Pub Date : 2025-10-09DOI: 10.1109/OJIA.2025.3619763
Komal Khan;Islam El-Sayed;Pablo Arboleya
Fast-growing distributed energy resources, prosumers, and electric vehicles risk overloading the grid and would require costly infrastructure expansion. In this respect, local energy markets seem to be a promising solution that enables the participation of prosumers and consumers in peer-to-peer energy transactions. However, most existing solutions require substantial computational resources and detailed real-time data, limiting practical deployment on edge devices and in large-scale environments. Conventional negotiation frameworks are mainly synchronous and prepaid, lacking lightweight, scalable, postpaid, and concurrent negotiation protocols to streamline transactions and minimize communication overhead. To address these gaps, we present an advanced three-stage multiagent model for peer-to-peer energy trading within the context of local energy markets, designed for simplicity and ease of integration in resource-constrained settings. This model is strategically engineered to optimize market participation and grid support by orchestrating a one-to-many concurrent composite negotiation strategy that supports postpaid transactions. Empowered by the smart Python multiagent development environment, which harnesses the instant extensible messaging and presence communication protocol, our model ensures seamless execution of peer-to-peer energy transactions with minimal computational burden. Furthermore, the methodology presented is extremely simple and generic compared to other procedures in the literature, facilitating scalable implementation on edge devices and supporting wide real-world adoption.
{"title":"A Multiagent Framework Coordinating One-to-Many Concurrent Composite Negotiations in a Multistage Postpaid P2P Energy Trading Model","authors":"Komal Khan;Islam El-Sayed;Pablo Arboleya","doi":"10.1109/OJIA.2025.3619763","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3619763","url":null,"abstract":"Fast-growing distributed energy resources, prosumers, and electric vehicles risk overloading the grid and would require costly infrastructure expansion. In this respect, local energy markets seem to be a promising solution that enables the participation of prosumers and consumers in peer-to-peer energy transactions. However, most existing solutions require substantial computational resources and detailed real-time data, limiting practical deployment on edge devices and in large-scale environments. Conventional negotiation frameworks are mainly synchronous and prepaid, lacking lightweight, scalable, postpaid, and concurrent negotiation protocols to streamline transactions and minimize communication overhead. To address these gaps, we present an advanced three-stage multiagent model for peer-to-peer energy trading within the context of local energy markets, designed for simplicity and ease of integration in resource-constrained settings. This model is strategically engineered to optimize market participation and grid support by orchestrating a one-to-many concurrent composite negotiation strategy that supports postpaid transactions. Empowered by the smart Python multiagent development environment, which harnesses the instant extensible messaging and presence communication protocol, our model ensures seamless execution of peer-to-peer energy transactions with minimal computational burden. Furthermore, the methodology presented is extremely simple and generic compared to other procedures in the literature, facilitating scalable implementation on edge devices and supporting wide real-world adoption.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"717-727"},"PeriodicalIF":3.3,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11197908","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455751","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 : 2025-10-06DOI: 10.1109/OJIA.2025.3618191
Kaif Ahmed Lodi;Khaled Ali Al Jaafari;Abdul R. Beig
This article presents an improved duty-ratio-based direct torque control (Duty-DTC) scheme for open-end winding induction motor (OEWIM) drives. Unlike conventional DTC (CDTC), which applies a single voltage vector over the entire sampling interval, the proposed method adjusts the duty ratio of the active voltage vector based on the instantaneous torque error. A computationally efficient and robust algorithm is developed to determine the optimal duty ratio, achieving reductions in torque ripple, flux ripple, and switching frequency variations while preserving the transient response of CDTC. A torque reference compensation method is introduced to mitigate the steady-state torque error caused by variations in motor speed. A novel switching state optimization method is used, in which the dwell time of the zero-voltage vector is split into two equal intervals and the active voltage vector is placed at the center of the switching interval, further improving the steady-state error and ripples. The proposed Duty-DTC algorithm is verified experimentally under various operating conditions using a 5-kW OEWIM drive laboratory prototype. The experimental results show that the proposed algorithm achieves 2.41%, 3.8%, and 4.5% torque ripple at 60 r/min, 720 r/min, and 1440 r/min, respectively, demonstrating the effectiveness of the proposed Duty-DTC in reducing torque ripples. The comparative results demonstrate a 85% reduction in torque ripple without an increase in computational time and complexity compared to CDTC. The results also show that the proposed algorithm achieves performance comparable to that of artificial neural network-based Duty-DTC algorithms, but with reduced computational time and complexity.
