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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Akash Samanta Chandan Chetri Dominic Karnehm Antje Neve Sheldon Williamson Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada Institute of Intelligent Distributed Systems Bundeswehr University Munich Germany

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

The experimental studies presented in this paper reveal that existing thermal management systems (TMS) and temperature-informed charging algorithms exhibit a response time lag of at least 5.3 minutes due to their reliance on surface temperature measurements. The results indicate that changes in the internal thermal state of lithium-ion batteries (LIBs), induced by variations in charging currents, take an average of 2 minutes to manifest on the battery surface, particularly evident in cylindrical cells. Current thermal management systems for automotive battery packs solely rely on surface temperature measurements, neglecting the approximately 5.8°C temperature difference between the core and surface in TMS control. Consequently, changes in the battery's thermal state due to internal heat losses are not promptly detected by surface-mounted temperature sensors. This delayed response time accelerates battery degradation and increases the risk of thermal runaway events. In this study, temperature-informed fast charging algorithms, tested under various ambient conditions for LIBs, along with a comparative analysis, demonstrate that response time can be reduced by at least 2 minutes by considering internal temperature rather than relying solely on surface temperature measurements. Moreover, accounting for the temperature difference between the core and surface facilitates rapid TMS control and health-conscious fast charging, thereby mitigating the risk of thermal runaway events.

关键词： Temperature measurement Temperature sensors Heating systems Sensitivity analysis Surface charging Thermal management Time measurement Fast charging Time factors Thermal degradation

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Voltage Relaxation Pattern Recognition for Efficient Sorting of Healthy Cells for Second-Life Applications of Retired Electric Vehicle Batteries

Voltage Relaxation Pattern Recognition for Efficient Sorting...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Akash Samanta Dominic Karnehm Antje Neve Sheldon Williamson Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada Institute of Intelligent Distributed Systems University of the Bundeswehr Munich Neubiberg Germany

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

First-generation electric vehicle (EV) batteries are now retiring from their first life with 70–80%of their initial capacity and are becoming available in the market. To harness the remaining capacity of retired batteries before they reach the end of their life, researchers have proposed various methods, including backup and emergency power supplies for homes, grid-tied stationary energy storage, and storage for renewable energy applications. These applications are collectively termed second-life applications. The first step in utilizing these retired batteries is the selection of healthy cells, as cells in an EV battery pack do not degrade evenly. State-of-the-art cell selection and sorting techniques are either ineffective for industrial-grade applications or highly time-consuming processes. Therefore, this paper proposes a charging voltage relaxation pattern recognition method to efficiently sort healthy cells, powered by data-driven machine learning algorithms. A wide range of battery cycling data collected under different ambient and charging conditions is used for training, testing, and validating the proposed sorting strategy. Furthermore, a comparative analysis is conducted to demonstrate the effectiveness of the proposed strategy compared to state-of-the-art methods.

关键词： Training Renewable energy sources Machine learning algorithms Clustering algorithms Voltage Electric vehicles Batteries

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Five-layer IoT and Fog Computing Framework Towards Digital Twinning of Battery Management systems for e-Transportation

Five-layer IoT and Fog Computing Framework Towards Digital T...

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Workshop on Smart Grid and Renewable Energy (SGRE)

作者： Dominic Karnehm Akash Samanta Antje Neve Sheldon Williamson Institute of Intelligent Distributed Systems University of the Bundeswehr Munich Neubiberg Germany Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada

It is needless to mention that the proven capability of cloud computing and digital twin-based monitoring and control systems will play a major role in the implementation of digital twin-based lithium-ion battery management systems (BMS) for e-transportation. In this context, the combination of the Internet of Things (IoT) and fog computing emerges as an enabling technology that facilitates bidirectional data communication and processing. This paper proposes a five-layer IoT framework for the implementation of cloud-based battery monitoring and BMS. Additionally, it critically analyzes the existing IoT frameworks applied to BMS and justifies the suitability of the five-layer architecture. Furthermore, the advantages of fog computing, such as low latency, fault tolerance, limitless systems, multiple applications, and shared responsibility, are discussed. The paper also explores four previously proposed computing-enabled architectures: centralized, hybrid, distributed, and hybrid-distributed computing. Moreover, the potential of utilizing hybrid computing architectures, incorporating fog computing as a supplement to cloud computing, is highlighted to address fault, privacy, or latency issues in cloud-based BMS.

