Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131196
DeAndre A. Johnson, Rayshaun L. Wheeler, J. Lambert
Across industry, government, and military, an increase in risk and uncertainty of market effects has stimulated innovations in risk identification and management. Complex distributed systems and enterprises are faced with related challenges, including data configuration of business processes. With disruptions to product and service supply chains etc., data on past decisions, prior knowledge, and outcomes are analyzed to improve the success of timely risk responses and mitigation. This paper describes an innovation to a methodology for identifying sources of risk and merging them with risk descriptions of subject matter experts in a business process model. In particular, this methodology aids in the identification of sources of risk and related causal relationships, enabling users to create defense mechanisms prior to the occurrence of supply chain disruptions. The unique new focus of this paper is the IDEF3 business process model used to capture precedence and causality relations. The approach is demonstrated with an example of a business process of an industrial paint shop. Future efforts will merge IDEF models 1, 2, and 3 for identifying and addressing sources of risk.
{"title":"Risk Description Augmenting a Business Process Model","authors":"DeAndre A. Johnson, Rayshaun L. Wheeler, J. Lambert","doi":"10.1109/SysCon53073.2023.10131196","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131196","url":null,"abstract":"Across industry, government, and military, an increase in risk and uncertainty of market effects has stimulated innovations in risk identification and management. Complex distributed systems and enterprises are faced with related challenges, including data configuration of business processes. With disruptions to product and service supply chains etc., data on past decisions, prior knowledge, and outcomes are analyzed to improve the success of timely risk responses and mitigation. This paper describes an innovation to a methodology for identifying sources of risk and merging them with risk descriptions of subject matter experts in a business process model. In particular, this methodology aids in the identification of sources of risk and related causal relationships, enabling users to create defense mechanisms prior to the occurrence of supply chain disruptions. The unique new focus of this paper is the IDEF3 business process model used to capture precedence and causality relations. The approach is demonstrated with an example of a business process of an industrial paint shop. Future efforts will merge IDEF models 1, 2, and 3 for identifying and addressing sources of risk.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127773866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131080
Guilherme Palazzo, E. Sbruzzi, C. Nascimento, M. Leles
Over the past years, there has been a growing interest in cryptocurrency markets. In this context, price forecasting initiatives that aid in the decision-making process of investors and market participants have emerged and drawn the interest of academia and the financial technology industry. In this paper, we present a machine learning classification model that forecasts the price direction - top, modeled as 1, or neutral or bottom, modeled as 0 - of Litecoin (LTC) over the forecast horizon equivalent to volume-wise samples of 100 thousand LTC. For modeling, we adopt a random forest classifier, achieving an Area Under the Receiver Operating Characteristic curve (AUROC or AUC) score of 0.65 on the hold-out, out-of-time test subset.
{"title":"Predicting Litecoin price movement in a pre-defined trading volume window using Random Forest model","authors":"Guilherme Palazzo, E. Sbruzzi, C. Nascimento, M. Leles","doi":"10.1109/SysCon53073.2023.10131080","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131080","url":null,"abstract":"Over the past years, there has been a growing interest in cryptocurrency markets. In this context, price forecasting initiatives that aid in the decision-making process of investors and market participants have emerged and drawn the interest of academia and the financial technology industry. In this paper, we present a machine learning classification model that forecasts the price direction - top, modeled as 1, or neutral or bottom, modeled as 0 - of Litecoin (LTC) over the forecast horizon equivalent to volume-wise samples of 100 thousand LTC. For modeling, we adopt a random forest classifier, achieving an Area Under the Receiver Operating Characteristic curve (AUROC or AUC) score of 0.65 on the hold-out, out-of-time test subset.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128204144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131114
H. Silva, M. Vieira, Augusto J. V. Neto
Safety-Critical Systems (SCS) stand for those systems designed to tackle events that could potentially cause human injury or loss of life, significant property damage, financial loss, or damage to the environment, among others. Modern SCS are in transport, infrastructure, medicine, nuclear engineering, recreation, and many other fields. Nevertheless, SCS are prone to various attacks aiming to explore their inherent complexity and broad attack surface to jeopardize essential services and assets. Survivability is key to protecting SCS through integrating preventive, reactive, and tolerant defenses. This paper stands out by analyzing the survivability aspects of SCS under attack through a systematic literature review of recently published articles. Based on the review, we devise a classification to separate the studies that focus on survivability for SCS from those that deal with related aspects, such as resistance, recognition, or tolerance to attacks. Further, we expose literature limitations indicating why there is still no guaranteed survivability of SCS in the presence of attacks.
