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2023 IEEE International Conference on Energy technologies for Future Grids, ETFG 2023

作者： Anees, Mohammad Anas Daula Siddique, Marif Mekhilef, Saad Mubin, Marizan Binti Seyedmahmoudian, Mehdi Stojcevski, Alex National University of Singapore Dept. of Electrical and Computer Engineering Singapore University of Malaya Dept. of Electrical Engineering Malaysia Swinburne University of Tech. School of Software and Electrical Engineering. Australia

ISBN: (纸本)9781665471640

This paper presents a novel fifteen-level two-source inverter topology that is reliable against source outages. The topology has two DC sources, a total of ten switches, and four DC-link capacitors. Level-shifted PWM is used to generate the required number of levels. Simulations are performed for normal operation as well as for the source outage conditions. The proposed topology is able to generate multi-level output waveform satisfactorily even at the advent of source outages. The simulation results for the source outages are presented for both static and dynamic conditions along with the THD measurements. © 2023 IEEE.

关键词： dc source failure fault tolerance level shifted PWM multilevel inverters (MLIs) reliability

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Building the metaverse using digital twins at all scales,states,and relations

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Virtual Reality & Intelligent Hardware 2022年第6期4卷 459-470页

作者： Zhihan LV Shuxuan XIE Yuxi LI M.Shamim HOSSAIN Abdulmotaleb El SADDIK Department of Game Design Faculty of ArtsUppsala UniversitySweden College of Computer Science and Technology Qingdao UniversityQingdaoChina Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Electrical Engineering and Computer Science(EECS) University of OttawaOttawaOntarioCanada

Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the *** objects can be at the micro-,meso-,or *** Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain ***,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a Digital Twins model for social ***,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the Digital Twins model.

关键词： Digital twins Metaverse Sensor

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Effective power electronics understanding using circuit simulation

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IEEE Potentials 2023年第6期42卷 25-31页

作者： Surya, Sumukh Chhetri, Ahilya Arjun, M. Williamson, Sheldon Bosch Global Software Technologies Pvt. Limited Senior Engineer Bangalore India Cactus Communications Engineering and Technology Mumbai400093 India BOsch Global Software Technologies Pvt. Limited Technical Specialist Bangalore560030 India Ontario Tech University Faculty of Engineering and Applied Sciences OshawaONLIG 0C5 Canada

Learning power electronic circuits through simulation is one of the effective methods available for students and researchers to understand the subject effectively. This article aims at providing a panoramic view of different software tools used for simulating electrical circuits, enabling students to make an appropriate choice among various tools for a specific application. In this regard, a simple buck converter operating in the continuous conduction mode (CCM) is considered and realized using two different approaches, viz., coding and modeling using the Matrix Laboratory (MATLAB), Scientific Laboratory (Scilab), and LTspice (by Linear technology) software tools. Symbolic object function (syms) and ordinary differential equation (ODE) solvers are used to solve coupled ODEs in MATLAB. Detailed analyses of the frequency response for constant voltage (G_vd) and average current operations (G_id) are carried out. Although Scilab is open source software, it provides the same accuracy as that of a licensed tool, such as MATLAB. Furthermore, the LTspice software tool is observed to provide a quicker frequency response when compared to MATLAB. © 1988-2012 IEEE.

关键词： Frequency response

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Design and Development of a Digital Twin Platform for Scenario-Based Testing of Road Vehicles

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Procedia computer Science 2024年 241卷 220-227页

作者： Akramul Azim Ridwan Hossain Department of Electrical Computer and Software Engineering Ontario Tech University 2000 Simcoe Street North Oshawa L1G 0C5 Canada

There currently exists a need for a platform that provides users with the ability to perform extensive, repeatable and meaningful simulation and testing for the hardware and software which compose vehicle/autonomous vehicle systems whilst being broadly accessible, widely supported and provides robust features and development tools. The contemporary implementations of similar systems are either financially exorbitant or highly contained. The system reflected in this paper aims to fill a gap in the industry of vehicle/autonomous vehicle development by extending on currently existing open-source software to provide a highly streamlined platform to support the production of general road vehicle and autonomous vehicle driving systems. The software tools and hardware components chosen for the system will be discussed, followed by the features constructed throughout the development process. The end result of the system is a platform that allows for quick, repeatable, accurate, and nearly endless testing of a digital twin of real life vehicles. This system will allow users to gain valuable simulation and testing data of hardware and software components in a manner which is not always feasible using the traditional methods of autonomous vehicle testing.

