Channel Title: IEEE Industrial Electronics Society Channel Description: <video> Digital Twin Architecture & Implementation for DC Microgrids in Industrial Applications Description: Digital Twin Architecture & Implementation for DC Microgrids in Industrial Applications Speaker : Dr. Kristen Garcia Booth, Assistant Professor, University of South Carolina, USA </video> <video> Transforming Manufacturing with AI: From Data Analytics to the Smart Factory Description: Transforming Manufacturing with AI: From Data Analytics to the Smart Factory Speaker: Dr. Qing Tang, Data Scientist, Senior Researcher, INTERX, South Korea </video> <video> Temporal Sensitivity Analysis for Lithium-ion Batteries Description: Title: Temporal Sensitivity Analysis for Enhanced Dynamic Equivalent Circuit Modeling of Lithium-ion Batteries in On-board Battery Management Systems Alvin Huynh Department of Electrical, Computer and Software Engineering Ontario Tech University Oshawa, Canada alvin.huynh@ontariotechu.net Akash Samanta Department of Electrical, Computer and Software Engineering Ontario Tech University Oshawa, Canada akash.samanta@ontariotechu.net Sheldon Williamson Department of Electrical, Computer and Software Engineering Ontario Tech University Oshawa, Canada sheldon.williamson@ontariotechu.ca Abstract: State-of-the-art lithium-ion battery state estimation techniques, including state-of-charge, state-of-health, and remaining useful life in battery management systems (BMS), are extensively dependent on equivalent electric circuit model (ECM) parameters. ECM parameters are subject to change due to battery aging, changes in operating temperature, and other operating conditions. Therefore, updating the model parameters in real-time by on-board BMS is essential to maintain the accuracy of state estimation where ECM is used as the primary building block. ECM parameters obtained in laboratory conditions cannot guarantee accuracy in onboard BMS throughout the entire life cycle of an electric vehicle battery. Currently, onboard state estimation techniques use static ECM parameters due to complexity and computational time in parameterization and online computation, especially with higher-order ECMs. Therefore, this paper presents a comparative analysis of 2-RC, 3-RC, and 4-RC ECMs concerning parameterization time, computational cost, and accuracy, providing an understanding of the possible integration of dynamic ECM models through regular parameterization in onboard BMS. The sensitivity analysis depicts that the 3-RC model would be most appropriate for considerably high accuracy for a BMS with moderate computational power, ensuring safe and reliable state estimation throughout the lifetime of the battery. Moreover, with the changes in ambient conditions, as the sensitivity of R2 and C2 are much lower compared to other parameters,these do not need updating with the changes in operating temperature. </video> <video> Nocturne - A Real-Time Driving Assistant Description: Paper title : Nocturne - A Real-Time Driving Assistant at Night for Sri Lanka Authors names : Mohamed Safrullah Mohomed Mohammed Ashfaq Ashar Abdul Qadir Vilcassim Sukumar Kavishan Let us obey Your Mercy Manjusri Wikramasinghe Adrian David Cheok Affiliation : Mixed Reality Lab, University of Colombo School of Computing Paper abstract : Nighttime driving presents significant challenges, including detecting pedestrians, cyclists, and potholes in low- visibility conditions, leading to frequent road accidents. In Sri Lanka, there is a lack of automated systems capable of addressing these challenges. This research proposes a system leveraging AI and real-time video processing to enhance driver safety by im- proving pedestrian and cyclist visibility and developing a reliable pothole detection system for night time. These enhancements rely on extensive data collection and preprocessing for training specialized computer vision and machine learning models tailored for real-time, low-light scenarios. The application provides real- time alerts and visual cues to reduce nighttime driving accidents. Additionally, a software framework is proposed to offer real-time feedback for drivers leveraging available hardware capabilities, enhancing awareness of vulnerable road users. Through rigorous data collection, testing, and development, this approach signifi- cantly helps to enhance nighttime driving safety in Sri Lanka. </video> <video> Impact of Flux Barrier Shape on Reduced Rare-Earth ML-IPMSM Description: Paper title- "Impact of Flux Barriers Shape on the Performance of