Pub Date : 2024-03-13DOI: 10.1109/OJIA.2024.3400208
Nicolaus Jennings;David Wetz;Rick Langley;Nancy LaFlair;John Heinzel
As the Navy moves forward with implementing electrochemical energy sources in their power systems, a need to understand the hazards present to electric workers comes to light. Understanding the effects these sources have on arc flash hazards drives the need to study relevant energy sources that are deployed on naval platforms. A 1000-V valve regulated lead acid (VRLA) battery system presents the greatest need to study as incident energy models can suggest dramatic personal protective equipment (PPE) especially with the inclusion of scale factors. As a part of a collaborative effort between the Electric Power Research Institute (EPRI) and the University of Texas at Arlington (UTA) arc flash studies of VRLA battery systems at voltages as high as 936 V have been performed. Findings show that below 800 V, the battery sourced incident energy as high as 0.26 cal/cm 2 . Above 800 V, incident energy surpassed 1.2 cal/cm 2 and approached category 1 PPE (4 cal/cm 2 ). A model derived from this work is used to emphasize the impact enclosure based scale factors have on incident energy estimates. This work has also compared relevant dc incident energy models to the measured incident energy sourced from this battery system.
随着海军在其电力系统中采用电化学能源，了解电工面临的危险的必要性逐渐凸显出来。了解这些能源对弧闪危险的影响，就需要对海军平台上部署的相关能源进行研究。1000 V 阀控式铅酸 (VRLA) 电池系统是最需要研究的，因为事故能量模型可以建议使用剧烈的个人防护设备 (PPE)，特别是在包含比例因素的情况下。作为美国电力研究所 (EPRI) 和德克萨斯大学阿灵顿分校 (UTA) 合作项目的一部分，对电压高达 936 V 的 VRLA 电池系统进行了弧闪研究。研究结果表明，电压低于 800 V 时，电池产生的入射能量高达 0.26 cal/cm2。高于 800 V 时，入射能量超过 1.2 cal/cm2，接近 1 类 PPE（4 cal/cm2）。从这项工作中得出的模型用于强调基于外壳的比例系数对入射能量估计值的影响。这项工作还将相关直流入射能量模型与来自该电池系统的测量入射能量进行了比较。
{"title":"DC Arc Flash Measurements From a 1000 V Valve Regulated Lead Acid Battery System","authors":"Nicolaus Jennings;David Wetz;Rick Langley;Nancy LaFlair;John Heinzel","doi":"10.1109/OJIA.2024.3400208","DOIUrl":"10.1109/OJIA.2024.3400208","url":null,"abstract":"As the Navy moves forward with implementing electrochemical energy sources in their power systems, a need to understand the hazards present to electric workers comes to light. Understanding the effects these sources have on arc flash hazards drives the need to study relevant energy sources that are deployed on naval platforms. A 1000-V valve regulated lead acid (VRLA) battery system presents the greatest need to study as incident energy models can suggest dramatic personal protective equipment (PPE) especially with the inclusion of scale factors. As a part of a collaborative effort between the Electric Power Research Institute (EPRI) and the University of Texas at Arlington (UTA) arc flash studies of VRLA battery systems at voltages as high as 936 V have been performed. Findings show that below 800 V, the battery sourced incident energy as high as 0.26 cal/cm\u0000<sup>2</sup>\u0000. Above 800 V, incident energy surpassed 1.2 cal/cm\u0000<sup>2</sup>\u0000 and approached category 1 PPE (4 cal/cm\u0000<sup>2</sup>\u0000). A model derived from this work is used to emphasize the impact enclosure based scale factors have on incident energy estimates. This work has also compared relevant dc incident energy models to the measured incident energy sourced from this battery system.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"168-176"},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10529540","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939826","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 : 2024-03-10DOI: 10.1109/OJIA.2024.3399603
Nandakumar Saminathan;Aditya P;Satish Naik Banavath;Alessandro Lidozzi;Marco Di Benedetto;Vengadarajan A
This article proposes a novel zero-voltage switching (ZVS) and zero-current switching (ZCS)-based hybrid dc circuit breaker for a radar power system. Long-range radars demand huge power, in the order of hundreds of kW. Radar's phased array antenna houses a large number of electronic devices and works primarily on a dc power supply. Typically, military systems are required to have the highest operational reliability, as a result, electrical system protection plays a crucial role. A high power 310 V dc electrical power grid in radar carries hundreds of amperes of current under nominal operating conditions, results in significant fault current due to very low impedance, and demands a very fast fault interruption device. This article proposes and demonstrates the complete operation of a hybrid dc circuit breaker topology for radar applications. The proposed dc circuit breaker employs a mechanical switch that carries the entire current during the nominal operating conditions, and a power electronic module (PEM) connected in parallel helps in diverting the fault current from the main path. Fault current transfers to the PEM branch in a fraction of a second (5 $mu s$ ), which ensures faster load-side isolation. During the fault interruption process, mechanical switch contact opening experiences both ZVS and ZCS features, resulting in arcless operation, and also helps in faster contact separation. The ZVS and ZCS features greatly improve the reliability of the mechanical switch. The proposed concept does not involve any capacitors or corresponding precharging circuits for the ZVS/ZCS features. The proposed dc circuit breaker is analyzed theoretically, and also by simulations in LTspice. Additionally, an experimental prototype with a dc system rating of 310 V–10 A is developed to experimentally validate the performance of the proposed breaker topology. The article also presents a detailed design and comparative analysis, along with a discussion on the limitations of the proposed dc circuit breaker, and the scope for improvements.