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CAC 2.0: A Corrupt and Correct Logic Locking Technique Resilient to Structural Analysis Attacks

CAC 2.0: A Corrupt and Correct Logic Locking Technique Resil...

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Latin American Test Workshop, LATW

作者： Levent Aksoy Muhammad Yasin Samuel Pagliarini Department of Computer Systems Tallinn University of Technology Tallinn Estonia Department of Computer and Software Engineering National University of Sciences and Technology Islamabad Pakistan Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh USA

ISBN: (数字)9798350365559

ISBN: (纸本)9798350365566

Logic locking proposed to protect integrated circuits from serious hardware threats has been studied extensively over a decade. In these years, many logic locking techniques have been proven to be broken. The state-of-the-art logic locking techniques, including the prominent corrupt and correct (CAC) technique, are resilient to satisfiability (SAT)-based and removal attacks, but vulnerable to structural analysis attacks. To overcome this drawback, this paper introduces an improved version of CAC, called CAC 2.0, which increases the search space of structural analysis attacks using obfuscation. To do so, CAC 2.0 locks the original circuit twice, one after another, on different nodes with different number of protected primary inputs using CAC, while hiding original protected primary inputs among decoy primary inputs. This paper also introduces an open source logic locking tool, called HIID, equipped with well-known techniques including CAC 2.0. Our experiments show that CAC 2.0 is resilient to existing SAT-based, removal, and structural analysis attacks. To achieve this, it increases the number of key inputs at most 4× and the gate-level area between 30.2% and 0.8% on circuits with low and high complexity with respect to CAC.

关键词： Integrated circuits Logic gates Hardware Complexity theory Delays Resilience

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A Compact 28 GHz Millimeter Wave Antenna for Future Wireless Communication

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computers, Materials & Continua 2022年第7期72卷 301-314页

作者： Shahid Khan Adil Bashir Haider Ali Abdul Rauf Mohamed Marey Hala Mostafa Ikram Syed LCOMS ASECUniversity de LorraineMetz57070France Department of Electrical and Computer Engineering Comsats University IslamabadAbbottabad Campus22060Pakistan Electrical Engineering Department Bahauddin Zakariya UniversityMultan60800Pakistan Department of Electronics Technology University of TechnologyNowshera24100Pakistan Department of Electrical Engineering National University of Sciences and TechnologyH-12Islamabad44000Pakistan Smart Systems Engineering Laboratory College of EngineeringPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Software Engineering Military College of SignalsNational University of Sciences and TechnologyIslamabad44000Pakistan

This article presents a novel modified chuck wagon dinner bell shaped millimeter wave(mm-wave)antenna at 28 *** proposed design has ultra-thin Rogers 5880 substrate with relative permittivity of *** design consists of T shaped resonating elements and two open ended side *** desired 28 GHz frequency response is achieved by careful parametric modeling of the proposed *** maximum achieved single element gain at the desired resonance frequency is 3.45 *** efficiency of the proposed design over the operating band is more than 88%.The impedance bandwidth achieved for−10 dB reference value is nearly 2.9 *** proposed antenna is transformed into four element linear array which increases the gain up to 10.5 *** fabricated prototype is tested for the measured *** is observed that measured results closely match the simulated *** considering its simple structure and focused radiation patterns,the proposed design is well suited for IoT(Internet of Things),mmWave microwave sensing,5G and future RF(Radio Frequency)frontends.

关键词： RF front-ends mmWave partial ground plane 28 GHz IoT 5G antenna

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KRATT: QBF-Assisted Removal and Structural Analysis Attack Against Logic Locking

KRATT: QBF-Assisted Removal and Structural Analysis Attack A...