Reduced Rare-Earth Multilayer Interior Permanent Magnet Synchronous Motor" Author Names- Abhishek Shukla, Saptarshi Basak Affiliation- Centre for Automotive Research and Tribology, IIT Delhi India. Paper abstract- Multilayer interior permanent magnet synchronous motor has more flexibility when choosing different magnet materials for rotor structures. It also has high power density and high efficiency during high-speed operation. However, due to the limited availability of rare earth materials, high cost, and environmental issues, there is a need to replace with non-rare-earth or reduce rare earth magnet material in the interior permanent magnet synchronous motors. To improve motor performance, different shapes of flux barriers inserted in double U-shaped rotor topology still require detailed analysis, which is yet to be explored in the literature from a design perspective. So, this work proposes a reduced rare earth double-layer U-shaped rotor topology with a hybrid magnet structure to reduce rare earth magnets. The design process includes fractional slot windings, the impact of different flux barrier shapes in the rotor topology, and the manufacturing of the stampings. This study examines the reduction of cogging torque and core losses and improves the efficiency of low-voltage level, especially two-wheeler applications for high CPSR. Cost estimation, comparative analysis of proposed topology, and simulation results as obtained from the 2D FEM simulation software have been presented. </video> <video> Taichi Nakano - IECON2024 SYPA - 3M Video Description: Paper Title: Active Control of Pyrofuse in Circuit Breaker with State Estimation of Current-Limiting Fuse Authors: Taichi Nakano, Reon Sasaki, Wataru Ohnishi, Yasushi Yamano, Yuki Inada Affiliation: Taichi Nakano, Reon Sasaki, Wataru Ohnisho: The University of Tokyo, Yasushi Yamano, Yuki Inada: Saitama University Abstract: Compact and cost-effective DC circuit breakers are becoming increasingly crucial as the prevalence of household solar panels and electric vehicles for a sustainable society. For this demand, a current-limiting fuse, which can limit current flow, and a pyrofuse, which physically interrupts circuits by detonating gunpowder, have been focused on as practical and compact components. This paper presents an active control of a pyrofuse in a compact circuit breaker consisting of a current-limiting fuse and a pyrofuse in series connection. The system interrupts fault currents by first limiting the current through the current-limiting fuse and then activating the pyrofuse to interrupt the circuit. The pyrofuse is activated based on a real-time estimation of the current-limiting fuse, developed in our previous research, which detects the end of the current-limiting by utilizing a real-time current data. This system safely interrupts fault currents that each component alone is unable to handle. The effectiveness of this breaker has been validated through experiments, with the interruption of a fault current of 1.7 kV and 10 kA occurring within 8.3ms. Additional Information: Creator: Taichi Nakano (Koseki-Ohnishi Lab, Faculty of Engineering, The University of Tokyo). About Koseki-Ohnishi Lab: URL: https://ctl.t.u-tokyo.ac.jp/en/ Koseki-Ohnishi Laboratory mainly researches the application of control engineering theories to information, communication, and electrical engineering across diverse areas. Within these research topics, our group focuses on advancing Direct Current Circuit Breakers (DCCB) to achieve faster and safer interruption. </video> <video> Sequential model predictive controls for MLIs Description: Paper title: A Comprehensive Study of Sequential Model Predictive Control Methods for Multilevel Inverters. Authors: Hoang Le and Apparao Dekka. Affiliation: Department of Electrical and Computer Engineering, Lakehead University, Thunder Bay, Ontario, Canada. Paper abstract: Due to the low computational burden, sequential model predictive control (SMPC) methods have emerged as promising solutions for multilevel inverters (MLIs). Over the years, several SMPC approaches focusing on either load current or load voltage as the primary objective have been explored for MLIs. These methods have adopted philosophies such as cost function with weighting factors, offline switching vector selection or inherent strategies to minimize common-mode voltage (CMV). However, the literature lacks a comprehensive analysis of SMPC methods with CMV minimization and their pros and cons on system performance. To fill the research gap, this paper