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X-ORIGINAL-URL:https://ee.iisc.ac.in
X-WR-CALDESC:Events for EE
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TZID:Asia/Kolkata
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TZOFFSETFROM:+0530
TZOFFSETTO:+0530
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250102T100000
DTEND;TZID=Asia/Kolkata:20250102T110000
DTSTAMP:20260526T183450
CREATED:20241224T061206Z
LAST-MODIFIED:20250101T042719Z
UID:241864-1735812000-1735815600@ee.iisc.ac.in
SUMMARY:Talk : Renewable Energy Integration to Electric Grid: Modeling and Analysis
DESCRIPTION:Sukumar Kamalasadan\, Professor\, Department of Electrical and Computer Engineering\, The University of North Carolina at Charlotte\, Charlotte\, NC 28223\nThis lecture series mainly focuses on modeling Inverter Based Resources (IBRs) for small signal stability studies. Small signal modeling methods\, modeling of relevant control architectures\, and the overall system level security and stability analysis are discussed considering both transmission and distribution systems. The course sequence is divided into three parts: a) Part 1: small-signal modeling of inverters\, b) Part 2: modeling of control architectures\, and c) Part 3:  Modeling of advance control architectures and system-level considerations.
URL:https://ee.iisc.ac.in/event/talk-renewable-energy-integration-to-electric-grid-modeling-and-analysis/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250117T160000
DTEND;TZID=Asia/Kolkata:20250117T173000
DTSTAMP:20260526T183450
CREATED:20250113T105316Z
LAST-MODIFIED:20250113T105316Z
UID:241880-1737129600-1737135000@ee.iisc.ac.in
SUMMARY:Colloquium on Modelling\, Analysis and Control of Switched Reluctance Motors
DESCRIPTION:Speaker: THIRUMALASETTY MOULI . of Ph.D. (Engg) in Electrical Engineering under Electrical Engineering \nDate/Time: Jan 17 / 16:00:00 \nLocation: Multi Media Class Room (MMCR)\, EE Department \nResearch Supervisor: Narayanan G \nAbstract:\nSwitched reluctance machine (SRM) is known for many advantages such as permanent magnet-free operation\, robust structure\, low rotor inertia\, low manufacturing cost\, and excellent fault-tolerant capability. Hence\, SRM has been adopted in many applications such as\, electric vehicles\, aerospace\, and robotics. Nonlinear characteristics and pulsations in torque developed are well-known problems\, rendering modelling and control of the SRM challenging. This thesis focuses on the modelling\, characterization and control of switched reluctance machines. Current\, torque\, and speed control are all part of the scope of study. Conventionally rotors with laminations are used in SRM. In certain applications where the shaft temperature increases very significantly\, the thermal expansion of the different constituent materials in a typical laminated would be at different rates. This creates stress in the rotor assembly and could reduce the reliability of the machine. Hence\, in such applications\, rotors made from a single piece of magnetic material are potential candidates. Solid-rotor and recently proposed slitted-rotor SRMs are prospective candidates for high temperature applications. However\, research on solid- and slitted-rotor SRMs remains relatively limited. In this thesis\, solid and slitted rotor SRMs are systematically compared through comprehensive 3D transient finite element analysis (FEA) and experimental evaluations under both static and dynamic conditions. Blocked rotor experiments and 3D finite element analyses reported show that the slitted-rotor SRM has lower core loss and higher torque density than the solid-rotor SRM. High torque density is essential for applications such as electric vehicles and aerospace systems. This thesis compares several methods to enhance laminated-rotor SRMs torque density through FEA simulations. Various magnetic structure-based techniques\, including multi-toothed stators\, tapered poles\, non-uniform air gaps\, flux barriers\, and segmental rotors\, are analyzed. Additionally\, the performance of two winding configurations—double-layer conventional (DLC) and double-layer mutually coupled (DLMC)—is compared under unipolar and bipolar excitations\, respectively. The DLMC winding concept is applied to solid- and slitted-rotor SRMs to enhance torque output. These machines are reconfigured from conventional windings to a DLMC configuration. Due to the absence of existing literature on mutually coupled solid- and slitted-rotor SRMs\, FEA simulations and extensive blocked-rotor experiments are conducted to evaluate their performance under bipolar current excitation. Comparative analysis with conventionally wound counterparts reveals a significant enhancement in torque characteristics achieved through the DLMC winding connection. Two new current control schemes are proposed in this research work. In the first part\, an extended horizon model-based predictive current controller is proposed for SRM. An