{"title":"Improved Duty Ratio-Based Direct Torque Control for Open-End Winding Induction Motor Drives","authors":"Kaif Ahmed Lodi;Khaled Ali Al Jaafari;Abdul R. Beig","doi":"10.1109/OJIA.2025.3618191","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3618191","url":null,"abstract":"This article presents an improved duty-ratio-based direct torque control (Duty-DTC) scheme for open-end winding induction motor (OEWIM) drives. Unlike conventional DTC (CDTC), which applies a single voltage vector over the entire sampling interval, the proposed method adjusts the duty ratio of the active voltage vector based on the instantaneous torque error. A computationally efficient and robust algorithm is developed to determine the optimal duty ratio, achieving reductions in torque ripple, flux ripple, and switching frequency variations while preserving the transient response of CDTC. A torque reference compensation method is introduced to mitigate the steady-state torque error caused by variations in motor speed. A novel switching state optimization method is used, in which the dwell time of the zero-voltage vector is split into two equal intervals and the active voltage vector is placed at the center of the switching interval, further improving the steady-state error and ripples. The proposed Duty-DTC algorithm is verified experimentally under various operating conditions using a 5-kW OEWIM drive laboratory prototype. The experimental results show that the proposed algorithm achieves 2.41%, 3.8%, and 4.5% torque ripple at 60 r/min, 720 r/min, and 1440 r/min, respectively, demonstrating the effectiveness of the proposed Duty-DTC in reducing torque ripples. The comparative results demonstrate a 85% reduction in torque ripple without an increase in computational time and complexity compared to CDTC. The results also show that the proposed algorithm achieves performance comparable to that of artificial neural network-based Duty-DTC algorithms, but with reduced computational time and complexity.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"703-716"},"PeriodicalIF":3.3,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11193708","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145352049","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 : 2025-10-01DOI: 10.1109/OJIA.2025.3616287
Nicolaus Jennings;David Wetz;Alexander Johnston;Rick Langley;Nancy LaFlair;John Heinzel
Many civilian and defense applications are either considering or actively incorporating 1000 V electrochemical energy sources into their power systems for a multitude of uses. It is well known that lithium-ion batteries can introduce significant safety challenges, but the risk is most often worth the reward. In addition to the shock hazard that comes with high operational voltages, the potential danger to workers from arc flash hazard—intense heat, bright (blinding) light, and loud (deafening) sound—also exists, and it is not well documented from dc sources. As batteries become more attractive for use across industry, the risks posed by these sources drives a need to study the arc flash phenomena produced at application-relevant potentials. Consequently, the Electric Power Research Institute (EPRI) and the University of Texas at Arlington (UTA) have performed 91 arc flash experiments with battery sources at voltages roughly 1000 Vdc. Data collected from these experiments are the first comprehensive experimental analysis of dc arc flash phenomena from 1000 V lithium-ion battery systems, revealing previously unreported nonthermal hazards and overestimations from models typically employed. Two lithium-ion chemistries have been studied, Lithium Iron Phosphate (LFP) and Lithium Titanate (LTO). LFP modules studied previously at 540 V produced incident energies as high as 6.12 cal/cm2 from an arc lasting 2.39 s with a gap distance of 0.25 in. At 908 V, the same LFPs exhibited upward of 4.48 cal/cm2 from a 0.5 in gap distance tests that had to be manually cut off. LTOs at 730 V produced 2.16 cal/cm2 for an arc lasting 0.88 s at a gap distance of 0.5 in. The light and sound intensity studied in some tests indicates the necessity for workers to use hearing and vision precautions. Models developed through this research and two relevant models from literature have been used to evaluate overestimations and their effectiveness at predicting the incident energy for arc flash events sourced from lithium-ion batteries.