presents the philosophies behind various SMPC methods for four-level inverters (FLIs), along with the mathematical models utilized in SMPC implementation and case studies to highlight their performances. Finally, a comparative analysis of SMPC methods is provided, aiding researchers in selecting suitable methods for their applications. </video> <video> Optimized Sequence Control of a Fuse-Semiconductor Circuit Breaker Description: Paper Title: Optimized Sequence Control of a Fuse-Semiconductor Hybrid Circuit Breaker through Real-Time Fuse State Estimation Author Names / Affiliation: Songah Shin / Graduate School of Engineering, The University of Tokyo Reon Sasaki / Graduate School of Engineering, The University of Tokyo Yusuke Nakano / Institute of Science and Engineering, Kanazawa University Naoto Kodama / Graduate School of Engineering, Nagoya University Shungo Zen / College of Science and Engineering, Aoyama Gakuin University Yasushi Yamano / Graduate School of Science and Engineering, Saitama University Yuki Inada / Graduate School of Science and Engineering, Saitama University Wataru Ohnishi / Graduate School of Engineering, The University of Tokyo Abstract: Hybrid DC circuit breakers have become a critical choice for ensuring safety in modern DC transmission and distribution systems. In this paper, we validate a current path control strategy in the fuse-semiconductor hybrid circuit breaker. This strategy utilizes an RC circuit model to describe the arcing current of the fuse and applies the Recursive Least Squares (RLS) algorithm to minimize the difference between the modeled current and the observed current data in real-time. By presenting the fuse’s current-limiting state in real-time, this method effectively prevents re-arcing and potential fuse explosions. Our approach addresses the limitations of the predetermined current threshold method, enabling a more accurate current model in complex situations. The proposed strategy was experimentally validated under extreme conditions of 1.7 kV and 10 kA fault currents, demonstrating its robustness and reliability. Creator: Songah Shin (Koseki-Ohnishi Lab, Graduate School of Engineering, The University of Tokyo) Koseki-Ohnishi Laboratory mainly researches the application of control engineering theories to information, communication, and electrical engineering across diverse areas. Within these research topics, our group focuses on advancing Direct Current Circuit Breakers (DCCB) to achieve faster and safer interruption. </video> <video> Distributed Resilient Control of DC Microgrids Under FDI Attacks Description: Paper Title: Distributed Resilient Control of DC Microgrids Under Unbounded FDI Attacks and Communication Link Faults Considering Balance of Charge State Authors: Mohamadamin Rajabinezhad, Yi Zhang, Shan Zuo Affiliation: The Department of Electrical and Computer Engineering University of Connecticut Storrs Mansfield, USA Abstract: This paper presents a fully distributed resilient secondary control approach for DC microgrids, designed to enhance resilience against unbounded false data injection (FDI) attacks on control inputs and communication link faults. The approach links the injected power with the current state of charge (SoC) and the observed average SoC value, adjusting the droop coefficient in the secondary control level for energy storage systems (ESSs) accordingly to prevent overuse of any single ESS. Each converter employs a resilient consensus-based secondary control strategy, effectively mitigating these sophisticated threats. A rigorous Lyapunov stability analysis verifies that the framework can maintain essential DC microgrid distributed control objectives, such as voltage regulation, proportional load sharing, and SoC balancing, even under unbounded FDI attacks and communication link faults. The practical effectiveness of the framework is demonstrated through hardware-in-the-loop experiments using Typhoon HIL 604, showcasing its improved resilience against the complex challenges posed by such FDI attacks. </video> <video> IES Townhall Sep 2024 - IEEE Fellow Applications by Dr Don Tan Description: Are you qualified and ready for IEEE fellowship, particularly, as a member from industry? What is the best way to prepare a nomination package? And how is your nomination going to be evaluated? Hosted by IES President Milos Manic, our recent IES Town Hall Meeting, Dr. Tan provides a unique perspective from an IEEE Fellow Committee Immediate Past Chair's viewpoint. It aims to demystify the fellow nomination and evaluation process. Dr