关键词： Digital Twin Road Vehicles CARLA Open Source Testing

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Critical Role of Individual Cell Temperature Monitoring in Mitigating Thermal Runaway and Reducing Accelerated Degradation in Lithium-Ion Batteries 14

Critical Role of Individual Cell Temperature Monitoring in M...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Sharma, Mohit Samanta, Akash Locke, William Williamson, Sheldon Ontario Tech University Department of Electrical Computer and Software Engineering OshawaONL1G 0C5 Canada

ISBN: (纸本)9798331516116

Thermal runaway in lithium-ion batteries (LIBs) is a critical risk, potentially leading to fires and explosions. This phenomenon can be triggered by overcharging, short-circuiting, physical damage, manufacturing defects, and overheating. Effective mitigation of thermal runaway relies on precise and close monitoring of individual cells within the battery pack, a task often complicated by the complexity and cost of implementing temperature sensors on each cell in automotive applications. This study demonstrates the importance of individual cell temperature monitoring by intentionally including an unhealthy cell (C#12) in a 14-cell LIB 21700 module equipped with an automotive-grade battery management system (BMS) from NXP®. Experimental results reveal that despite efficient BMS balancing, the weak cell exhibited a significantly higher temperature rise, with a final temperature difference of 6°C and a voltage difference of over 200 mV compared to healthy cells. These findings underscore the potential for thermal failure and runaway if individual cell temperatures are not closely monitored. Additionally, reliance on voltage-based control alone can lead to suboptimal battery pack utilization, as evidenced by a 5% capacity loss due to the weak cell. This research highlights the necessity of monitoring the temperature of each cell to prevent thermal runaway and ensure efficient battery performance. © 2025 IEEE.

关键词： Lithium-ion batteries

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Review of on-board conductive charger topologies for electric transportation

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International Journal of Power Electronics 2023年第4期17卷 406-442页

作者： Vijaya Anand, N. Jaya Sai Praneeth, A.V. Yalla, Naveen Sood, Vijay K. Department of EEE P.V.P. Siddhartha Institute of Technology Kanuru Vijayawada520007 India Advance Engineering Group Borg Warner Technical Center Bascharage Luxembourg Varanasi221005 India Department of Electrical Computer and Software Engineering Faculty of Engineering and Applied Science Ontario Tech University 2000 Simcoe Street North OshawaONL1H 7K4 Canada

This paper presents an overview of on-board conductive charger topologies for electric vehicles (EVs). Battery packs in electric and plug-in hybrid electric vehicles (EVs/PHEVs) need frequent energy refills to fulfil their duty cycles and overcome the range anxiety of vehicle owners. Due to the limited availability of fast charging infrastructures, all automotive manufacturers prefer an on-board battery charger in their vehicles. However, there are power level limitations for these chargers because of the weight, space and cost constraints. On-board charging systems can be either conductive or inductive. This paper reviews the topologies that are involved in conductive charging only. Globally, all automotive companies provide levels 1 and 2 for residential charging of vehicles. Single- and two-stage power converter topologies are summarised with their limitations. Furthermore, the current trends in the DC-DC converters for the two-stage conversion battery charger topologies are also outlined. This paper provides an overview of various topologies and configurations involved in EV charging with their limitations. © 2023 Inderscience Enterprises Ltd.

关键词： Topology

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Temporal Sensitivity Analysis of Internal Temperature Informed Charging Algorithms and Rapid Thermal Management System for E-mobility

Temporal Sensitivity Analysis of Internal Temperature Inform...

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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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Cyberattack Classification in Smart Grid Distribution Substations using a Novel Ensemble Bagging Learning technique

Cyberattack Classification in Smart Grid Distribution Substa...

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Canadian Conference on Electrical and computer engineering (CCECE)

作者： Victor O. Ijeh Walid G. Morsi Computer and Software Engineering Dept. Smart Grid & Electric Vehicles Research Laboratory Electrical Ontario Tech University Oshawa Canada

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

Smart grid incorporates the communication networking that enables the exchange of information among the monitoring and controlling devices. Such incorporation of the communication networking into the electricity grid infrastructure poses the risk of cyberattacks that target the critical assets within such an infrastructure. Most of the existing research focuses on the detection of such cyberattacks but without identifying the type of the attacks. This can result in overlooked threats and misdirected the necessary countermeasures. Recognizing the attack’s type is essential for timely responses and strategic planning against future threats, thereby enhancing the resilience of the smart grid. In this paper, a Fine Tree Bagging-based Ensemble Learning (FTBE) technique is proposed to detect and classify the different types of cyberattacks and power quality disturbances. The salient features of the attacks’ types are highlighted, which helps in identifying the types of the attack following the detection process.

关键词： Training Accuracy Substation automation Uncertainty Scalability Smart grids Ensemble learning

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