analytical equation is reported for real-time computation of the optimal duty ratio to minimize the RMS error between the future current references and predicted currents over a horizon. The proposed controller demonstrates lower RMS error in current tracking and robustness to parameter variations\, with experimental validation on a laboratory prototype drive\, over an existing dead-beat predictive controller. Further\, a fixed-frequency\, model-independent predictive current control for SRM is proposed. Unlike traditional approaches\, this method does not require any pre-measured characteristics of the SRM. Instead\, it only requires two constants: the optimal value of equivalent inductance and the moving average window period. Hence this method eliminates the need for time consuming characterization experiments\, multi-dimensional lookup tables\, and offline curve fitting to model the flux-linkage characteristics of the SRM for current control. A high-performance torque control scheme for SRMs is presented\, incorporating a PI controller\, feedforward compensation\, high-frequency compensation\, and optimized gating functions. This controller achieves significant reduction in pulsating torque and outperforms state-of-the-art techniques across various operating conditions. Further improvement in performance is achieved through a novel PWM-based optimal predictive direct torque control scheme. In this work\, a cost function\, encompassing the instantaneous torque error and the RMS values of phase currents is formulated to be minimized. An analytical expression for the optimal duty ratio towards this objective is derived resulting in improved computational efficiency. This controller delivers improved torque tracking\, higher torque per ampere\, and lower sound pressure levels compared to existing methods. A novel experimental method for determining the combined moment of inertia and frictional torque characteristics of an SRM coupled to a load\, utilizing a low torque ripple controller. The identified mechanical parameters are leveraged to develop a systematic design procedure for a PI-based speed controller\, achieving fast speed reference tracking and robust disturbance rejection. The controller’s effectiveness is validated through simulations and experiments\, demonstrating its effectiveness in improving SRM drive performance.
URL:https://ee.iisc.ac.in/event/colloquium-on-modelling-analysis-and-control-of-switched-reluctance-motors/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250121T110000
DTEND;TZID=Asia/Kolkata:20250121T130000
DTSTAMP:20260526T183450
CREATED:20250121T040923Z
LAST-MODIFIED:20250121T040923Z
UID:241882-1737457200-1737464400@ee.iisc.ac.in
SUMMARY:Talk on Voltage Monitoring and Control of Active Distribution Systems
DESCRIPTION:Speaker:\nProf Anamitra Pal\nSchool of Electrical\, Computer\, and Energy Engineering\nArizona State University (ASU)\, USA\n \nDate: 21st January 2025\, 11:30 AM\n \nVenue: C 241\, MMCR\, Electrical Engg Dept\, IISc\n \nAbstract: Residential solar photovoltaic (PV) systems are integral for achieving the carbon neutral goals for 2050. At the same time\, power utilities\, who are responsible for the reliability and stability of the electric distribution grid\, are often unaware of the extent of behind-the-meter solar PV penetration. In the absence of real-time visibility and adequate control\, the increasing proliferation of residential PV systems can play havoc with the distribution feeder voltage. Consequently\, there is a genuine need to closely monitor and control the voltage over the entire length of the feeder.\nThis talk will describe how system-wide information obtained from a select few real-time sensors using machine learning can be used to optimize reactive power regulation for achieving coordinated\, robust\, and fast voltage control of active distribution systems. To ensure trust in the machine learning-based approach\, formal guarantees of performance will also be established. The talk will conclude by demonstrating additional system-wide benefits that an integrated approach towards monitoring and control provides to power utilities responsible for operating large\, complex distribution grids.\n \n \nShort Biography: Anamitra Pal is an Associate Professor in the School of Electrical\, Computer\, and Energy Engineering at Arizona State University (ASU). His research interests include data analytics with a special emphasis on time-synchronized measurements\, artificial intelligence-applications in power systems\, renewable generation integration studies\, and critical infrastructure resilience. Dr. Pal has received numerous accolades including the 2018 Young CRITIS Award for his contributions to the field of critical infrastructure protection\, the 2019 Outstanding Young Professional Award from the IEEE Phoenix Section\, the National Science Foundation CAREER Award in 2022\, and the Centennial Professorship Award from ASU in 2023.
