This article introduces a new half-bridge inverter that employs Z-source technology to achieve a high boost factor without blocking high voltage on passive or active devices. This configuration includes the coupled inductors shaped in the A-source form, which is why the proposed topology is referred to as an A-source-based half-bridge inverter. The operation modes of the proposed topology are analyzed based on the states of diodes and switches in each state. The boost factor, average currents, and voltages related to the passive components are calculated, and equations are derived to estimate the size of required inductors and capacitors and the ratings of the switches and diodes. Furthermore, the topology’s efficiency is analyzed through power loss studies. A comparison of the proposed topology with past configurations reveals its advantages and disadvantages, demonstrating its capacity to provide a high boost factor while having superior specifications than some of them. Finally, an experimental sample of the proposed topology is tested in the laboratory to ensure proper operation and to compare its power losses and efficiency with other past works.
{"title":"A-Source-Based Half-Bridge Inverter: Analysis, Design, and Implementation","authors":"Mohammadamin Aalami;Ebrahim Babaei;Saeid Ghassem Zadeh","doi":"10.1109/OJIES.2025.3574190","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3574190","url":null,"abstract":"This article introduces a new half-bridge inverter that employs Z-source technology to achieve a high boost factor without blocking high voltage on passive or active devices. This configuration includes the coupled inductors shaped in the A-source form, which is why the proposed topology is referred to as an A-source-based half-bridge inverter. The operation modes of the proposed topology are analyzed based on the states of diodes and switches in each state. The boost factor, average currents, and voltages related to the passive components are calculated, and equations are derived to estimate the size of required inductors and capacitors and the ratings of the switches and diodes. Furthermore, the topology’s efficiency is analyzed through power loss studies. A comparison of the proposed topology with past configurations reveals its advantages and disadvantages, demonstrating its capacity to provide a high boost factor while having superior specifications than some of them. Finally, an experimental sample of the proposed topology is tested in the laboratory to ensure proper operation and to compare its power losses and efficiency with other past works.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1014-1026"},"PeriodicalIF":5.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11016201","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524372","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 : 2025-03-24DOI: 10.1109/OJIES.2025.3553061
Abdullah Berkay Bayindir;Ali Sharida;Sertac Bayhan;Haitham Abu-Rub
This article presents an approach for enhancing the reliability and robustness of electric vehicle (EV) chargers, particularly the dc–dc side of the EV chargers, by using the inverse model predictive control (IMPC). IMPC, a recently introduced control method for power electronic converters, leverages the strengths of model predictive control (MPC), while minimizing its computational burden. IMPC excels in managing sophisticated and nonlinear systems, controlling multiple objectives, and adhering to various constraints. However, the effectiveness of conventional IMPC is heavily dependent on the accurate dynamic model of the power converter. This dependency makes IMPC susceptible to uncertainties and disturbances. To address this challenge, the proposed method employs an adaptive estimation strategy utilizing a recursive least square algorithm for online dynamic model estimation. This real-time estimated model enables IMPC to predict optimal switching states with improved reliability. The proposed control technique is designed to provide constant power, constant current, and constant voltage modes, with the ability to seamlessly transition between them. The efficacy of this technique is demonstrated through extensive simulations and experimental validation for a dual active bridge (DAB) converter. This adaptive method underscores the potential of IMPC for practical EV charging scenarios, ensuring reliable and high-performance charging.