{"title":"Are safety-critical systems really survivable to attacks?","authors":"H. Silva, M. Vieira, Augusto J. V. Neto","doi":"10.1109/SysCon53073.2023.10131114","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131114","url":null,"abstract":"Safety-Critical Systems (SCS) stand for those systems designed to tackle events that could potentially cause human injury or loss of life, significant property damage, financial loss, or damage to the environment, among others. Modern SCS are in transport, infrastructure, medicine, nuclear engineering, recreation, and many other fields. Nevertheless, SCS are prone to various attacks aiming to explore their inherent complexity and broad attack surface to jeopardize essential services and assets. Survivability is key to protecting SCS through integrating preventive, reactive, and tolerant defenses. This paper stands out by analyzing the survivability aspects of SCS under attack through a systematic literature review of recently published articles. Based on the review, we devise a classification to separate the studies that focus on survivability for SCS from those that deal with related aspects, such as resistance, recognition, or tolerance to attacks. Further, we expose literature limitations indicating why there is still no guaranteed survivability of SCS in the presence of attacks.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130584665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131224
Anthony Abi Badra, Ombeline Aïello, J. Chaudemar
Unmanned Aerial Vehicles (UAVs) are complex systems whose complexity lies mainly in the plurality of their missions. Among aerospace vehicles with various missions (aircraft, satellite, etc.), UAVs have the advantage of being easily scalable due to their small size. Thus, the missions developed should be relatively easily implementable, raising the need for genericity. For this reason, this paper discusses multiple tools and methods used to model a UAV mission. Starting from a Simulink State flow model, a top-level mission architecture was created, and operational, functional, and logical analyses were conducted using an ARCADIA/Capella based approach.
{"title":"Applying a Model-Based Systems Engineering Approach to Model an Unmanned Aerial Vehicle Mission","authors":"Anthony Abi Badra, Ombeline Aïello, J. Chaudemar","doi":"10.1109/SysCon53073.2023.10131224","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131224","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) are complex systems whose complexity lies mainly in the plurality of their missions. Among aerospace vehicles with various missions (aircraft, satellite, etc.), UAVs have the advantage of being easily scalable due to their small size. Thus, the missions developed should be relatively easily implementable, raising the need for genericity. For this reason, this paper discusses multiple tools and methods used to model a UAV mission. Starting from a Simulink State flow model, a top-level mission architecture was created, and operational, functional, and logical analyses were conducted using an ARCADIA/Capella based approach.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128402544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131274
Yuki Tomita, N. Kohtake
Developing regions are vulnerable to disaster with limited ICT technology, and there are challenges in reducing flood damage through early warning systems. As a countermeasure, Community-based Flood Early Warning System (CBFEWS) based on sociotechnical systems developed by integrating low-cost technologies and human-centered communication networks that do not rely solely on governmental early warnings is being promoted by several disaster relief organizations as an affordable option in developing regions. While the effectiveness of CBFEWS has been proven, challenges remain in maintaining the effectiveness of the system over the long term. This study proposes a model-driven design parameter exploration method for CBFEWS-implementing organizations to develop strategies for sustaining the effectiveness of CBFEWS over years. The dynamic probabilistic performance evaluation is designed based on probabilistic risk assessment (PRA) and the proposal assists in identifying factors that are sensitive to successfully maintaining system effectiveness. The factors are selected based on a sociotechnical systems perspective such as social preparedness, component failure rate, and system performance. Based on the output from this model, organizations can design, operate, and maintain effective CBFEWS and strengthen system resilience. This paper demonstrates the proposed methodology to show how the model-driven design parameter exploration can facilitate a discussion of increasing CBFEWS sustainability and resiliency.