{"title":"Study of DC Arc Flash Phenomenon From 1000 V Lithium Ion Battery Systems","authors":"Nicolaus Jennings;David Wetz;Alexander Johnston;Rick Langley;Nancy LaFlair;John Heinzel","doi":"10.1109/OJIA.2025.3616287","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3616287","url":null,"abstract":"Many civilian and defense applications are either considering or actively incorporating 1000 V electrochemical energy sources into their power systems for a multitude of uses. It is well known that lithium-ion batteries can introduce significant safety challenges, but the risk is most often worth the reward. In addition to the shock hazard that comes with high operational voltages, the potential danger to workers from arc flash hazard—intense heat, bright (blinding) light, and loud (deafening) sound—also exists, and it is not well documented from dc sources. As batteries become more attractive for use across industry, the risks posed by these sources drives a need to study the arc flash phenomena produced at application-relevant potentials. Consequently, the Electric Power Research Institute (EPRI) and the University of Texas at Arlington (UTA) have performed 91 arc flash experiments with battery sources at voltages roughly 1000 V<sub>dc</sub>. Data collected from these experiments are the first comprehensive experimental analysis of dc arc flash phenomena from 1000 V lithium-ion battery systems, revealing previously unreported nonthermal hazards and overestimations from models typically employed. Two lithium-ion chemistries have been studied, Lithium Iron Phosphate (LFP) and Lithium Titanate (LTO). LFP modules studied previously at 540 V produced incident energies as high as 6.12 cal/cm<sup>2</sup> from an arc lasting 2.39 s with a gap distance of 0.25 in. At 908 V, the same LFPs exhibited upward of 4.48 cal/cm<sup>2</sup> from a 0.5 in gap distance tests that had to be manually cut off. LTOs at 730 V produced 2.16 cal/cm<sup>2</sup> for an arc lasting 0.88 s at a gap distance of 0.5 in. The light and sound intensity studied in some tests indicates the necessity for workers to use hearing and vision precautions. Models developed through this research and two relevant models from literature have been used to evaluate overestimations and their effectiveness at predicting the incident energy for arc flash events sourced from lithium-ion batteries.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"689-702"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11185300","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145315369","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 : 2025-09-08DOI: 10.1109/OJIA.2025.3607115
Zbigniew Gmyrek;Federica Graffeo;Silvio Vaschetto;Andrea Cavagnino
The article addresses the challenge of determining the individual components of ferromagnetic losses within the generally accepted three-component loss model. It carefully examines variations in each loss contribution caused by the varying proportion of material whose characteristics have been altered by the cutting process. Special emphasis is given to the approach for calculating eddy current losses, which are highly dependent on the proportion of damaged material. Additionally, the article investigates the dependence of excess losses on frequency. In this context, the applicability of known analytical formulas for determining eddy current losses and excess losses is discussed. The merit of this article is the accuracy of mapping the measurement results using the proposed methodology.