{"title":"Enhanced Inverse Model Predictive Control for EV Chargers: Solution for DC–DC Side","authors":"Abdullah Berkay Bayindir;Ali Sharida;Sertac Bayhan;Haitham Abu-Rub","doi":"10.1109/OJIES.2025.3553061","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3553061","url":null,"abstract":"This article presents an approach for enhancing the reliability and robustness of electric vehicle (EV) chargers, particularly the dc–dc side of the EV chargers, by using the inverse model predictive control (IMPC). IMPC, a recently introduced control method for power electronic converters, leverages the strengths of model predictive control (MPC), while minimizing its computational burden. IMPC excels in managing sophisticated and nonlinear systems, controlling multiple objectives, and adhering to various constraints. However, the effectiveness of conventional IMPC is heavily dependent on the accurate dynamic model of the power converter. This dependency makes IMPC susceptible to uncertainties and disturbances. To address this challenge, the proposed method employs an adaptive estimation strategy utilizing a recursive least square algorithm for online dynamic model estimation. This real-time estimated model enables IMPC to predict optimal switching states with improved reliability. The proposed control technique is designed to provide constant power, constant current, and constant voltage modes, with the ability to seamlessly transition between them. The efficacy of this technique is demonstrated through extensive simulations and experimental validation for a dual active bridge (DAB) converter. This adaptive method underscores the potential of IMPC for practical EV charging scenarios, ensuring reliable and high-performance charging.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"478-490"},"PeriodicalIF":5.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10935818","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808881","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}
This article presents a novel methodology for estimating the double-cage model (DCM) for three-phase induction machines (TIMs) using decision tree-based algorithms. Validated on a diverse dataset of 860 machines spanning a power range from 0.12 to 370 kW, the proposed method stands out by requiring fewer input parameters than traditional techniques like the modified Newton method. Moreover, the proposed approach remains effective even when the input data exhibits statistical deviations, a common challenge in practical scenarios. The main contributions of this work are the reduction of the number of parameters necessary for the estimation of the DCM equivalent circuit and employing three distinct decision tree-based algorithms, whose effectiveness was confirmed through simulations and experimental tests, thereby providing an accurate representation of the dynamics of real TIMs. The results indicate that by using only basic and readily available data from machine nameplates, such as nominal current, power, speed, voltage, and torque, the proposed methodology provides a reliable and efficient framework for incorporating the real dynamics of TIMs into computational models.
{"title":"Estimation of the Double-Cage Model for Three-Phase Induction Machines Using Decision Tree-Based Algorithms","authors":"Eduardo Ferreira Rios Oliveira;Rafael Santos;Marcelo Godoy Simões;Helmo Morales Paredes","doi":"10.1109/OJIES.2025.3572372","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3572372","url":null,"abstract":"This article presents a novel methodology for estimating the double-cage model (DCM) for three-phase induction machines (TIMs) using decision tree-based algorithms. Validated on a diverse dataset of 860 machines spanning a power range from 0.12 to 370 kW, the proposed method stands out by requiring fewer input parameters than traditional techniques like the modified Newton method. Moreover, the proposed approach remains effective even when the input data exhibits statistical deviations, a common challenge in practical scenarios. The main contributions of this work are the reduction of the number of parameters necessary for the estimation of the DCM equivalent circuit and employing three distinct decision tree-based algorithms, whose effectiveness was confirmed through simulations and experimental tests, thereby providing an accurate representation of the dynamics of real TIMs. The results indicate that by using only basic and readily available data from machine nameplates, such as nominal current, power, speed, voltage, and torque, the proposed methodology provides a reliable and efficient framework for incorporating the real dynamics of TIMs into computational models.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"915-926"},"PeriodicalIF":5.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010148","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219639","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 : 2025-03-22DOI: 10.1109/OJIES.2025.3572429
Thierry A. Meynard;Hugues Renaudineau;Polidoro S. Canales;Samir Kouro;Diego Concha;Ana M. Llor;Maurice Fadel;Henri Schneider
The concept of partial power converters is promising since it might bring significant cost, weight, volume, and power losses reduction. However, most partial power converters presented in the literature include a high-frequency transformer to redirect power from one part of the circuit to another, which adds cost, weight, volume and losses, and cancels out most of the potential advantages introduced by the partiality concept. In this article two variants of a transformerless partial voltage converter capable of supplying twice the power of conventional converters are described and analyzed. These converters can be used for applications in which the load voltages can be split into several sub-voltages of similar characteristics, which makes it typically applicable to batteries, fuel cells, electrolyzers and LEDs. Two main conditions are required to use these topologies: first, the voltage across the load needs to be controlled in a limited range only, typically [50%;100%] or less, and second, it must be possible to split easily the load voltages in several smaller dc voltages. Nevertheless, these restrictions still allow a wide range of possible applications including electrochemical loads such as batteries, fuel cells, electrolyzers, and even PV systems. Their main properties are analyzed and confirmed by experimental results. The lack of transformer and the partial power processing capabilities of the topologies result in extremely high efficiencies of over 99%.