{"title":"Bidirectional Hybrid DC Circuit Breaker With Zero Voltage and Current Switching for Radar Power System","authors":"Nandakumar Saminathan;Aditya P;Satish Naik Banavath;Alessandro Lidozzi;Marco Di Benedetto;Vengadarajan A","doi":"10.1109/OJIA.2024.3399603","DOIUrl":"10.1109/OJIA.2024.3399603","url":null,"abstract":"This article proposes a novel zero-voltage switching (ZVS) and zero-current switching (ZCS)-based hybrid dc circuit breaker for a radar power system. Long-range radars demand huge power, in the order of hundreds of kW. Radar's phased array antenna houses a large number of electronic devices and works primarily on a dc power supply. Typically, military systems are required to have the highest operational reliability, as a result, electrical system protection plays a crucial role. A high power 310 V dc electrical power grid in radar carries hundreds of amperes of current under nominal operating conditions, results in significant fault current due to very low impedance, and demands a very fast fault interruption device. This article proposes and demonstrates the complete operation of a hybrid dc circuit breaker topology for radar applications. The proposed dc circuit breaker employs a mechanical switch that carries the entire current during the nominal operating conditions, and a power electronic module (PEM) connected in parallel helps in diverting the fault current from the main path. Fault current transfers to the PEM branch in a fraction of a second (5 \u0000<inline-formula><tex-math>$mu s$</tex-math></inline-formula>\u0000), which ensures faster load-side isolation. During the fault interruption process, mechanical switch contact opening experiences both ZVS and ZCS features, resulting in arcless operation, and also helps in faster contact separation. The ZVS and ZCS features greatly improve the reliability of the mechanical switch. The proposed concept does not involve any capacitors or corresponding precharging circuits for the ZVS/ZCS features. The proposed dc circuit breaker is analyzed theoretically, and also by simulations in LTspice. Additionally, an experimental prototype with a dc system rating of 310 V–10 A is developed to experimentally validate the performance of the proposed breaker topology. The article also presents a detailed design and comparative analysis, along with a discussion on the limitations of the proposed dc circuit breaker, and the scope for improvements.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"224-234"},"PeriodicalIF":0.0,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10528799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939689","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 proposes the theoretical development and experimental application of the active disturbance rejection control (ADRC) to synchronous reluctance motor (SynRM) drives. The ADRC is a robust adaptive extension of the input-output feedback linearization control (FLC). It performs the exact linearization of the SynRM model by a suitable nonlinear transformation of the state based on the online estimation of the corrective term by the so-called extended state observers (ESO). Consequently, any unmodeled dynamics or uncertainty of the parameters are properly addressed. The control strategy has been verified successfully both in numerical simulations and experimentally on a suitably developed test set-up that provides the ADRC robustness versus parameters variations which cannot be obtained with other model-based nonlinear control techniques (e.g., FLC). Simulation results show the capability of the ADRC to maintain its dynamic performance, even in the presence of quick variations of the SynRM dynamic inductances. Experimental results confirm the robustness of the ADRC versus any model parameter uncertainty. The proposed ADRC has been experimentally compared with a previously developed FLC, in both a tuned and detuned working configuration, with the classic rotor oriented control, and with a finite state model predictive control (MPC), where speed control is integrated into the MPC. Experimental results show far better robustness versus any parameter variation.
