributions in this article. One of them is to have generated the interpretable model about the relationship between sEMG and force. The other is to have conducted on estimating force from sEMG with the same level accuracy as the conventional method. As the above, we proposed the effective modeling method to estimate the human force from surface-electromyography (sEMG) in this article. A sEMG is one of the human biological signal and it indicates muscle contractions. In the conventional research, the force estimation from sEMG has been conducted. However, the calculation process between sEMG and force is unclear because those methods are the machine learning such as the DNN, etc. From the above, it could not be considered about the relationship between input and output based on the model. Then, we proposed the element description method (EDM) which can generate the model whose calculation process is not black box for the force estimation from sEMG in this article. We compared the conventional method (DNN) with the EDM in this article. As the result, the root mean square error with an EDM was same degree with the DNN. Moreover, the model with an EDM was more effective than the DNN because the calculating process of the model by an EDM was interpretable. From the above, we could show the effectiveness of the proposed method in this article.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"6 1","pages":"447-454"},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905774","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 : 2024-07-09DOI: 10.1109/JESTIE.2024.3425670
Soumya Ranjan Biswal;Tanmoy Roy Choudhury;Subhendu Bikash Santra;Babita Panda;Subhrajyoti Mishra;Sanjeevikumar Padmanaban
Automated greenhouse is essential for sustainable development and food security. Photovoltaic (PV) power with physical sensors-based control using Internet of Things needs high initial investment and operational cost. This also needs significant installed storage capacity. In the proposed solution, the dependency on physical sensors like temperature, humidity, soil moisture sensors, etc., are eliminated due to the application of eXtreme Gradient Boosting-based machine learning (ML) algorithm. The training and testing of ML algorithm are performed with one-year physical data (approx. 50k @10 min interval) from greenhouse which provides accurate mapping (Temperature MAPE: 1.51%, R 2 : 0.9785 and Humidity MAPE: 1.68%, R 2 : 0.9867) between predicted and sensor data. Also, a novel priority-based demand side management scheme is implemented which includes load shifting which reduces the requirement of installed PV and storage capacity. A reduction of 63.27% storage capacity is possible with proposed control approach. ML algorithm is programmed using Python language and implemented in Raspberry Pi-3B+ SBC. For physical verification of the proposed control unit, a laboratory-based prototype is developed with PV emulator (1.5 kW), programmable electronic load box, and relay unit controlled through Arduino UNO, Raspberry Pi-3B+ SBC, ESP-32 Combo unit.
{"title":"Simplified Prediction-Based AI-IoT Model for Energy Management Scheme in Standalone PV Powered Greenhouse","authors":"Soumya Ranjan Biswal;Tanmoy Roy Choudhury;Subhendu Bikash Santra;Babita Panda;Subhrajyoti Mishra;Sanjeevikumar Padmanaban","doi":"10.1109/JESTIE.2024.3425670","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3425670","url":null,"abstract":"Automated greenhouse is essential for sustainable development and food security. Photovoltaic (PV) power with physical sensors-based control using Internet of Things needs high initial investment and operational cost. This also needs significant installed storage capacity. In the proposed solution, the dependency on physical sensors like temperature, humidity, soil moisture sensors, etc., are eliminated due to the application of eXtreme Gradient Boosting-based machine learning (ML) algorithm. The training and testing of ML algorithm are performed with one-year physical data (approx. 50k @10 min interval) from greenhouse which provides accurate mapping (Temperature MAPE: 1.51%, \u0000<italic>R</i>\u0000<sup>2</sup>\u0000: 0.9785 and Humidity MAPE: 1.68%, \u0000<italic>R</i>\u0000<sup>2</sup>\u0000: 0.9867) between predicted and sensor data. Also, a novel priority-based demand side management scheme is implemented which includes load shifting which reduces the requirement of installed PV and storage capacity. A reduction of 63.27% storage capacity is possible with proposed control approach. ML algorithm is programmed using Python language and implemented in Raspberry Pi-3B+ SBC. For physical verification of the proposed control unit, a laboratory-based prototype is developed with PV emulator (1.5 kW), programmable electronic load box, and relay unit controlled through Arduino UNO, Raspberry Pi-3B+ SBC, ESP-32 Combo unit.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"6 1","pages":"224-237"},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905800","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 : 2024-07-09DOI: 10.1109/JESTIE.2024.3425518
Marco Guerreiro;Pedro dos Santos;Steven Liu
Grid-forming converters in dc microgrids will have a key role in the next generation power system. These converters are responsible for stabilizing the bus voltage in a grid dominated by constant power loads, a task that requires highly dynamic voltage control loops. This article presents an energy-based method to control the output voltage of an isolated Ćuk converter, a high-order nonlinear system. The main motivation behind the energy-based method is to control the total energy of the converter. In many cases, most of the energy is stored in the output capacitor of the converter, and controlling total energy allows shaping the output voltage directly. By using feedback linearization, we show that it is possible to use a linear controller to control energy, and that the internal dynamics resulting from feedback linearization is stable. The energy-based method results in a single-loop controller capable of naturally handling constant power loads, characteristics that make it well suited for voltage control of grid-forming converters. The proposed controller is verified by experimental results, using an isolated Ćuk converter to supply a constant power load.