{"title":"TransformerLess Partial Voltage DC–DC Converter With Double Power Processing Capacity","authors":"Thierry A. Meynard;Hugues Renaudineau;Polidoro S. Canales;Samir Kouro;Diego Concha;Ana M. Llor;Maurice Fadel;Henri Schneider","doi":"10.1109/OJIES.2025.3572429","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3572429","url":null,"abstract":"The concept of partial power converters is promising since it might bring significant cost, weight, volume, and power losses reduction. However, most partial power converters presented in the literature include a high-frequency transformer to redirect power from one part of the circuit to another, which adds cost, weight, volume and losses, and cancels out most of the potential advantages introduced by the partiality concept. In this article two variants of a transformerless partial voltage converter capable of supplying twice the power of conventional converters are described and analyzed. These converters can be used for applications in which the load voltages can be split into several sub-voltages of similar characteristics, which makes it typically applicable to batteries, fuel cells, electrolyzers and LEDs. Two main conditions are required to use these topologies: first, the voltage across the load needs to be controlled in a limited range only, typically [50%;100%] or less, and second, it must be possible to split easily the load voltages in several smaller dc voltages. Nevertheless, these restrictions still allow a wide range of possible applications including electrochemical loads such as batteries, fuel cells, electrolyzers, and even PV systems. Their main properties are analyzed and confirmed by experimental results. The lack of transformer and the partial power processing capabilities of the topologies result in extremely high efficiencies of over 99%.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"927-937"},"PeriodicalIF":5.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243670","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}
Manufacturing processes increasingly depend on advanced production machinery that must deliver high quality and large volumes. This applies to die-bonding machines as well that, especially at the time being after the years of shortage, need to meet very high standards of speed and accuracy. To achieve this, these devices are exploring the use of computer vision algorithms for automatic recognition of wafer positioning and die size. Nevertheless, these systems are typically managed by software-only solutions, which may fall short under stringent execution time requirements. A promising solution is the use of heterogeneous platforms, combining general-purpose processors with reconfigurable hardware. Such platforms offer the flexibility to handle both software tasks, which benefit from operating system support, and critical functions requiring hardware acceleration. This article presents a closed-loop implementation of a vision-based multisensor control system for an industrial application. The implementation exploits the capabilities of system on module technologies to provide flexible input/output and software execution coupled with computing acceleration for the vision algorithm on the reconfigurable field-programmable gate array (FPGA) fabric. The FPGA coprocessor has been designed leveraging the high-level synthesis technology and optimized on a dataset of 10 k realistic images to meet the industrial use case's performance, communication, and accuracy requirements. Moreover, the resulting accelerator performance and resource utilization demonstrate the possibility of reaching state-of-the-art metrics of handwritten hardware designs while allowing for higher abstraction and productivity of the design process.
{"title":"Integrating FPGA-Based Acceleration in Industrial Motion Control System","authors":"Claudio Rubattu;Antonio Ledda;Francesco Ratto;Chaitanya Jugade;Dip Goswami;Francesca Palumbo","doi":"10.1109/OJIES.2025.3571218","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3571218","url":null,"abstract":"Manufacturing processes increasingly depend on advanced production machinery that must deliver high quality and large volumes. This applies to die-bonding machines as well that, especially at the time being after the years of shortage, need to meet very high standards of speed and accuracy. To achieve this, these devices are exploring the use of computer vision algorithms for automatic recognition of wafer positioning and die size. Nevertheless, these systems are typically managed by software-only solutions, which may fall short under stringent execution time requirements. A promising solution is the use of heterogeneous platforms, combining general-purpose processors with reconfigurable hardware. Such platforms offer the flexibility to handle both software tasks, which benefit from operating system support, and critical functions requiring hardware acceleration. This article presents a closed-loop implementation of a vision-based multisensor control system for an industrial application. The implementation exploits the capabilities of system on module technologies to provide flexible input/output and software execution coupled with computing acceleration for the vision algorithm on the reconfigurable field-programmable gate array (FPGA) fabric. The FPGA coprocessor has been designed leveraging the high-level synthesis technology and optimized on a dataset of 10 k realistic images to meet the industrial use case's performance, communication, and accuracy requirements. Moreover, the resulting accelerator performance and resource utilization demonstrate the possibility of reaching state-of-the-art metrics of handwritten hardware designs while allowing for higher abstraction and productivity of the design process.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"898-914"},"PeriodicalIF":5.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006509","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219638","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 : 2025-03-19DOI: 10.1109/OJIES.2025.3571204
Yang Zhao;Chee Shen Lim;Fei Xue;Chao Long;Andrew Huey Ping Tan