{"title":"Robust Control of Synchronous Reluctance Motor Based on Automatic Disturbance Rejection","authors":"Angelo Accetta;Maurizio Cirrincione;Filippo D'Ippolito;Marcello Pucci;Antonino Sferlazza","doi":"10.1109/OJIA.2024.3399009","DOIUrl":"10.1109/OJIA.2024.3399009","url":null,"abstract":"This article proposes the theoretical development and experimental application of the active disturbance rejection control (ADRC) to synchronous reluctance motor (SynRM) drives. The ADRC is a robust adaptive extension of the input-output feedback linearization control (FLC). It performs the exact linearization of the SynRM model by a suitable nonlinear transformation of the state based on the online estimation of the corrective term by the so-called extended state observers (ESO). Consequently, any unmodeled dynamics or uncertainty of the parameters are properly addressed. The control strategy has been verified successfully both in numerical simulations and experimentally on a suitably developed test set-up that provides the ADRC robustness versus parameters variations which cannot be obtained with other model-based nonlinear control techniques (e.g., FLC). Simulation results show the capability of the ADRC to maintain its dynamic performance, even in the presence of quick variations of the SynRM dynamic inductances. Experimental results confirm the robustness of the ADRC versus any model parameter uncertainty. The proposed ADRC has been experimentally compared with a previously developed FLC, in both a tuned and detuned working configuration, with the classic rotor oriented control, and with a finite state model predictive control (MPC), where speed control is integrated into the MPC. Experimental results show far better robustness versus any parameter variation.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"209-223"},"PeriodicalIF":0.0,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10526420","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939990","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}
The Industrial Revolution has shifted toward Industry 5.0, reinventing the Industry 4.0 operational process by introducing human elements into critical decision processes. Industry 5.0 would present massive customization via transformative technologies, such as cyber-physical systems (CPSs), artificial intelligence (AI), and big data analytics. In Industry 5.0, the AI models must be transparent, valid, and interpretable. AI models employ machine learning and deep learning mechanisms to make the industrial process autonomous, reduce downtime, and improve operational and maintenance costs. However, the models require explainability in the learning process. Thus, explainable AI (EXAI) adds interpretability and improves the diagnosis of critical industrial processes, which augments the machine-to-human explanations and vice versa. Recent surveys of EXAI in industrial applications are mostly oriented toward EXAI models, the underlying assumptions. Still, fewer studies are conducted toward a holistic integration of EXAI with human-centric processes that drives the Industry 5.0 applicative verticals. Thus, to address the gap, we propose a first-of-its-kind survey that systematically untangles EXAI integration and its potential in Industry 5.0 applications. First, we present the background of EXAI in Industry 5.0 and CPSs and a reference EXAI-based Industry 5.0 architecture with insights into large language models. Then, based on the research questions, a solution taxonomy of EXAI in Industry 5.0 is presented, which is ably supported by applicative use cases (cloud, digital twins, smart grids, augmented reality, and unmanned aerial vehicles). Finally, a case study of EXAI in manufacturing cost assessment is discussed, followed by open issues and future directions. The survey is designed to extend novel prototypes and designs to realize EXAI-based real-time Industry 5.0 applications.
{"title":"Explainable AI for Industry 5.0: Vision, Architecture, and Potential Directions","authors":"Chandan Trivedi;Pronaya Bhattacharya;Vivek Kumar Prasad;Viraj Patel;Arunendra Singh;Sudeep Tanwar;Ravi Sharma;Srinivas Aluvala;Giovanni Pau;Gulshan Sharma","doi":"10.1109/OJIA.2024.3399057","DOIUrl":"10.1109/OJIA.2024.3399057","url":null,"abstract":"The Industrial Revolution has shifted toward Industry 5.0, reinventing the Industry 4.0 operational process by introducing human elements into critical decision processes. Industry 5.0 would present massive customization via transformative technologies, such as cyber-physical systems (CPSs), artificial intelligence (AI), and big data analytics. In Industry 5.0, the AI models must be transparent, valid, and interpretable. AI models employ machine learning and deep learning mechanisms to make the industrial process autonomous, reduce downtime, and improve operational and maintenance costs. However, the models require explainability in the learning process. Thus, explainable AI (EXAI) adds interpretability and improves the diagnosis of critical industrial processes, which augments the machine-to-human explanations and vice versa. Recent surveys of EXAI in industrial applications are mostly oriented toward EXAI models, the underlying assumptions. Still, fewer studies are conducted toward a holistic integration of EXAI with human-centric processes that drives the Industry 5.0 applicative verticals. Thus, to address the gap, we propose a first-of-its-kind survey that systematically untangles EXAI integration and its potential in Industry 5.0 applications. First, we present the background of EXAI in Industry 5.0 and CPSs and a reference EXAI-based Industry 5.0 architecture with insights into large language models. Then, based on the research questions, a solution taxonomy of EXAI in Industry 5.0 is presented, which is ably supported by applicative use cases (cloud, digital twins, smart grids, augmented reality, and unmanned aerial vehicles). Finally, a case study of EXAI in manufacturing cost assessment is discussed, followed by open issues and future directions. The survey is designed to extend novel prototypes and designs to realize EXAI-based real-time Industry 5.0 applications.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"177-208"},"PeriodicalIF":0.0,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10526434","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939890","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 : 2024-02-27DOI: 10.1109/OJIA.2024.3369993