{"title":"Voltage Control of the Ćuk Converter for Grid-Forming in DC Grids: An Energy-Based Approach","authors":"Marco Guerreiro;Pedro dos Santos;Steven Liu","doi":"10.1109/JESTIE.2024.3425518","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3425518","url":null,"abstract":"Grid-forming converters in dc microgrids will have a key role in the next generation power system. These converters are responsible for stabilizing the bus voltage in a grid dominated by constant power loads, a task that requires highly dynamic voltage control loops. This article presents an energy-based method to control the output voltage of an isolated Ćuk converter, a high-order nonlinear system. The main motivation behind the energy-based method is to control the total energy of the converter. In many cases, most of the energy is stored in the output capacitor of the converter, and controlling total energy allows shaping the output voltage directly. By using feedback linearization, we show that it is possible to use a linear controller to control energy, and that the internal dynamics resulting from feedback linearization is stable. The energy-based method results in a single-loop controller capable of naturally handling constant power loads, characteristics that make it well suited for voltage control of grid-forming converters. The proposed controller is verified by experimental results, using an isolated Ćuk converter to supply a constant power load.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1388-1395"},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438515","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}
Class-E inverters are widely used in high-frequency power conversion applications, and impedance matching networks are commonly used to match various loads to the given drain-source impedance required for class E inverter. However, due to the influence of the stray parameters in high-frequency circuit, fast and accurate design of the impedance matching network is still challenging. In this article, a design method of impedance matching network for cascaded class E inverters is proposed. The impedance matching network design method presented in this article prioritizes the design of the filter network to meet the waveform quality requirements, then adjusts the real part of the impedance using shunt capacitors, and finally adjusts the imaginary part of the impedance using an LC series circuit. In the driver circuit, the gate-source impedance including parasitic parameters of the main circuit switch is extracted to accomplish impedance matching. The correctness and effectiveness of the proposed scheme is verified by a 13.56 MHz, 5 kW experimental prototype, and experimental waveforms show good impedance matching and high output waveform quality.
{"title":"Design Method of Impedance Matching Network for High Power Cascaded Class-E Inverter","authors":"Hui Wang;Chen Chen;Lifang Ha;Shiming Xie;Guangfu Ning;Mei Su;Xinyan Huang","doi":"10.1109/JESTIE.2024.3425750","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3425750","url":null,"abstract":"Class-E inverters are widely used in high-frequency power conversion applications, and impedance matching networks are commonly used to match various loads to the given drain-source impedance required for class E inverter. However, due to the influence of the stray parameters in high-frequency circuit, fast and accurate design of the impedance matching network is still challenging. In this article, a design method of impedance matching network for cascaded class E inverters is proposed. The impedance matching network design method presented in this article prioritizes the design of the filter network to meet the waveform quality requirements, then adjusts the real part of the impedance using shunt capacitors, and finally adjusts the imaginary part of the impedance using an \u0000<italic>LC</i>\u0000 series circuit. In the driver circuit, the gate-source impedance including parasitic parameters of the main circuit switch is extracted to accomplish impedance matching. The correctness and effectiveness of the proposed scheme is verified by a 13.56 MHz, 5 kW experimental prototype, and experimental waveforms show good impedance matching and high output waveform quality.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"6 1","pages":"327-337"},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905945","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 : 2024-07-08DOI: 10.1109/JESTIE.2024.3419636
{"title":"Officers and Vice Presidents of Co-Sponsoring Societies Information","authors":"","doi":"10.1109/JESTIE.2024.3419636","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3419636","url":null,"abstract":"","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 3","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10588999","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141618098","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}
Pub Date : 2024-07-08DOI: 10.1109/JESTIE.2024.3419638
{"title":"IEEE Industrial Electronics Society Information","authors":"","doi":"10.1109/JESTIE.2024.3419638","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3419638","url":null,"abstract":"","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 3","pages":"C4-C4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10589000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141618060","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}
Pub Date : 2024-07-08DOI: 10.1109/JESTIE.2024.3419634
{"title":"Journal of Emerging and Selected Topics in Industrial Electronics Publication Information","authors":"","doi":"10.1109/JESTIE.2024.3419634","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3419634","url":null,"abstract":"","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 3","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10588991","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141560962","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}
Dynamic wireless power transfer using repeater coils is studied as a cost-effective method that allows a single inverter to supply power to multiple transmitter coils. However, this method has a zone where the receiver coil positions on a transmitter coil called a dead zone. In the dead zone, the transfer efficiency and received power are significantly reduced. This is caused by matching the series resonance frequencies of each closed-loop circuit with the operating frequency of the inverter. Therefore, this article proposes the operating frequency control of the inverter to improve the power factor, which increases the efficiency and received power. The angle difference between the inverter output voltage and current is measured, and the operating frequency is controlled using a proportional–integral controller so that the angle difference becomes 0. From the experimental results, it was confirmed that the efficiency is 0.90 and the received power increases by $text{1.33} ,text{kW}$ when the operating frequency in the dead zone is not fixed compared to when it was fixed. In addition, the settling time of the operating frequency and angle difference was compared between the hill climbing algorithm and the proportional–integral controller. The settling time decreased by $text{2.9} ,text{ms}$ .