High-performance motor drives rely on closed-loop controls that typically obtain rotor position from a physical encoder or a rotor position estimator. However, it is well established that there may be discrepancies between the measured/estimated position and the actual one. This may be due to the loosening of the encoder's mechanical fixing, initialization errors, sensorless estimation errors, etc. The rotor position error, if left uncompensated, may lead to torque fluctuation and reduced system efficiency. Different from the mainstream iterative or model-based methods introduced thus far, this article focused on a data-driven solution that is based on the use of lightweight long short-term memory (LSTM) and gated recurrent unit (GRU) neural networks, realized in conjunction with real-time embedded microcontrollers. Benchmarked against the familiar choice of multilayer perceptron, these emerging recurrent neural networks (RNNs), which have received tremendous attention in computer science subjects but much less in power- electronic-based electric drives, are designed for estimating position errors with high accuracy. Upon careful consideration of the embedded data in the stationary and rotating reference frames, data down sampling, and real-time computing capability, this article shows that these emerging RNNs are potentially more robust against measurement noises and harmonics inherently present in drive systems. They are proven to better generalize to nontraining operating points or data, constituting an essential feature when dealing with closed-loop control's experimental data. The proposed lightweight LSTM- and GRU-based neural networks are extensively validated using a 2.2-kW interior permanent-magnet synchronous motors through simulations and experiments for estimating the step- and ramp-type dynamic rotor position errors. The comparative evaluation against the classical iterative rotor position correction method confirms its superiority in terms of estimation speed and accuracy, suggesting a good potential of the data-driven concept in improving electric drives.
{"title":"Lightweight LSTM and GRU Design for Data-Driven Rotor Position Error Estimation in IPMSM Drives","authors":"Yang Zhao;Chee Shen Lim;Fei Xue;Chao Long;Andrew Huey Ping Tan","doi":"10.1109/OJIES.2025.3571204","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3571204","url":null,"abstract":"High-performance motor drives rely on closed-loop controls that typically obtain rotor position from a physical encoder or a rotor position estimator. However, it is well established that there may be discrepancies between the measured/estimated position and the actual one. This may be due to the loosening of the encoder's mechanical fixing, initialization errors, sensorless estimation errors, etc. The rotor position error, if left uncompensated, may lead to torque fluctuation and reduced system efficiency. Different from the mainstream iterative or model-based methods introduced thus far, this article focused on a data-driven solution that is based on the use of lightweight long short-term memory (LSTM) and gated recurrent unit (GRU) neural networks, realized in conjunction with real-time embedded microcontrollers. Benchmarked against the familiar choice of multilayer perceptron, these emerging recurrent neural networks (RNNs), which have received tremendous attention in computer science subjects but much less in power- electronic-based electric drives, are designed for estimating position errors with high accuracy. Upon careful consideration of the embedded data in the stationary and rotating reference frames, data down sampling, and real-time computing capability, this article shows that these emerging RNNs are potentially more robust against measurement noises and harmonics inherently present in drive systems. They are proven to better generalize to nontraining operating points or data, constituting an essential feature when dealing with closed-loop control's experimental data. The proposed lightweight LSTM- and GRU-based neural networks are extensively validated using a 2.2-kW interior permanent-magnet synchronous motors through simulations and experiments for estimating the step- and ramp-type dynamic rotor position errors. The comparative evaluation against the classical iterative rotor position correction method confirms its superiority in terms of estimation speed and accuracy, suggesting a good potential of the data-driven concept in improving electric drives.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"851-867"},"PeriodicalIF":5.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006416","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219701","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 : 2025-03-16DOI: 10.1109/OJIES.2025.3571319
Victor Chavez;Jörg Wollert
Semantic interoperability is essential for the development of intelligent systems, the integration of heterogeneous devices, and the exchange of information independent of protocol. To this end, Industry 4.0 consortia have proposed interoperable information models to ensure the standardized interpretation of data for industrial systems. However, adapting existing standards to Industry 4.0 models remains a challenge for field devices due to the complexity of generically mapping domain-specific concepts and their interpretation. In this article, we propose a novel ontology-based framework to automate the interpretation of field device standards, providing a high-level interface to measure or control a process through generic capabilities. Through the use of the Industry 4.0 field device ontology, we generalize the interpretation of application data and device profiles to model the IO-Link and CANOpen standards. The proposed framework is evaluated using a plug-and-play tank demonstrator that leverages generic capabilities to identify commercial field devices and control an industrial process. Our results demonstrate that the generalization of field device semantics significantly reduces the manual effort of integrating different standards, in turn bridging the semantic gap between field devices and Industry 4.0 information models.