{"title":"Design parameter exploration for community-based flood early warning system with dynamic probabilistic performance assessment approach","authors":"Yuki Tomita, N. Kohtake","doi":"10.1109/SysCon53073.2023.10131274","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131274","url":null,"abstract":"Developing regions are vulnerable to disaster with limited ICT technology, and there are challenges in reducing flood damage through early warning systems. As a countermeasure, Community-based Flood Early Warning System (CBFEWS) based on sociotechnical systems developed by integrating low-cost technologies and human-centered communication networks that do not rely solely on governmental early warnings is being promoted by several disaster relief organizations as an affordable option in developing regions. While the effectiveness of CBFEWS has been proven, challenges remain in maintaining the effectiveness of the system over the long term. This study proposes a model-driven design parameter exploration method for CBFEWS-implementing organizations to develop strategies for sustaining the effectiveness of CBFEWS over years. The dynamic probabilistic performance evaluation is designed based on probabilistic risk assessment (PRA) and the proposal assists in identifying factors that are sensitive to successfully maintaining system effectiveness. The factors are selected based on a sociotechnical systems perspective such as social preparedness, component failure rate, and system performance. Based on the output from this model, organizations can design, operate, and maintain effective CBFEWS and strengthen system resilience. This paper demonstrates the proposed methodology to show how the model-driven design parameter exploration can facilitate a discussion of increasing CBFEWS sustainability and resiliency.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131178426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131050
Daniel Dunbar, Maximilian Vierlboeck, M. Blackburn
This paper uses Natural Language Processing to provide augmented intelligence assistance to the resource intensive task of aligning systems engineering artifacts, namely text requirements and system models, with ontologies. Ontologies are a key enabling technology for digital, multidisciplinary interoperability. The approach presented in this paper combines the efficiency of statistical based natural language processing to process large sets of data with expert verification of output to enable accurate alignment to ontologies in a time efficient manner. It applies this approach to an example from the telecommunications domain to demonstrate the workflows and highlight key points in the process. Enabling easier, faster alignment of systems engineering artifacts with ontologies allows for a holistic view of a system under design and enables interoperability between tools and domains.
{"title":"Use of Natural Language Processing in Digital Engineering Context to Aid Tagging of Model","authors":"Daniel Dunbar, Maximilian Vierlboeck, M. Blackburn","doi":"10.1109/SysCon53073.2023.10131050","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131050","url":null,"abstract":"This paper uses Natural Language Processing to provide augmented intelligence assistance to the resource intensive task of aligning systems engineering artifacts, namely text requirements and system models, with ontologies. Ontologies are a key enabling technology for digital, multidisciplinary interoperability. The approach presented in this paper combines the efficiency of statistical based natural language processing to process large sets of data with expert verification of output to enable accurate alignment to ontologies in a time efficient manner. It applies this approach to an example from the telecommunications domain to demonstrate the workflows and highlight key points in the process. Enabling easier, faster alignment of systems engineering artifacts with ontologies allows for a holistic view of a system under design and enables interoperability between tools and domains.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"23 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134580162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131090
Amy Eddy, J. Daily
Life Cycle Systems Engineering is an iterative process which relies on feedback loops from the operational phase to facilitate continuous system improvement tasks so that systems stay relevant in changing operational environments. In the aerospace defense industry, real world operational data can be used as feedback to identify impacts to the system unrelated to the physical product. Operational data includes both physical system performance metrics, as well as performance of all the supporting non-product related system characteristics called operational feasibility elements. Operational feasibility elements such as processes, people, training, supportability, and maintainability play a significant role in overall system performance. Operational data can be used to inform the next iteration of the systems engineering process and enables updates to policy/processes, models, simulations, and analyses in addition to more common physical product updates. Failure to utilize operational data as validation of system performance may result in significant gaps understanding why system failure occurs, thus rendering technical solutions inadequate to resolve performance issues since the true root cause of the enterprise system failure is unknown.