Tan discusses, with industry member focus, on recent fellow statistics, nomination package preparation, contribution category selection, and qualification characteristics matrix (e.g., selection criteria) details. A few samples from past successful nominations are presented and discussed as well. </video> <video> Reinforcement Learning Controller for PUC5 Grid-Tied Inverter Description: Paper title: Reinforcement Learning Based Control of Grid-Connected PUC5 Inverter Authors: Azadeh Kermansaravi, Alamera Nouran Alquennah, Aleksandra Lekic, Mohamed Trabelsi, Hani Vahedi, Ali Ghrayeb, Haitham Abu-rub Affiliation: Delft University of Technology Paper abstract: In this paper, a Reinforcement Learning controller (RLC) is designed and implemented on a 5-level Packed U-Cell (PUC5) grid-connected inverter to control the injected current flowing into the electric network. The RL agent is trained using a Proportional-Integral (PI) reward function to optimize its control strategy. Moreover, the voltage balancing of the auxiliary capacitor in PUC5 is separated from the RL controller and integrated into the switching algorithm to reduce the training burden. This modification reduces the observation inputs re[1]quired for RL training, significantly shorten the training time. Simulation studies conducted in Matlab/Simulink evaluate the performance of the proposed RL controller, demonstrating robust dynamic response and accurate tracking of reference signals across different operational conditions. </video> <video> Rotor Fault Diagnosis of Large Hydrogenerators Description: Runing title: Rotor Fault Diagnosis of Large Hydrogenerators Paper title: Rotor Fault Diagnosis of Large Hydrogenerators Using Vibration Data and VAE-Desirability Function Authors and Affiliation: Author Affiliation Rony Ibrahim Higher School of Technology Zemouri Row Hydro-Quebec Research Center Antoine Tahan Higher School of Technology Bachir Kedjar Higher School of Technology Kamal Al-Haddad Higher School of Technology Arezki Merkhouf Hydro-Quebec Research Center Abstract: In electrical equipment maintenance, precise diagnosis is critical for dependability and efficiency. Variational Autoencoder (VAE) approaches show promise for fault classification but encounter hurdles due to their non-deterministic nature, which results in inconsistent fault grouping across machines. To address this, a novel method incorporates a desirability function into the VAE's cost function, resulting in standardized fault classification. This approach, evaluated with vibration data from large hydrogenerators, demonstrates that the enhanced model can cluster 86% of comparable faults into predefined zones, compared to 27% without including this term, while accounting for two severity levels of three rotor faults. </video> <video> Inductive Loop Detector for Personal Transporters Description: Paper title, authors names, affiliation - Paper Title - An Inductive Loop Detector for Personal Transporters in Urban Cycle Lanes Author Names - Thomas P. Rajan and Boby George Affiliation - Department of Electrical Engineering, Indian Institute of Technology - IIT Madras, Chennai, India Paper abstract - A sensor coil is developed for detecting personal transporters based on unique vehicle signatures. Mixed use of a wide range of personal transportation vehicles like kick scooters, skateboards and hoverboards on the urban cycle lanes have led to an increased traffic on these lanes. For the planning and optimal use of such lanes, accurate information regarding the traffic on such lanes, i.e. the number and types of vehicles are needed. Most of the conventional vehicle detection schemes fail to sense these vehicles accurately due to their small size. As the vehicle size is less compared to the rider, even the computer vision based techniques confuse them as pedestrians. Inductive loop sensors have several advantages and are widely used for traffic detection of large vehicles. They provide a signature for each type of vehicle, due to the change in inductance of the sensor coil owing to the metallic bottom structure of the vehicle. The present work proposes four sensor coil designs for cycle lanes, and evaluates their performance in sensing and classifying the personal transporters. A simple coupled resonating circuit that gives high sensitivity and noise rejection capability is used to measure from the sensor coil. The sensor designs are tested with three types of vehicles, typically found on cycle lanes - electric kick scooter, bicycle and a skateboard. The vehicles are