{"title":"An Industry 4.0 Semantic Framework for the Inference of Generic Field Device Capabilities","authors":"Victor Chavez;Jörg Wollert","doi":"10.1109/OJIES.2025.3571319","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3571319","url":null,"abstract":"Semantic interoperability is essential for the development of intelligent systems, the integration of heterogeneous devices, and the exchange of information independent of protocol. To this end, Industry 4.0 consortia have proposed interoperable information models to ensure the standardized interpretation of data for industrial systems. However, adapting existing standards to Industry 4.0 models remains a challenge for field devices due to the complexity of generically mapping domain-specific concepts and their interpretation. In this article, we propose a novel ontology-based framework to automate the interpretation of field device standards, providing a high-level interface to measure or control a process through generic capabilities. Through the use of the Industry 4.0 field device ontology, we generalize the interpretation of application data and device profiles to model the IO-Link and CANOpen standards. The proposed framework is evaluated using a plug-and-play tank demonstrator that leverages generic capabilities to identify commercial field devices and control an industrial process. Our results demonstrate that the generalization of field device semantics significantly reduces the manual effort of integrating different standards, in turn bridging the semantic gap between field devices and Industry 4.0 information models.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"868-882"},"PeriodicalIF":5.2,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006417","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219641","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 : 2025-03-16DOI: 10.1109/OJIES.2025.3570789
Yasuhiro Kato;Sho Sakaino;Toshiaki Tsuji
This article introduces a novel approach for guiding human arm movement in the context of robotic rehabilitation. We propose upper limb movement guidance using a force field based on an asymmetric stiffness matrix. By introducing asymmetry in stiffness design, the proposed force field can deflect arm movement toward the target direction of a reaching movement while minimizing impeding effects. We hypothesize that this method can guide a human in the desired direction without interfering with their voluntary movement. To evaluate the performance of the human arm guidance technique, we conducted upper limb reaching experiments using a 2-degree-of-freedom robot arm with ten healthy volunteers. The experimental results revealed that the proposed approach demonstrated a similar reduction in movement error compared to the conventional stiffness approach. Moreover, participants exhibited higher movement activeness, and robotic interference with human movement was lower. The proposed approach may improve movement guidance based on stiffness control by enabling the robot to guide without inhibiting voluntary movement.
{"title":"Minimizing Interference in Robotic Rehabilitation via Asymmetric Stiffness Force Fields","authors":"Yasuhiro Kato;Sho Sakaino;Toshiaki Tsuji","doi":"10.1109/OJIES.2025.3570789","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3570789","url":null,"abstract":"This article introduces a novel approach for guiding human arm movement in the context of robotic rehabilitation. We propose upper limb movement guidance using a force field based on an asymmetric stiffness matrix. By introducing asymmetry in stiffness design, the proposed force field can deflect arm movement toward the target direction of a reaching movement while minimizing impeding effects. We hypothesize that this method can guide a human in the desired direction without interfering with their voluntary movement. To evaluate the performance of the human arm guidance technique, we conducted upper limb reaching experiments using a 2-degree-of-freedom robot arm with ten healthy volunteers. The experimental results revealed that the proposed approach demonstrated a similar reduction in movement error compared to the conventional stiffness approach. Moreover, participants exhibited higher movement activeness, and robotic interference with human movement was lower. The proposed approach may improve movement guidance based on stiffness control by enabling the robot to guide without inhibiting voluntary movement.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"840-850"},"PeriodicalIF":5.2,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190565","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 : 2025-03-14DOI: 10.1109/OJIES.2025.3551369
Seong Jin Lim;Sung-Geun Song;Guangxu Zhou;Feel-Soon Kang
Metal oxide varistor (MOV) is a nonlinear resistive element whose resistance decreases rapidly when the applied voltage exceeds a threshold value. A dc solid-state circuit breaker (SSCB) uses MOVs or MOV with resistor-capacitor-diode (RCD) snubber circuit combinations to reduce the surge voltage that occurs when breaking a fault current. The more MOV and RCD circuit components are added, the greater the surge voltage reduction effect. However, an increase in several parts leads to a rise in the cost of the snubber circuit. This article aims to find an economical circuit structure that improves the surge voltage reduction rate and does not increase the cost significantly by adding MOV and RCD snubber combinations to the conventional MOV-based surge voltage reduction circuits. First, three circuit combinations employing MOV, R, C, and diodes are presented. We confirm the proposed snubber circuit structures effectively reduce surge voltage by comparing surge voltage reduction rates through theoretical analysis, simulation, and experiment. Second, cost model analysis for the proposed circuits is used to calculate the total price of components. Finally, the economic feasibility of the proposed snubber circuits is evaluated by the cost required to achieve a 1% surge voltage reduction rate. The results of this article facilitate the selection of an economical circuit structure that combines additional MOV or RCD snubbers in the conventional MOV-based snubber circuits to reduce the surge voltage of SSCBs while minimizing cost increase.