{"title":"Measurements and Modeling of Iron Losses in Guillotine and Laser Cut Soft-Magnetic Sheets","authors":"Zbigniew Gmyrek;Federica Graffeo;Silvio Vaschetto;Andrea Cavagnino","doi":"10.1109/OJIA.2025.3607115","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3607115","url":null,"abstract":"The article addresses the challenge of determining the individual components of ferromagnetic losses within the generally accepted three-component loss model. It carefully examines variations in each loss contribution caused by the varying proportion of material whose characteristics have been altered by the cutting process. Special emphasis is given to the approach for calculating eddy current losses, which are highly dependent on the proportion of damaged material. Additionally, the article investigates the dependence of excess losses on frequency. In this context, the applicability of known analytical formulas for determining eddy current losses and excess losses is discussed. The merit of this article is the accuracy of mapping the measurement results using the proposed methodology.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"663-675"},"PeriodicalIF":3.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11153435","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145141782","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 : 2025-09-02DOI: 10.1109/OJIA.2025.3605167
Balram Kumar;Sankar Peddapati;Waleed Alhosaini
In this work, a multilevel inverter with the feature of single and multiswitch fault-tolerant capability is proposed for ensuring uninterrupted power supply in emergency load applications. By integrating a redundant unit into the multilevel inverter, the converter tolerates faults effectively in both symmetrical and asymmetrical voltage modes. To demonstrate the converter’s robust performance, experimental validation on a 500 W prototype is done under various faulty and dynamic conditions. Additionally, the article includes the reliability and efficiency analysis of the proposed converter. Furthermore, a new parameter is introduced in this work to evaluate the fault-tolerant capability of the converter topologies, offering deeper insights into its reliability. A comparative analysis is finally presented to emphasize the advantages of the proposed topology in terms of various performance matrices.
{"title":"A Novel Fault-Tolerant Single-Phase Multilevel Inverter for Reliable UPS Applications","authors":"Balram Kumar;Sankar Peddapati;Waleed Alhosaini","doi":"10.1109/OJIA.2025.3605167","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3605167","url":null,"abstract":"In this work, a multilevel inverter with the feature of single and multiswitch fault-tolerant capability is proposed for ensuring uninterrupted power supply in emergency load applications. By integrating a redundant unit into the multilevel inverter, the converter tolerates faults effectively in both symmetrical and asymmetrical voltage modes. To demonstrate the converter’s robust performance, experimental validation on a 500 W prototype is done under various faulty and dynamic conditions. Additionally, the article includes the reliability and efficiency analysis of the proposed converter. Furthermore, a new parameter is introduced in this work to evaluate the fault-tolerant capability of the converter topologies, offering deeper insights into its reliability. A comparative analysis is finally presented to emphasize the advantages of the proposed topology in terms of various performance matrices.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"647-662"},"PeriodicalIF":3.3,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11146677","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110315","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 : 2025-08-13DOI: 10.1109/OJIA.2025.3598640
Umer Amir Khan
High-voltage insulators play a critical role in ensuring the reliability of power transmission systems by preventing flashover under severe environmental conditions. Traditional monitoring techniques rely on visual inspection or static classification schemes, which often fail to capture the progressive nature of surface discharge activity leading to flashover. This article presents a novel machine learning framework that addresses this limitation by classifying leakage current signals into five distinct operational stages: negligible leakage current, leakage current starting, leading to flashover, preflashover, and flashover. This multistage classification approach enables more accurate early warning of impending flashover by identifying subtle changes in leakage current behavior that precede catastrophic insulation failure. Controlled contamination experiments were conducted using porcelain insulators under varying environmental stressors and leakage current data was systematically acquired, segmented, and labeled based on amplitude variations, harmonic distortion, and dry band arcing characteristics. The proposed model, based on inception modules with residual connections, effectively captures multiscale temporal patterns in leakage current signals. Furthermore, posttraining quantization was applied to compress the model for edge deployment, achieving a 91.4% reduction in model size and a 90% decrease in inference time with negligible accuracy loss. Comparative evaluation against conventional neural networks and state-of-the-art ML architectures demonstrated the superior classification accuracy, robustness, and computational efficiency of the proposed framework. This architecture not only facilitates early detection of flashover stages but also enables low-latency, low-power deployment on resource-constrained devices, such as embedded systems, in remote substations.