URL:https://ee.iisc.ac.in/event/talk-on-voltage-monitoring-and-control-of-active-distribution-systems/
LOCATION:Multi-Media Class Room (MMCR)\, EE Department (Hybrid mode)
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250124T120000
DTEND;TZID=Asia/Kolkata:20250124T130000
DTSTAMP:20260526T183450
CREATED:20250123T044700Z
LAST-MODIFIED:20250123T044700Z
UID:241888-1737720000-1737723600@ee.iisc.ac.in
SUMMARY:Talk on Wearable Sensor Signal Processing and Data Analytics for Health Applications
DESCRIPTION:Title: Wearable Sensor Signal Processing and Data Analytics for Health Applications\nby\nProfessor Gaurav Sharma\nDepartment of Electrical and Computer Engineering & Department of Computer Science\nUniversity of Rochester\nVenue: Multimedia Classroom\, EE\, IISc\nTime: 12 noon to 1 PM on (Friday) 24th January 2025. Coffee will be served at 11.45 AM.\nAbstract\nAdvances in nano-fabrication and MEMS devices have led to radical improvements in sensing technologies in recent years. These improvements are most visible to all of us in our SmartPhones that already feature a panoply of miniaturized sensors. Many of the same sensors are also positively impacting several other application domains. In this talk\, we highlight how smart light-weight body worn sensors are set to revolutionize healthcare and the practice of medicine by providing technologies for assessing biomarkers for physiological and physical attributes related to disease condition\, treatment effectiveness\, and longitudinal progression. In contrast with the subjective\, sporadic in-clinic assessments that are in common use today\, body-worn sensors can provide objective and repeatable measurements and based on extended periods of continuous monitoring. We present examples from our recent and ongoing research that features light-weight\, low-power sensors that can be affixed to the body like adhesive temporary tattoos\, in a diverse set of health monitoring applications including quantification of movement disorders for Parkinson’s and Huntington’s diseases\, stroke rehabilitation\, and cardiac monitoring. We present examples of signal processing and data analytics for these applications that effectively exploit the sensor measurements. Finally\, we highlight ongoing and emerging directions for research and development.\nSpeaker Biography\nGaurav Sharma is a professor in the Departments of Electrical and Computer Engineering\, Computer Science\, and Biostatistics and Computational Biology\, and a Distinguished Researcher in Center of Excellence in Data Science (CoE) at the Goergen Institute for Data Science at the University of Rochester. He received the PhD degree in Electrical and Computer engineering from North Carolina State University\, Raleigh in 1996. From 1993 through 2003\, he was with the Xerox Innovation group in Webster\, NY\, most recently in the position of Principal Scientist and Project Leader. His research interests include data analytics\, cyber physical systems\, signal and image processing\, computer vision\, and media security; areas in which he has 56 patents and has authored over 220 journal and conference publications. He served as the Editor-in-Chief for the IEEE Transactions on Image Processing from 2018 through 2020\, and for the Journal of Electronic Imaging from 2011 through 2015. He is a member of the IEEE Publications\, Products\, and Services Board (PSPB) and chaired the IEEE Conference Publications Committee in 2017-18. He is the editor of the Digital Color Imaging Handbook published by CRC press in 2003. Dr. Sharma is a fellow of the IEEE\, a fellow of SPIE\, a fellow of the Society for Imaging Science and Technology (IS&T) and has been elected to Sigma Xi\, Phi Kappa Phi\, and Pi Mu Epsilon. In recognition of his research contributions\, he received an IEEE Region I technical innovation award in 2008 and the IS&T Bowman award in 2021. Dr. Sharma served as a 2020-2021 Distinguished Lecturer for the IEEE Signal Processing Society.\n\nHost: Chandra Sekhar Seelamantula\, EE\, IISc.