Jonathan D. Boyd;Donald R. Reising;Anthony M. Murphy;Justin D. Kuhlers;C. Michael McAmis;James B. Rossman
Voltage unbalance is a growing issue that, among other things, can impact three-phase motor and drive loads, result in nuisance tripping of generation units and capacitor banks, and prevent optimization of conservative voltage regulation strategies. This difference between the three phases of voltage delivered to customers can damage the equipment of these customers as well as negatively impact the power system itself. This work presents an approach for predicting voltage unbalance using machine learning. Historical megawatt and megavar data–obtained through a Supervisory Control And Data Acquisition (SCADA) system–are used to train an artificial neural network model as a binary classifier with a portion of the data serving to validate the trained model. Voltage unbalance is predicted at an accuracy above 95% for eight substations within the power utility's extra-high voltage transmission network and over 91% for all 42 substations. The trained model is tested in a manner that would be employed using simulated data generated by state estimation software. This simulated data validates the model's capacity to predict the substation buses that would experience voltage unbalance.
{"title":"Machine Learning Techniques to Predict Voltage Unbalance in a Power Transmission System","authors":"Jonathan D. Boyd;Donald R. Reising;Anthony M. Murphy;Justin D. Kuhlers;C. Michael McAmis;James B. Rossman","doi":"10.1109/OJIA.2024.3369993","DOIUrl":"10.1109/OJIA.2024.3369993","url":null,"abstract":"Voltage unbalance is a growing issue that, among other things, can impact three-phase motor and drive loads, result in nuisance tripping of generation units and capacitor banks, and prevent optimization of conservative voltage regulation strategies. This difference between the three phases of voltage delivered to customers can damage the equipment of these customers as well as negatively impact the power system itself. This work presents an approach for predicting voltage unbalance using machine learning. Historical megawatt and megavar data–obtained through a Supervisory Control And Data Acquisition (SCADA) system–are used to train an artificial neural network model as a binary classifier with a portion of the data serving to validate the trained model. Voltage unbalance is predicted at an accuracy above 95% for eight substations within the power utility's extra-high voltage transmission network and over 91% for all 42 substations. The trained model is tested in a manner that would be employed using simulated data generated by state estimation software. This simulated data validates the model's capacity to predict the substation buses that would experience voltage unbalance.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"86-93"},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10448538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140002408","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 : 2024-02-26DOI: 10.1109/OJIA.2024.3354443
{"title":"IEEE Industry Applications Society Information","authors":"","doi":"10.1109/OJIA.2024.3354443","DOIUrl":"https://doi.org/10.1109/OJIA.2024.3354443","url":null,"abstract":"","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10444962","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139976195","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 : 2024-02-20DOI: 10.1109/OJIA.2024.3367547
Zahra Soltani;Mojdeh Khorsand;Shanshan Ma
Modern distribution systems are changing from passive load serving networks to active load and generation-inclusive networks. Accurate distribution systems modeling is critical for effective distribution system control, operation, and planning. This article proposes novel nonlinear and convex ac optimal power flow (ACOPF) models based on current–voltage (IVACOPF) formulation for an unbalanced distribution system with distributed energy resources (DERs). In the proposed formulation, untransposed distribution lines, shunt elements of distribution lines, distribution transformers, and DERs are modeled. The proposed nonlinear IVACOPF model is linearized and convexified using the Taylor series. The accuracy of the proposed nonlinear and convex IVACOPF approaches for modeling unbalanced distribution systems is compared with OpenDSS and the widely used LinDistFlow method. The proposed accurate convex IVACOPF model has multiple applications for distribution systems management, planning, and operation. Applications of the proposed model on two key parts of advanced distribution management systems (ADMS)—DERs scheduling and state estimation—are presented in this article. The proposed models are tested on the distribution feeder of an electric utility in Arizona with 2100 primary nodes and a large number of rooftop photovoltaic units. The results confirm the accuracy and effectiveness of the proposed IVACOPF for both examined ADMS applications.