{"title":"Toward Real-Time Monitoring of High-Voltage Insulators: Progressive Flashover Classification Using Quantized Deep Learning","authors":"Umer Amir Khan","doi":"10.1109/OJIA.2025.3598640","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3598640","url":null,"abstract":"High-voltage insulators play a critical role in ensuring the reliability of power transmission systems by preventing flashover under severe environmental conditions. Traditional monitoring techniques rely on visual inspection or static classification schemes, which often fail to capture the progressive nature of surface discharge activity leading to flashover. This article presents a novel machine learning framework that addresses this limitation by classifying leakage current signals into five distinct operational stages: negligible leakage current, leakage current starting, leading to flashover, preflashover, and flashover. This multistage classification approach enables more accurate early warning of impending flashover by identifying subtle changes in leakage current behavior that precede catastrophic insulation failure. Controlled contamination experiments were conducted using porcelain insulators under varying environmental stressors and leakage current data was systematically acquired, segmented, and labeled based on amplitude variations, harmonic distortion, and dry band arcing characteristics. The proposed model, based on inception modules with residual connections, effectively captures multiscale temporal patterns in leakage current signals. Furthermore, posttraining quantization was applied to compress the model for edge deployment, achieving a 91.4% reduction in model size and a 90% decrease in inference time with negligible accuracy loss. Comparative evaluation against conventional neural networks and state-of-the-art ML architectures demonstrated the superior classification accuracy, robustness, and computational efficiency of the proposed framework. This architecture not only facilitates early detection of flashover stages but also enables low-latency, low-power deployment on resource-constrained devices, such as embedded systems, in remote substations.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"630-646"},"PeriodicalIF":3.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11123745","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027892","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 : 2025-08-11DOI: 10.1109/OJIA.2025.3591740
Zahra Masoumi;Bijan Moaveni
This article presents a data-driven approach for diagnosing interturn short-circuit (ITSC) faults in the field winding of synchronous generators (SGs). A notable advantage of this method is its independence from the load’s linearity or nonlinearity. The method’s foundation is derived from analyzing the impact of ITSC faults on the state-space model of an SG, utilizing the SG equations in the dq rotor reference frame. Based on the state-space model, subspace identification and input–output data, including voltages and currents, are used to estimate the eigenvalues of the state matrix. The detection, isolation, and estimation of faults are achieved through the estimated eigenvalues, without relying on the model. Simulation and experimental results validate the effectiveness of this data-driven fault diagnosis methodology.
{"title":"Data-Driven Fault Diagnosis Approach for Synchronous Generators","authors":"Zahra Masoumi;Bijan Moaveni","doi":"10.1109/OJIA.2025.3591740","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3591740","url":null,"abstract":"This article presents a data-driven approach for diagnosing interturn short-circuit (ITSC) faults in the field winding of synchronous generators (SGs). A notable advantage of this method is its independence from the load’s linearity or nonlinearity. The method’s foundation is derived from analyzing the impact of ITSC faults on the state-space model of an SG, utilizing the SG equations in the <italic>dq</i> rotor reference frame. Based on the state-space model, subspace identification and input–output data, including voltages and currents, are used to estimate the eigenvalues of the state matrix. The detection, isolation, and estimation of faults are achieved through the estimated eigenvalues, without relying on the model. Simulation and experimental results validate the effectiveness of this data-driven fault diagnosis methodology.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"593-602"},"PeriodicalIF":3.3,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11121658","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144814084","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}
Electrically excited synchronous machines (EESMs) have historically been used as efficient and reliable synchronous generators. However, the actual need for cost-effective, sustainable motors without rare-earth magnets has notably increased the interest in EESMs, which are considered a valid replacement for permanent magnet synchronous machines (PMSMs) in electrified powertrains. As the electrical machines employed in automotive applications exhibit deep magnetic saturation, the EESM introduces significant challenges in properly modeling the magnetic behavior, especially considering the cross-coupling effects between stator and rotor. EESM-based electrical drive development requires accurate circuital models to predict EESM behavior. Therefore, this article proposes a novel voltage-behind-reactance (VBR) model based on flux maps provided by finite element analysis (FEA) or experimental identification procedures. The proposed VBR model has been validated in simulation and experimentally on a commercial 100 kW EESM currently used on the Renault Zoe EV R135, demonstrating its potential for accurately modeling EESMs designed for traction applications.