{"title":"Systems Engineering Methods for Validation and Verification of Changes to Legacy Fielded Systems","authors":"Amy Eddy, J. Daily","doi":"10.1109/SysCon53073.2023.10131090","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131090","url":null,"abstract":"Life Cycle Systems Engineering is an iterative process which relies on feedback loops from the operational phase to facilitate continuous system improvement tasks so that systems stay relevant in changing operational environments. In the aerospace defense industry, real world operational data can be used as feedback to identify impacts to the system unrelated to the physical product. Operational data includes both physical system performance metrics, as well as performance of all the supporting non-product related system characteristics called operational feasibility elements. Operational feasibility elements such as processes, people, training, supportability, and maintainability play a significant role in overall system performance. Operational data can be used to inform the next iteration of the systems engineering process and enables updates to policy/processes, models, simulations, and analyses in addition to more common physical product updates. Failure to utilize operational data as validation of system performance may result in significant gaps understanding why system failure occurs, thus rendering technical solutions inadequate to resolve performance issues since the true root cause of the enterprise system failure is unknown.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133311018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131060
Emi Aoki, Bach Tran, Vinh Tran, Kimseng Soth, C. Thompson, S. Tripathy, K. Chandra, Shivakumar Sastry
Augmented Reality (AR) devices offer novel capabilities that can be exploited in AR systems to positively impact human-machine interactions in a variety of future-work and education contexts. This paper presents a systems model for a no-code AR systems framework that can be used to create AR applications that present just-in-time informatics to assist and guide users in the completion of complex task sequences while ensuring operator and environment safety. The salient structural and behavioral aspects of the system, and key use cases are modeled using the Systems Modeling Language (SysML). Representative examples of the model are presented using use case, block definition, internal block, activity, and state-machine diagrams. These models offer new insights into how AR capabilities can be integrated with a variety of engineered systems. In the future such SysML models can steer the design of new tools and an ontology to strengthen connections to domain knowledge.
{"title":"Representing Augmented Reality Applications in Systems Modeling Language","authors":"Emi Aoki, Bach Tran, Vinh Tran, Kimseng Soth, C. Thompson, S. Tripathy, K. Chandra, Shivakumar Sastry","doi":"10.1109/SysCon53073.2023.10131060","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131060","url":null,"abstract":"Augmented Reality (AR) devices offer novel capabilities that can be exploited in AR systems to positively impact human-machine interactions in a variety of future-work and education contexts. This paper presents a systems model for a no-code AR systems framework that can be used to create AR applications that present just-in-time informatics to assist and guide users in the completion of complex task sequences while ensuring operator and environment safety. The salient structural and behavioral aspects of the system, and key use cases are modeled using the Systems Modeling Language (SysML). Representative examples of the model are presented using use case, block definition, internal block, activity, and state-machine diagrams. These models offer new insights into how AR capabilities can be integrated with a variety of engineered systems. In the future such SysML models can steer the design of new tools and an ontology to strengthen connections to domain knowledge.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131836845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131084
Mingrui Yu, Ho-fung Leung
Unmanned aerial systems (UAS) are increasingly being deployed in civilian and commercial areas. The application of machine learning in UAS image analysis greatly promotes the progress of target detection and tracking algorithms. However, current object detection and tracking system algorithm can hardly be applied to detect aerial targets. Because the view of UAS changes and rotates quickly during the flight. In this paper, we propose a fast and accurate real-time small object detection system based on a two-stage architecture. The proposed addresses the small object detection challenges by combining the traditional target detection with deep learning. More precisely, it uses conventional background subtraction and deep learning algorithm to get the initial detection box, and then use target tracking to get the final result. We evaluated our approach on the small object data sets. Experimental results show that the proposed method has improved the aerial object detection performance compared with other conventional approaches.