{"title":"Current–Voltage Unbalanced Distribution AC Optimal Power Flow for Advanced Distribution Management System Applications","authors":"Zahra Soltani;Mojdeh Khorsand;Shanshan Ma","doi":"10.1109/OJIA.2024.3367547","DOIUrl":"10.1109/OJIA.2024.3367547","url":null,"abstract":"Modern distribution systems are changing from passive load serving networks to active load and generation-inclusive networks. Accurate distribution systems modeling is critical for effective distribution system control, operation, and planning. This article proposes novel nonlinear and convex ac optimal power flow (ACOPF) models based on current–voltage (IVACOPF) formulation for an unbalanced distribution system with distributed energy resources (DERs). In the proposed formulation, untransposed distribution lines, shunt elements of distribution lines, distribution transformers, and DERs are modeled. The proposed nonlinear IVACOPF model is linearized and convexified using the Taylor series. The accuracy of the proposed nonlinear and convex IVACOPF approaches for modeling unbalanced distribution systems is compared with OpenDSS and the widely used LinDistFlow method. The proposed accurate convex IVACOPF model has multiple applications for distribution systems management, planning, and operation. Applications of the proposed model on two key parts of advanced distribution management systems (ADMS)—DERs scheduling and state estimation—are presented in this article. The proposed models are tested on the distribution feeder of an electric utility in Arizona with 2100 primary nodes and a large number of rooftop photovoltaic units. The results confirm the accuracy and effectiveness of the proposed IVACOPF for both examined ADMS applications.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"155-167"},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10440561","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139945644","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 : 2024-02-16DOI: 10.1109/OJIA.2024.3366524
Dennis Erdogan;Zhang Peng Du;Stefan Jakubek;Franz Holzinger;Christian Mayr;Christoph Hametner
Power hardware-in-the-loop (PHIL) testing has become indispensable for the rapid, modular, and cost-saving development of automotive components. This article focuses on PHIL tests composed of entire powertrains that exchange speed and torque signals with vehicle simulations. Previous studies pointed out the importance of promptly following the references from the virtual simulation environment to replicate realistic driving conditions and introduced control strategies to cope with the challenges associated with this setup. However, a comprehensive comparison of the different control strategies has not yet been carried out. To fill this gap, the concepts are first investigated in-depth in simulations and are then, rigorously validated on a state-of-the-art powertrain test bed under highly dynamic driving scenarios, including full-braking. Furthermore, an improvement of existing shaft torque control approaches, which are mainly based on feedforward control, is proposed to better compete with the other methods. The proposed extension shows higher resilience to low accuracy of torque actuators, while the other concepts exhibit greater robustness against time delays. The results from the direct comparisons are summarized and allow the appropriate selection of control strategies for specific use cases.
动力硬件在环（PHIL）测试已成为快速、模块化和节约成本的汽车零部件开发不可或缺的一部分。本文重点讨论由整个动力系统组成的 PHIL 测试，这些动力系统与车辆模拟交换速度和扭矩信号。以往的研究指出，必须及时遵循虚拟仿真环境中的参考数据来复制真实的驾驶条件，并引入了控制策略来应对与这种设置相关的挑战。然而，尚未对不同的控制策略进行全面比较。为了填补这一空白，我们首先在模拟环境中对这些概念进行了深入研究，然后在包括完全制动在内的高动态驾驶场景下，在最先进的动力总成试验台上进行了严格验证。此外，还对现有的轴扭矩控制方法（主要基于前馈控制）提出了改进建议，以更好地与其他方法竞争。所提出的扩展方案对扭矩执行器的低精度表现出更高的适应性，而其他概念则对时间延迟表现出更高的鲁棒性。对直接比较的结果进行了总结，以便为特定的使用案例选择适当的控制策略。
{"title":"Experimental Validation of Innovative Control Concepts for Powertrain Test Beds in Power Hardware-in-the-Loop Configuration","authors":"Dennis Erdogan;Zhang Peng Du;Stefan Jakubek;Franz Holzinger;Christian Mayr;Christoph Hametner","doi":"10.1109/OJIA.2024.3366524","DOIUrl":"10.1109/OJIA.2024.3366524","url":null,"abstract":"Power hardware-in-the-loop (PHIL) testing has become indispensable for the rapid, modular, and cost-saving development of automotive components. This article focuses on PHIL tests composed of entire powertrains that exchange speed and torque signals with vehicle simulations. Previous studies pointed out the importance of promptly following the references from the virtual simulation environment to replicate realistic driving conditions and introduced control strategies to cope with the challenges associated with this setup. However, a comprehensive comparison of the different control strategies has not yet been carried out. To fill this gap, the concepts are first investigated in-depth in simulations and are then, rigorously validated on a state-of-the-art powertrain test bed under highly dynamic driving scenarios, including full-braking. Furthermore, an improvement of existing shaft torque control approaches, which are mainly based on feedforward control, is proposed to better compete with the other methods. The proposed extension shows higher resilience to low accuracy of torque actuators, while the other concepts exhibit greater robustness against time delays. The results from the direct comparisons are summarized and allow the appropriate selection of control strategies for specific use cases.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"128-142"},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10438857","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139956910","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 : 2024-02-15DOI: 10.1109/OJIA.2024.3366415