电激励同步电机（eesm）历来被用作高效可靠的同步发电机。然而，对经济高效、可持续的无稀土磁铁电机的实际需求显著增加了对eesm的兴趣，eesm被认为是电气化动力系统中永磁同步电机（pmsm）的有效替代品。由于汽车应用中使用的电机表现出深度磁饱和，EESM在正确建模磁行为方面引入了重大挑战，特别是考虑到定子和转子之间的交叉耦合效应。基于EESM的电气驱动开发需要精确的电路模型来预测EESM的行为。因此，本文提出了一种基于有限元分析（FEA）或实验识别程序提供的磁通图的新型电抗电压（VBR）模型。该VBR模型已在雷诺Zoe EV R135上使用的100 kW商用EESM上进行了仿真和实验验证，证明了其在为牵引应用设计的EESM精确建模方面的潜力。
{"title":"High-Fidelity Voltage-Behind-Reactance Model of Electrically Excited Synchronous Machines Using Flux Maps","authors":"Alessandro Ionta;Sandro Rubino;Federica Graffeo;Radu Bojoi","doi":"10.1109/OJIA.2025.3597812","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3597812","url":null,"abstract":"Electrically excited synchronous machines (EESMs) have historically been used as efficient and reliable synchronous generators. However, the actual need for cost-effective, sustainable motors without rare-earth magnets has notably increased the interest in EESMs, which are considered a valid replacement for permanent magnet synchronous machines (PMSMs) in electrified powertrains. As the electrical machines employed in automotive applications exhibit deep magnetic saturation, the EESM introduces significant challenges in properly modeling the magnetic behavior, especially considering the cross-coupling effects between stator and rotor. EESM-based electrical drive development requires accurate circuital models to predict EESM behavior. Therefore, this article proposes a novel voltage-behind-reactance (VBR) model based on flux maps provided by finite element analysis (FEA) or experimental identification procedures. The proposed VBR model has been validated in simulation and experimentally on a commercial 100 kW EESM currently used on the Renault Zoe EV R135, demonstrating its potential for accurately modeling EESMs designed for traction applications.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"603-618"},"PeriodicalIF":3.3,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11122645","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144918319","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}
Traditional high-speed rotor configurations employing magnetic bearing technology, which typically integrates two radial bearings and one axial bearing to suspend the rotor, are sensitive to changes in impeller mass properties. This article focuses on modular magnetically levitated rotor technology, which enables drivelines with two or more impellers and three or more radial active magnetic bearings (AMBs). This configuration ensures the reliability and robustness of the rotordynamic behavior by providing a structure that enables adaptable integration of components, such as compressors and turbines, onto the same long high-speed shaft. The structure considered here includes a 2-MW, 12 000 r/min induction machine with three radial magnetic bearings and a rotor system where the impeller is installed on a separate shaft and connected to the motor drive with a flexible coupling. The main focus of this article is on the proof-of-concept testing and commissioning of such a technology, with particular attention given to modeling and control aspects. An $H_{infty }$ loop-shaping approach is adopted for model-based control design, using a model that incorporates two flexible modes and adaptive notch structures to eliminate speed-synchronous components from the feedback signal. The AMB–rotor system modeling is validated through system identification routines. The experimental results demonstrate that the proposed modular technology provides improvements in rotordynamics despite the increased complexity of the system and control.