driven through various possible paths along the sensor coil and the corresponding signatures are recorded. From the observed signatures for each vehicle type, a set of attributes are identified, which could be used as inputs for any classification algorithm. The proposed designs are also evaluated based on a set of criteria, from which, one of the designs is selected as the best. This study shows that, if suitably designed, inductive loop sensors can give unique signatures for personal transportation vehicles, enabling reliable detection and classification. </video> <video> Real-time CAN Data Acquisition & Visualization for BMS Description: Paper Title, Authors, Affiliation: Paper Title: Real-time CAN Data Acquisition and Visualization: Synerging Physical-to-Virtual (P2V) Twinning of Automotive Battery Management Systems Authors: Mohit Sharma (Student Member, IEEE), Department of Electrical, Computer and Software Engineering, Ontario Tech University, Oshawa, Canada Akash Samanta (Student Member, IEEE), Department of Electrical, Computer and Software Engineering, Ontario Tech University, Oshawa, Canada Chandan Chetri (Student Member, IEEE), Department of Electrical, Computer and Software Engineering, Ontario Tech University, Oshawa, Canada Sheldon Williamson (Fellow, IEEE), Department of Electrical, Computer and Software Engineering, Ontario Tech University, Oshawa, Canada Paper Abstract: Controller area network (CAN) is widely used in automotive applications and has become the standard communication protocol to enable efficient communication primarily between electronic control units (ECUs) to reduce the complexity and cost of electrical wiring in automobiles through multiplexing. Towards developing the cloud-based electric vehicle battery data monitoring and digital-twinning of a battery management system (BMS), this paper introduced an online CAN data acquisition and visualization technique from an automotive grade BMS of NXP®®. Python-based CAN data processing tool is developed to process the raw data from the NXP® BMS and an open-source platform Grafana® is utilized together with the InfluxDB for visualization of the time-series data in real-time from a battery module containing 14 SAMSUNG 21700 lithium-ion battery cells. Each of those elements is implemented through the Docker container platform to become a standardized unit called a container. Besides presenting the detailed architecture of the data acquisition and visualization platform and the python-based data processing tool, this paper demonstrated the capability of the proposed architecture through examples of visualizing individual cell voltage, current, and temperature in real-time and their applications and utility in implementing cloud-based BMS. Additional Information for YouTube Page: This video will explore the practical application of real-time CAN data acquisition from automotive-grade BMS and the utility of cloud-based data visualization for electric vehicles. It demonstrates a novel Python-based tool for processing raw CAN data and the use of Grafana for real-time data analysis, contributing to advancements in the development of digital twin-based battery management systems. </video> <video> Adaptive Pulsewidth using Magamp for Bio-Medical Applications Description: Paper title: Adaptive Pulse Power Converter using Magamp for Bio-Medical Applications Authors names: Sai Sushma Pasupuleti, Harish Sarma Krishnamoorthy Affiliation: University of Houston Paper abstract: Isolated power converters capable of delivering high-voltage and high-frequency pulses are critical for a range of applications spanning industrial, biomedical, and environmental fields. These applications include but are not limited to electroporation, ozone generation, food sterilization, water treatment, and semiconductor manufacturing. There is an increasing emphasis on enhancing the efficiency and flexibility of pulse power converters, particularly for biomedical uses. This paper introduces a novel approach employing a forward converter topology with a magnetic amplifier on the secondary side. The integration of a magnetic amplifier on the secondary side of a forward converter for pulse generation significantly improves the control over the pulse characteristics, including the peak magnitude, width, and frequency, thereby enhancing overall performance. Comprehensive simulations have been conducted using the LTSpice software to demonstrate the control of output pulses on the secondary side. </video>

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