{"title":"Comparison of Surge Voltage Reduction and Economic Efficiency of DC SSCBs According to MOV and RCD Snubber Combination","authors":"Seong Jin Lim;Sung-Geun Song;Guangxu Zhou;Feel-Soon Kang","doi":"10.1109/OJIES.2025.3551369","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3551369","url":null,"abstract":"Metal oxide varistor (MOV) is a nonlinear resistive element whose resistance decreases rapidly when the applied voltage exceeds a threshold value. A dc solid-state circuit breaker (SSCB) uses MOVs or MOV with resistor-capacitor-diode (RCD) snubber circuit combinations to reduce the surge voltage that occurs when breaking a fault current. The more MOV and RCD circuit components are added, the greater the surge voltage reduction effect. However, an increase in several parts leads to a rise in the cost of the snubber circuit. This article aims to find an economical circuit structure that improves the surge voltage reduction rate and does not increase the cost significantly by adding MOV and RCD snubber combinations to the conventional MOV-based surge voltage reduction circuits. First, three circuit combinations employing MOV, R, C, and diodes are presented. We confirm the proposed snubber circuit structures effectively reduce surge voltage by comparing surge voltage reduction rates through theoretical analysis, simulation, and experiment. Second, cost model analysis for the proposed circuits is used to calculate the total price of components. Finally, the economic feasibility of the proposed snubber circuits is evaluated by the cost required to achieve a 1% surge voltage reduction rate. The results of this article facilitate the selection of an economical circuit structure that combines additional MOV or RCD snubbers in the conventional MOV-based snubber circuits to reduce the surge voltage of SSCBs while minimizing cost increase.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"522-534"},"PeriodicalIF":5.2,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10925887","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808880","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 : 2025-03-12DOI: 10.1109/OJIES.2025.3569349
Sepideh Amirpour;Sima Soltanipour;Torbjörn Thiringer;Pranav Katta
This study focuses on identifying the optimal switching frequency for silicon-carbide (SiC)-based motor drives across a wide range of operating conditions using a loss minimization strategy. The results are then compared with those of traditional silicon-insulated-gate bipolar transistor (IGBT) systems. The approach involves conducting a comprehensive real-time finite element method (FEM) analysis of losses induced by pulsewidth modulation (PWM) voltages in an interior permanent magnet synchronous machine, compared to conventional sinusoidal current excitation feeding. The analysis integrates electromagnetic field simulations in Ansys Maxwell with the drive system control algorithm in Ansys Twin Builder, ensuring an accurate representation of their interactions. In addition, a method utilizing speed-adaptive core loss coefficients, which account for variable frequencies, is implemented for a more precise core loss estimation. The results reveal a notable discrepancy of up to 80$%$ in the core loss calculations when using speed-adaptive coefficients versus fixed coefficients. By employing the real-time coupled simulations, the higher switching capabilities of SiC mosfets could be effectively realized to optimize the PWM frequency over a broader range (10–50 kHz), particularly in the main drive region of electric vehicles, with differences of up to 20 kHz compared to IGBT systems. Furthermore, applying the proposed optimal PWM frequency profile in the worldwide harmonized light vehicle test cycle leads to a reduction of up to 22$%$ in accumulated energy losses in the SiC motor drive compared to its IGBT counterpart.
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