EE

EE Talk 'Generic Modelling of Inverter Based Resources (IBRs) for Power System Planning Studies'
2024-08-23 16:00 - 17:00 (Asia/Kolkata) | B-303,EE
IEEE PES Student Branch Chapter, IISc, is organizing a series of technical talks on ‘Generic Modelling of Inverter Based Resources (IBRs) for Power System Planning Studies’ by Prof. Vijay Vittal, Arizona State University, USA.
The details of the Third technical talk are as follows.
Venue: Conference Room B-303,EE 2nd Floor, Electrical Engineering Department
Date and Time: Friday, 23rd August 4 PM – 5 PM IST.
Mode: In-person
Speaker Biography:

Regents Professor Vijay Vittal is the Ira A. Fulton Chair Professor (2005) and ASU Foundation Professor in Electric Power Systems at Arizona State University. Prior to ASU, Vittal was an Anson Marston Distinguished Professor at the Iowa State University, Electrical and Computer Engineering Department. In addition, Vittal was a Murray and Ruth Harpole Professor and director of the university’s Electric Power Research Center and site director of the National Science Foundation IUCRC Power System Engineering Research Center. He also served as the program director for power systems for the National Science Foundation Division of Electrical and Communication Systems in Washington, D.C., from 1993 to 1994. He was the editor-in-chief of the IEEE Transactions on Power Systems from 2005 to 2011. Professor Vittal was elected to the U.S. National Academy of Engineering in 2004. In 2018, he received the IEEE Power and Energy Society Prabha. S. Kundur Power System Dynamics and Control Award and the Utility Variable-Generation Integration Group Achievement Award. In 2013, he was awarded the IEEE Herman Halperin Transmission and Distribution Technical Field Award. He also received the IEEE Power and Energy Society (PES) Outstanding Power Engineering Educator Award in 2000. He was elected an IEEE Fellow in 1997 and awarded the U.S. National Science Foundation Presidential Young Investigator Award in 1985.

PhD Colloquium on Image Reconstruction
2024-08-14 10:00 - 13:00
PhD Thesis Colloquium
Student : Deepak G Skariah
Advisor : Prof. Muthuvel Arigovindan
Title : Infimal Convolution Based Regularization for Image recovery
Date and Time: 14.08.2024 (Wednesday), 11 am.
Venue : MMCR, Department of Electrical Engineering

Abstract
The quality of image captured by acquisition devices has increased drastically over the years largely due to a revolution in imaging sensor capability. But, image acquisition under low illumination continues to be a bottleneck for imaging devices such as optical microscopes leading to blurred and noisy images. A potential solution to this limitation is a computational approach known as image restoration. An image restoration algorithm recovers an estimate of the original image from a noisy blurred observation while assuming a knowledge of the image degradation model. The restoration problem is even more challenging when it comes to a spatio-temporal signal as a good restoration scheme needs to be mindful of presence of motion in the measured signal. This means that in spatio-temporal signal restoration problem, the algorithm should ensure temporal regularity of restored signal in addition to spatial regularity. Regularization based image restoration attempts to pose image restoration problem as a regularized optimization problem from the measured signal. We propose to exploit the concept of infimal convolution from convex analysis to design effective and efficient restoration schemes for images and spatio-temporal images.
In our first work, we address the problem of regularization design. We propose a family of derivative based regularization which we call generalized unitary invariant regularization and it belongs to class of infimal convolution based functionals. We also design an algorithmic scheme to optimize the resultant optimization problem. We demonstrate the quality of proposed algorithm and restoration scheme through multiple experiments on simulated data.
In our second work, we address the restoration of spatio-temporal images measured from TIRF microscopes where a sequence of noisy blurred images are observed over time. We once again exploit the infimal convolution based approach to design a novel spatio-temporal regularizer that is tailor made for above class of signals. The proposed regularization was designed to ensure both spatial and temporal regularity of restored signal. The resultant regularization functional is defined as an optimization problem where the cost is a weighted sum of two constituent functions where the two functions play the role of promoting spatial and temporal regularity respectively. We also design an algorithm to optimize the resultant restoration problem using this regularization. We demonstrate the quality of the proposed algorithm by testing the restoration quality against spatio-temporal measurements collected from TIRF microscopes.
In the third and final work we address the problem of estimating the relative weights in spatio-temporal regularization functional designed based on infimal convolution formulation. We propose a renewed optimization model where the spatio-temporal signal is estimated together with the better quality image estimate by incorporating the weights as part of the optimization problem. We also design an iterative scheme to optimize the resultant joint optimization model. We demonstrate the effectiveness of this scheme against other joint optimization schemes for spatio-temporal signal estimation.
ALL ARE WELCOME

Talk by SMA Solar India Pvt. Ltd
2024-08-09 15:30 - 17:00 | B-303,EE
Representative from SMA Solar India Pvt Ltd will be giving a talk today at 3:30 pm in the room B303. SMA is a leading global specialist in photovoltaic system technology headquartered in Niestetal. They are looking for interactions with faculties and students. In their talk, they will mostly explain the activities of their company.