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Design, Automation and Test in Europe Conference and Exhibition

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

This paper introduces KRATT, a removal and structural analysis attack against state-of-the-art logic locking techniques, such as single and double flip locking techniques (SFLTs and DFLTs). KRATT utilizes powerful quantified Boolean formulas (QBFs), which have not found widespread use in hardware security, to find the secret key of SFLTs for the first time. It can handle locked circuits under both oracle-less (OL) and oracle-guided (OG) threat models. It modifies the locked circuit and uses a prominent OL attack to make a strong guess under the OL threat model. It uses a structural analysis technique to identify promising protected input patterns and explores them using the oracle under the OG model. Experimental results on ISCAS'85, ITC'99, and HeLLO: CTF'22 benchmarks show that KRATT can break SFLTs using a QBF formulation in less than a minute, can decipher a large number of key inputs of SFLTs and DFLTs with high accuracy under the OL threat model, and can easily find the secret key of DFLTs under the OG threat model. It is shown that KRATT outperforms publicly available OL and OG attacks in terms of solution quality and run-time.

关键词： Threat modeling Analytical models Hardware security Circuits Benchmark testing Complexity theory Integrated circuit modeling

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IC Layouts Patterns Topological Profiling Using Directional Geometrical Kernels 2

IC Layouts Patterns Topological Profiling Using Directional ...

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DTCO and Computational Patterning II 2023

作者： Hamed, Ahmed Hamed Fathi El-Sewefy, Omar Khalaf, Sara Hegazy, Hazem Dessouky, Mohamed Salem, Ashraf Ain Shams University Faculty of Engineering Electronics Engineering and Electrical Communications Department Cairo11835 Egypt Ain Shams University Faculty of Engineering Computer and Systems Engineering Department Cairo11835 Egypt Siemens EDA Calibre Semi-Manufacturing Solutions Siemens Digital Industries Software Cairo11535 Egypt Siemens EDA Calibre Design-to-Silicon Siemens Digital Industries Software Cairo11535 Egypt

ISBN: (纸本)9781510660977

As the semiconductor manufacturing technology node scales down in the deep submicron domain, hotspot detection becomes more challenging and geo-contextually dependent than ever before. The need to profile IC layout patterns based on geometrical commonalities becomes a significant demand either during IC layout design or manufacturing phases. Identified hotspots during the manufacturing phase are usually correlated to specific geometrical configurations sensitive to the lithography process or other manufacturing processes. Accordingly, identifying similar geometrical configurations is an important step toward locating potential hotspots. Once these hotspots are identified, their patterns can be provided to the router to avoid using these patterns and find other valid alternatives. Furthermore, in the IC design sign-off phase or Design Rules Check (DRC), layout profiling can identify patterns with high commonalities to these problematic patterns that potentially lead to a yield loss. In this paper, we introduce automated IC layout patterns topological profiling approach using Directional Geometrical Kernels (DGKs) to capture the context of patterns around a Point-Of-Interest (POI) in an IC layout, such as a hotspot. The DGKs pattern representation provides a direct one-to-one mapping with physical geometrical measurements centered by the POI and doesn't need further feature extraction models or maps used by other pixelized gridded image-based or density-based representations, which are both time and computational resources-consuming. The DGKs are decomposed into topological and dimensional components. This makes the mechanism of patterns topological profiling not in need of complex models and can be precisely fine controlled to produce adequate patterns profiling granularity that is not easily approached by other patterns profiling alternatives. © 2023 SPIE.

关键词： Integrated circuits

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Leveraging Digital Twins and Demand Side Recommender Chatbot for Optimizing Smart Grid Energy Efficiency

Leveraging Digital Twins and Demand Side Recommender Chatbot...