{"title":"Commissioning of a Modular Active-Magnetic-Bearing-Suspended Rotor System","authors":"Atte Putkonen;Juuso Narsakka;Gyan Ranjan;Tuomo Lindh;Jussi Sopanen;Niko Nevaranta","doi":"10.1109/OJIA.2025.3596973","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3596973","url":null,"abstract":"Traditional high-speed rotor configurations employing magnetic bearing technology, which typically integrates two radial bearings and one axial bearing to suspend the rotor, are sensitive to changes in impeller mass properties. This article focuses on modular magnetically levitated rotor technology, which enables drivelines with two or more impellers and three or more radial active magnetic bearings (AMBs). This configuration ensures the reliability and robustness of the rotordynamic behavior by providing a structure that enables adaptable integration of components, such as compressors and turbines, onto the same long high-speed shaft. The structure considered here includes a 2-MW, 12 000 r/min induction machine with three radial magnetic bearings and a rotor system where the impeller is installed on a separate shaft and connected to the motor drive with a flexible coupling. The main focus of this article is on the proof-of-concept testing and commissioning of such a technology, with particular attention given to modeling and control aspects. An <inline-formula><tex-math>$H_{infty }$</tex-math></inline-formula> loop-shaping approach is adopted for model-based control design, using a model that incorporates two flexible modes and adaptive notch structures to eliminate speed-synchronous components from the feedback signal. The AMB–rotor system modeling is validated through system identification routines. The experimental results demonstrate that the proposed modular technology provides improvements in rotordynamics despite the increased complexity of the system and control.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"619-629"},"PeriodicalIF":3.3,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11120452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914155","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}
Unscheduled event handling capability and swift recovery from transient events are indispensable study areas to ensure reliability in offshore multiterminal high-voltage dc (MT-HVdc) grids. This article focuses on enhancing the reliability of half-bridge modular multilevel converters (HB-MMCs) in MT-HVdc grids by introducing a predictive dc fault ride-through (DC-FRT) recovery controller and fault separation devices. A novel dc protection-informed zonal DC-FRT scheme for HB-MMCs is proposed, incorporating a model predictive planner for optimized control inputs based on local and interstation measurements and converter constraints. A real-time digital simulator environment simulates the approach, which improves lower level control during fault interruption and suppression by utilizing fault detection and location information. In addition, the study examines two control schemes to assess the impact of communication delays in MT-HVdc grids, a critical factor for system stability and reliability during faults. These schemes include a centralized scheme with delays in input and output signals and a decentralized approach focusing on external signal delays. Both are compared against a baseline centralized control with no delays. These approaches explore alternatives for the placement of the proposed controller, considering potential delays in interstation high-speed communication. The findings underscore the significance of the proposed DC-FRT control in reinforcing MT-HVdc systems against faults, which contributes to efficient recovery and grid stability.
{"title":"Predictive DC Fault Ride-Through for Offshore MMC-Based MT-HVDC Grid","authors":"Ajay Shetgaonkar;Vaibhav Nougain;Marjan Popov;Peter Palensky;Aleksandra Lekić","doi":"10.1109/OJIA.2025.3590306","DOIUrl":"https://doi.org/10.1109/OJIA.2025.3590306","url":null,"abstract":"Unscheduled event handling capability and swift recovery from transient events are indispensable study areas to ensure reliability in offshore multiterminal high-voltage dc (MT-HVdc) grids. This article focuses on enhancing the reliability of half-bridge modular multilevel converters (HB-MMCs) in MT-HVdc grids by introducing a predictive dc fault ride-through (DC-FRT) recovery controller and fault separation devices. A novel dc protection-informed zonal DC-FRT scheme for HB-MMCs is proposed, incorporating a model predictive planner for optimized control inputs based on local and interstation measurements and converter constraints. A real-time digital simulator environment simulates the approach, which improves lower level control during fault interruption and suppression by utilizing fault detection and location information. In addition, the study examines two control schemes to assess the impact of communication delays in MT-HVdc grids, a critical factor for system stability and reliability during faults. These schemes include a centralized scheme with delays in input and output signals and a decentralized approach focusing on external signal delays. Both are compared against a baseline centralized control with no delays. These approaches explore alternatives for the placement of the proposed controller, considering potential delays in interstation high-speed communication. The findings underscore the significance of the proposed DC-FRT control in reinforcing MT-HVdc systems against faults, which contributes to efficient recovery and grid stability.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"6 ","pages":"579-592"},"PeriodicalIF":3.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11083622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144814086","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}
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