{"title":"Feedback Operating Frequency Control for Eliminating Dead Zone in Dynamic Wireless Power Transfer","authors":"Yutaka Shikauchi;Ryo Matsumoto;Sakahisa Nagai;Toshiyuki Fujita;Osamu Shimizu;Hiroshi Fujimoto","doi":"10.1109/JESTIE.2024.3420121","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3420121","url":null,"abstract":"Dynamic wireless power transfer using repeater coils is studied as a cost-effective method that allows a single inverter to supply power to multiple transmitter coils. However, this method has a zone where the receiver coil positions on a transmitter coil called a dead zone. In the dead zone, the transfer efficiency and received power are significantly reduced. This is caused by matching the series resonance frequencies of each closed-loop circuit with the operating frequency of the inverter. Therefore, this article proposes the operating frequency control of the inverter to improve the power factor, which increases the efficiency and received power. The angle difference between the inverter output voltage and current is measured, and the operating frequency is controlled using a proportional–integral controller so that the angle difference becomes 0. From the experimental results, it was confirmed that the efficiency is 0.90 and the received power increases by \u0000<inline-formula><tex-math>$text{1.33} ,text{kW}$</tex-math></inline-formula>\u0000 when the operating frequency in the dead zone is not fixed compared to when it was fixed. In addition, the settling time of the operating frequency and angle difference was compared between the hill climbing algorithm and the proportional–integral controller. The settling time decreased by \u0000<inline-formula><tex-math>$text{2.9} ,text{ms}$</tex-math></inline-formula>\u0000.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"6 1","pages":"53-61"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905771","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 article presents a novel method to suppress high-frequency oscillations (HFOs) in voltage-source converters (VSCs) based high-voltage direct current (HVDC) systems. The analysis reveals that the main reason for HFOs is the negative damping of the VSC-HVDC impedance at high frequencies, which results from the time delay of the control system. The proposed method employs a Smith predictor to directly compensate for the time delay of the VSC-HVDC control system and eliminate the HFOs. The article first reviews the instability mechanism of VSC-HVDC systems. Then, it presents the Smith-predictor-based control method for HFO suppression and evaluates its robustness. Finally, the proposed method and theoretical analysis are verified by simulation and hardware-in-the-loop tests results.
{"title":"A Smith Predictor Based High-Frequency Oscillation Suppression Method for VSC-HVDC System","authors":"Siqi Liu;Pengfei Hu;Yiqi Liu;Naixuan Zhu;Yanxue Yu;Daozhuo Jiang","doi":"10.1109/JESTIE.2024.3418215","DOIUrl":"https://doi.org/10.1109/JESTIE.2024.3418215","url":null,"abstract":"This article presents a novel method to suppress high-frequency oscillations (HFOs) in voltage-source converters (VSCs) based high-voltage direct current (HVDC) systems. The analysis reveals that the main reason for HFOs is the negative damping of the VSC-HVDC impedance at high frequencies, which results from the time delay of the control system. The proposed method employs a Smith predictor to directly compensate for the time delay of the VSC-HVDC control system and eliminate the HFOs. The article first reviews the instability mechanism of VSC-HVDC systems. Then, it presents the Smith-predictor-based control method for HFO suppression and evaluates its robustness. Finally, the proposed method and theoretical analysis are verified by simulation and hardware-in-the-loop tests results.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1572-1581"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438614","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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