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2023 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2023

作者： Onile, Abiodun E. Belikov, Juri Petlenkov, Eduard Levron, Yoash Tallinn University of Technology Department of Software Science Akadeemia tee 15a Tallinn12618 Estonia Tallinn University of Technology Department of Computer Systems Akadeemia tee 15a Tallinn12618 Estonia Technion - Israel Institute of Technology Faculty of Electrical & Computer Engineering Haifa3200003 Israel

ISBN: (纸本)9798350327748

Electricity consumers often face the challenge of selecting an optimal plan for saving energy. Strategic energy management and monitoring plays a key role in overcoming these challenges. Developments around Industry 5.0 powered smart grid proffers adequate solutions which allows end-consumers to monitor their energy performance towards effecting demand side recommendation services. Specific problems where end-users are likely to ignore recommended advice exists, thereby contributing to widening 'knowledge-action gap'. An ensemble of hybrid digital twins (DT) asset modelling based on ordinary differential equation (ODE) physics engine and data driven recurrent neural network (RNN) prediction approach alongside PageRank based asset behavior scoring algorithm deployed for demand side recommender and generative pre-trained transformers (GPT) based conversational chatbot technology show effectiveness in engaging and extending end-consumers interests in recommended advice. The novelty of the study lies in extending current scope of demand side recommender scheme via conversational chatbot interface for DT of electricity grid assets that better engage and monitors end-user's energy behavior while offering appropriate energy efficiency advice towards achieving energy conservation goals of smart grid consumers. Extensive experiments, including evaluation of end-user studies, revealed the effectiveness of proposed approach in terms of improved recommendation quality and user engagement towards net electricity demand reduction. © 2023 IEEE.

关键词： Energy efficiency

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Applications of Digital Twins for Demand Side Recommendation Scheme with Consumer Comfort Constraints

Applications of Digital Twins for Demand Side Recommendation...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Onile, Abiodun E. Belikov, Juri Petlenkov, Eduard Levron, Yoash Department of Software Science Tallinn University of Technology Akadeemia tee 15a Tallinn12618 Estonia Department of Computer Systems Tallinn University of Technology Akadeemia tee 15a Tallinn12618 Estonia Faculty of Electrical and Computer Engineering Technion—Israel Institute of Technology Haifa3200003 Israel

ISBN: (纸本)9798350396782

The next evolution of traditional energy systems towards smart grid will require end-consumers to actively participate and make informed decisions regarding their energy usage. Industry 4.0 facilitates such progress by allowing more advanced analytics and creating means for end-consumers and distributed grid assets to be modelled as their Digital twins (DT) equivalents, paving the way for asset-level analytics. Note-worthily, consumers’ comfort is crucial towards promotion of easy adoption of such models from consumers’ perspectives. This study presents the application of hybrid DT and multiagent reinforcement learning models for real-time estimation of end-consumers future energy behaviors while generating actionable recommendation feedback for improving their energy efficiency and enhancing end-user comfort. © 2023 IEEE European Union.

关键词： Consumer comfort Demand side recommender system Distributed power systems Hybrid digital twins Industry 5.0

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Emerging Role of Industry 5.0 Digital Twins in Demand Response Electricity Market and Applications

Emerging Role of Industry 5.0 Digital Twins in Demand Respon...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

ISBN: (纸本)9798350396782

Traditional power system is facing challenges demanding new operational requirements to meet targets of Net Zero Emissions by 2050. Aggregators are playing progressively important role in the demand response (DR) electricity market but are often riddled with deep level of market monopoly and lack of transparency/secrecy. Emerging real-time information technology (IT) applications and novel modelling of digital twins (DT) of individual electricity assets are challenging this position by promising improvements and openness that allows TSO direct access to available demand side flexibility. Additionally, DT technologies are facilitating how demand response services are delivered to end-users by allowing individual assets participation at the atomic level. In this study, the application potentials of assets’ DT in participating in the demand response electricity market was examined. Again, an overview of DT applications for DR was conducted. The novelty of this study is highlighted in development of new approach that facilitates individual end-user assets’ contribution to demand response efforts. The research identifies key useful questions that might serve as inspiration for stakeholders and policy-makers to further close existing gaps in the field of DT, smart-grid and demand response. © 2023 European Union.

关键词： Aggregators demand response digital twins Industry 5.0 smart-grid

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