EE Talk 'Generic Modelling of Inverter Based Resources (IBRs) for Power System Planning Studies'
2024-08-08 16:00 - 17:00 | B308,2nd floor, EE Dept.
IEEE PES Student Branch Chapter, IISc, is organizing a series of technical talks on ‘Generic Modelling of Inverter Based Resources (IBRs) for Power System Planning Studies’ by Prof. Vijay Vittal, Arizona State University, USA.
The details of the first technical talk are as follows.
Venue: Conference Room B-303,EE 2nd Floor, Electrical Engineering Department
Date and Time: Thursday, 8th August 2024, 4 PM – 5 PM IST.
Mode: In-person
Speaker Biography:

Regents Professor Vijay Vittal is the Ira A. Fulton Chair Professor (2005) and ASU Foundation Professor in Electric Power Systems at Arizona State University. Prior to ASU, Vittal was an Anson Marston Distinguished Professor at the Iowa State University, Electrical and Computer Engineering Department. In addition, Vittal was a Murray and Ruth Harpole Professor and director of the university’s Electric Power Research Center and site director of the National Science Foundation IUCRC Power System Engineering Research Center. He also served as the program director for power systems for the National Science Foundation Division of Electrical and Communication Systems in Washington, D.C., from 1993 to 1994. He was the editor-in-chief of the IEEE Transactions on Power Systems from 2005 to 2011. Professor Vittal was elected to the U.S. National Academy of Engineering in 2004. In 2018, he received the IEEE Power and Energy Society Prabha. S. Kundur Power System Dynamics and Control Award and the Utility Variable-Generation Integration Group Achievement Award. In 2013, he was awarded the IEEE Herman Halperin Transmission and Distribution Technical Field Award. He also received the IEEE Power and Energy Society (PES) Outstanding Power Engineering Educator Award in 2000. He was elected an IEEE Fellow in 1997 and awarded the U.S. National Science Foundation Presidential Young Investigator Award in 1985.

PhD Thesis Defense by Apoorva Sahu
2024-08-06 10:30 - 13:00 | High Voltage Lab Seminar Hall (Hybrid mode)
Synopsis
Join conversation (microsoft.com)
The consumption of crude oil is increasing every day particularly in developing countries like India which is the third largest consumer of crude oil in the world, utilizing on an average around 160 million liters per annum of which 30% constitutes diesel fuel. More than 50% of the NOx and hydrocarbons in air come from the diesel exhaust affecting the health of human beings, vegetation, and environment. While the solid particulate in the exhaust is taken care to a greater extent by the mechanical filters it is the gaseous pollutants such as oxides of nitrogen (NOx), oxides of carbon, hydrocarbons (HC) etc., that need to be addressed as they cause several health-related ailments in addition to acid rain, global warming, smog etc. It is timely to work on the development of economical and efficient pollution control strategies. On the other hand, issues that is affecting our country India currently are accumulation of wastes from utility industry, mariculture industry and agriculture industry. The prominent amongst them are fly ash, red mud, foundry sand, iron ore tailings, lignite ash, rice husk, wheat straw and sugarcane bagasse etc. Accumulation of these wastes are in several million tons per annum in India. Any proposition in recycling waste is a welcoming step.

Efforts are continuously being made for the past three decades to mitigate these gaseous pollutants, particularly NOx, at various levels by changing the fuel composition, engine modifications, pre-combustion techniques and post-combustion (aftertreatment) techniques. The existing post-combustion mode technique “catalyst-based converters and adsorbent based techniques” are becoming expensive owing to the short life, dependency on noble metals, more vulnerability to acidic coating, bulk usage of adsorbents etc. In this regard the application of non-thermal plasma or electric discharge plasma for pollution control aided by additional techniques is slowly gaining popularity in the past few years. Discharge plasma ionizes the atoms at normal temperature and atmospheric pressure (NTP) thus creating an oxidative environment resulting in chemical reactions such as reduction, oxidation, decomposition etc. However, among these reactions it was observed that oxidation was dominating, to a certain extent the oxidised by-products in the plasma appeared to be less hazardous to humans than to nature. This led to the redesigning of plasma reactors with the intention of enhancing the energy in the charged species favoring reduction reactions instead of oxidation ones but not without serious limitations with respect to the gas flow.