{"title":"Small-Object Detection for UAV-Based Images","authors":"Mingrui Yu, Ho-fung Leung","doi":"10.1109/SysCon53073.2023.10131084","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131084","url":null,"abstract":"Unmanned aerial systems (UAS) are increasingly being deployed in civilian and commercial areas. The application of machine learning in UAS image analysis greatly promotes the progress of target detection and tracking algorithms. However, current object detection and tracking system algorithm can hardly be applied to detect aerial targets. Because the view of UAS changes and rotates quickly during the flight. In this paper, we propose a fast and accurate real-time small object detection system based on a two-stage architecture. The proposed addresses the small object detection challenges by combining the traditional target detection with deep learning. More precisely, it uses conventional background subtraction and deep learning algorithm to get the initial detection box, and then use target tracking to get the final result. We evaluated our approach on the small object data sets. Experimental results show that the proposed method has improved the aerial object detection performance compared with other conventional approaches.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"9 Suppl 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133257932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131089
J. Sarlashkar, B. Surampudi, Venkata R. Chundru, W. Downing
Battery energy storage system (BESS) is a key enabler of the modern renewable- and inverter-heavy electric grid. It is generally expected [1] that the BESS will see a more demanding duty in the modern grid as it delivers a multitude of ancillary services dispatched simultaneously (stacked duty) and sequentially (mixed duty). Such harsher duty will entail larger operating envelope of timescale, power, and state-of-charge (SOC), and further elevate the issues of BESS performance and safety. Lithium plating (lithium deposition in general) is widely reported as a significant aging and failure mechanism when charging the BESS at high current and high SOC [2], [3]. In this work we describe an extension to the so-called pseudo electrochemical impedance spectroscopy (EIS) method to detect and quantify general degradation in performance and specifically to detect lithium plating. The pseudo-EIS protocol is amenable to implementation in a battery management system (BMS) for real-time assessment of performance and safety. In particular, it enables proactive management of current profile during (fast) charging to trade-off performance and safety. Further, it can also be used offline to gauge state-of-health (SOH) of second-life batteries before redeployment.
{"title":"Pseudo Electrochemical Impedance Spectroscopy Method for In-Situ Performance and Safety Assessment of Lithium-Ion Battery Energy Storage Systems for Grid-Scale Applications","authors":"J. Sarlashkar, B. Surampudi, Venkata R. Chundru, W. Downing","doi":"10.1109/SysCon53073.2023.10131089","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131089","url":null,"abstract":"Battery energy storage system (BESS) is a key enabler of the modern renewable- and inverter-heavy electric grid. It is generally expected [1] that the BESS will see a more demanding duty in the modern grid as it delivers a multitude of ancillary services dispatched simultaneously (stacked duty) and sequentially (mixed duty). Such harsher duty will entail larger operating envelope of timescale, power, and state-of-charge (SOC), and further elevate the issues of BESS performance and safety. Lithium plating (lithium deposition in general) is widely reported as a significant aging and failure mechanism when charging the BESS at high current and high SOC [2], [3]. In this work we describe an extension to the so-called pseudo electrochemical impedance spectroscopy (EIS) method to detect and quantify general degradation in performance and specifically to detect lithium plating. The pseudo-EIS protocol is amenable to implementation in a battery management system (BMS) for real-time assessment of performance and safety. In particular, it enables proactive management of current profile during (fast) charging to trade-off performance and safety. Further, it can also be used offline to gauge state-of-health (SOH) of second-life batteries before redeployment.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133208936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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