Alessandro Faro;Alessandro Lidozzi;Marco di Benedetto;Luca Solero;Stefano Bifaretti
Repetitive controller provides a very low third harmonic dimension in the quantities under control. It exhibits an inherent issue when operated to track variable frequency references. The article deals with the analysis of the operating conditions when the controller is executed at variable frequency without any resynchronization with respect to the pulsewidth modulation carrier, which is the most common mode of operation. The delays introduced are then evaluated analytically concerning the sampling and output frequency that must be tracked. The proposed analysis allows obtaining the maximum delay affecting the control chain, which was introduced by the repetitive control desynched operation. The knowledge of the delay introduced in the control loops is at the basis of any control tuning procedure and gains selection, even when adaptive control strategies are used.
{"title":"Analytical Delay Evaluation for FPGA-Based Repetitive Controller in AC Variable Frequency Applications","authors":"Alessandro Faro;Alessandro Lidozzi;Marco di Benedetto;Luca Solero;Stefano Bifaretti","doi":"10.1109/OJIA.2024.3366415","DOIUrl":"10.1109/OJIA.2024.3366415","url":null,"abstract":"Repetitive controller provides a very low third harmonic dimension in the quantities under control. It exhibits an inherent issue when operated to track variable frequency references. The article deals with the analysis of the operating conditions when the controller is executed at variable frequency without any resynchronization with respect to the pulsewidth modulation carrier, which is the most common mode of operation. The delays introduced are then evaluated analytically concerning the sampling and output frequency that must be tracked. The proposed analysis allows obtaining the maximum delay affecting the control chain, which was introduced by the repetitive control desynched operation. The knowledge of the delay introduced in the control loops is at the basis of any control tuning procedure and gains selection, even when adaptive control strategies are used.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"117-127"},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10437987","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139945579","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 : 2024-02-13DOI: 10.1109/OJIA.2024.3365576
Muhammad Usama;Muhammad Naveed Aman
Cybersecurity is important in the realization of various smart grid technologies. Several studies have been conducted to discuss different types of cyberattacks and provide their countermeasures. The false command injection attack (FCIA) is considered one of the most critical attacks that have been studied. Various techniques have been proposed in the literature to detect FCIAs on different components of smart grids. The predominant focus of current surveys lies on FCIAs and detection techniques for such attacks. This article presents a survey of existing works on FCIAs and classifies FCIAs in smart grids according to the targeted component. The impacts of FCIAs on smart grids are also discussed. Subsequently, this article provides an extensive review of detection studies, categorizing them based on the type of detection technique employed.
{"title":"Command Injection Attacks in Smart Grids: A Survey","authors":"Muhammad Usama;Muhammad Naveed Aman","doi":"10.1109/OJIA.2024.3365576","DOIUrl":"10.1109/OJIA.2024.3365576","url":null,"abstract":"Cybersecurity is important in the realization of various smart grid technologies. Several studies have been conducted to discuss different types of cyberattacks and provide their countermeasures. The false command injection attack (FCIA) is considered one of the most critical attacks that have been studied. Various techniques have been proposed in the literature to detect FCIAs on different components of smart grids. The predominant focus of current surveys lies on FCIAs and detection techniques for such attacks. This article presents a survey of existing works on FCIAs and classifies FCIAs in smart grids according to the targeted component. The impacts of FCIAs on smart grids are also discussed. Subsequently, this article provides an extensive review of detection studies, categorizing them based on the type of detection technique employed.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"75-85"},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10433776","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139945611","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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