URL:https://ee.iisc.ac.in/event/talk-on-wearable-sensor-signal-processing-and-data-analytics-for-health-applications/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250128T150000
DTEND;TZID=Asia/Kolkata:20250128T170000
DTSTAMP:20260526T183450
CREATED:20250128T043207Z
LAST-MODIFIED:20250128T043207Z
UID:241890-1738076400-1738083600@ee.iisc.ac.in
SUMMARY:Talk on High-frequency Integrated Magnetics for High-performance Computing.
DESCRIPTION:Title: \nHigh-frequency Integrated Magnetics for High-performance Computing. \n  \nSpeaker: Ranajit Sai\, Tyndall National Lab \n  \nDate and Time: 28th January 2025\, Tuesday 3 pm \n  \nVenue: MMCR EE \n  \nAbstract: \nPower management for high performance processors\, SoCs and AI engines is evolving from Point of Load (POL) on-board DC-DC converters to in-package granular power delivery network (PDN). Granular PDN with integrated magnetics enables independently regulated per-core power delivery to match its power utilization profile within each workload\, thus reducing power overhead significantly and as a result enhancing system-level efficiency significantly. While the main role of the integrated inductor devices in a integrated voltage regulator remain same – to have sufficient inductance to filter the fundamental switching signal and have sufficient bandwidth to filter out the unwanted switching harmonics up to a certain frequency\, the form-factor and placement of these devices may vary significantly across applications. In addition\, these inductors must not saturate at the converter’s peak current\, while having lowest possible power loss over the entire operating range of the converter. Finally\, the magnetic component is expected to take as little space as possible – especially in the light of 3D integration\, height of the device is equally important to the footprint. The key question here is how to evaluate and compare integrated and embedded inductor devices for a certain voltage converter application. It is a daunting task even when the effect of temperature and electromagnetic interference (EMI) are not considered. \n  \nThis presentation will capture various efforts made by researchers over the past decade and the key technological trend of integrating high-frequency magnetic devices in 3D IC package. Furthermore\, key research and development scope in integrated magnetics will be highlighted.  \n  \nSpeaker’s bio: \nRanajit Sai is a Senior Researcher and Technical Lead of the Integrated Magnetics Research Group in Tyndall National Institute\, Ireland. He is driving design and development of futuristic on-silicon integrated thin-film magnetics and in-package embeddable magnetics for powering datacenter processors and AI engines. He’s leading research projects funded by leading industries\, research consortiums\, and Govt. agencies. His research is driven by probing novel physical phenomena\, tailoring material properties\, and solving technological bottlenecks through innovation in material development\, device design and integration strategies. \n  \nPrior to joining Tyndall in 2022\, Ranajit spent four years in Japan as an Asst. Professor at Tohoku University in Sendai\, and subsequently another four years in India as a Visiting Professor at Indian Institute of Science (IISc) in Bengaluru. He received his PhD in 2014 from Indian Institute of Science (IISc)\, India. To date\, Ranajit has published his work in 40+ journal/conference papers\, filed 5 patents\, and presented in more than 45 international conferences that include the flagship conferences organized by IEEE Magnetics Society\, IEEE Power Electronics Society\, and American Institute of Physics.              
URL:https://ee.iisc.ac.in/event/talk-on-high-frequency-integrated-magnetics-for-high-performance-computing/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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