Application of electrical discharges for environmental purposes lies in the basic concept of treating the pollutants, particularly the gaseous ones, with plasma excited species. It is observed that plasma alone is insufficient for the successful treatment of any of the gaseous pollutants due to the oxidative environment prevailing in the discharge plasma at atmospheric conditions. This necessitated inclusion of additional treatment technique along with plasma leading to the origin of plasma catalysis/plasma adsorption methods where in the catalytic materials were kept inside the plasma environment (plasma catalysis) or the adsorbent materials are cascaded with plasma (plasma adsorption). It should be noted here that the total cost involved in the proposed technique, should be lower than that associated with conventional catalyst-alone or adsorbent-alone techniques so that the proposed ones can be a promising economic alternative to the conventional ones. That said, cascading commercially available catalysts/adsorbent with plasma can never be a cheaper alternative. Several research works, therefore, started by blending plasma with other lab made catalysts/adsorbents but the DeNOx efficiency was not significant.

Present work aimed at studying the NOx abatement in diesel engine exhaust at controlled laboratory condition using electrical discharges. The intention of the study is to provide not only an efficient but also an economical solution for reduction of the NOx pollutants. Keeping this in mind, it was decided to utilize electrical discharge technique in association with abundantly available solid wastes in India be it from industrial, mariculture or agriculture domains. Given the whole spectrum of parametric variations the thesis plan was carefully drawn to touch upon the following variations: type of corona electrodes, type of applied high voltage, type of solid wastes, type of gas treatment. Four types of electrodes were studied that include needle plate, metal film, helical wire and pipe type. Type of voltage involves fast rising repetitive pulses at 80 Hz, power frequency and high frequency AC. The solid wastes comprise of three categories namely (a) industrial/mariculture wastes that include namely iron tailings, lignite ash, red mud, foundry sand, waste tiles and copper slag, oyster shell (b) agricultural wastes including coffee husk, sugarcane waste, mulberry husk, rice husk, ragi husk, corn husk, wheat husk, pine, ground nut and areca nut husk and (c) composite wastes which include a blend of waste tiles + foundry sand, copper slag + red mud, iron tailings + waste tiles, red mud + waste tiles, foundry sand + red mud and foundry sand + iron tailings. The type of gas treatment involves treating the exhaust with only plasma/plasma catalysis/plasma adsorption/thermal catalysis utilizing catalytic properties of metal oxides present in the industry wastes or porous nature of the industry wastes. A comparison was also made by replacing the industrial wastes with commercial NOx catalysts. Important contribution of this research work can be summarized as: (a) with plasma catalysis approach the NOx removal efficiency gets enhanced by a factor of 5.3-6.7 compared to only plasma. (b) with plasma adsorption approach the NOx removal efficiency gets enhanced by a factor of 4-6 compared to only plasma. (c) Fe2O3/TiO2 present in red mud can act as photo catalysts in oxidizing NO through plasma generated ethyl nitrate in the plasma cascaded red mud adsorption process (d) Amongst the agricultural wastes, ground nut husk-based pellets exhibited 83% NOx removal efficiency (e) The newly developed metal film based DBD reactor enhances surfaces discharges far better than the helical wire reactor (f) commercial catalysts performed much better in NOx removal under plasma catalysis mode when compared to thermal catalysis mode. Further, plasma catalysis with industrial wastes such as iron tailings and oyster shell yielded better/similar DeNOx efficiency when compared to that with commercial NOx catalysts thus, justifying the usage of cheaper industrial wastes instead of expensive commercial ones.

CBR/EE: Talk by Prof. Mathews Jacob
2024-07-30 11:30 - 12:30 | CBR Auditorium, CBR, IISc.
Talk on Model based deep Learning for inverse problems in MRI: Beyond Algorithm Unrolling

by Prof. Mathews Jacob, University of Iowa, USA.

on July 30th, from 11.30 AM to 12.30 PM.

Venue: CBR Auditorium, CBR, IISc.

Host: Prof. Chandra Sekhar Seelamantula, IISc

Abstract: The reconstruction of MR images from highly undersampled Fourier measurements is a problem that has received a lot of attention in the past decade. Compressed sensing algorithms have been extensively employed in MRI to overcome the challenges associated with the slow nature of MRI acquisition. These methods offer guaranteed uniqueness, fast convergence, and stability properties. Model-based deep learning methods that combine imaging physics with learned regularization priors have emerged as more powerful alternatives for MR image recovery in recent years. The talk will introduce different flavors of physics-based deep learning methods and discuss the unique challenges associated with these schemes in high-dimensional settings. Novel memory efficient iterative algorithms that possess guarantees similar to compressive sensing, while offering improved performance will be introduced. Energy models that allow sampling from the posterior distribution will also be discussed. The talk will draw upon our recent work, available at https://cbig.iibi.uiowa.edu/publications

Biography of the speaker: Mathews Jacob will be starting as a Professor in the Department of Electrical and Computer Engineering at the University of Virginia, starting August 2024. He is currently a professor in the Department of Electrical and Computer Engineering and is heading the Computational Biomedical Imaging Group (CBIG) at the University of Iowa. He obtained his B.Tech in Electronics and Communication Engineering from National Institute of Technology, Calicut, Kerala, and his M.E in signal processing from the Indian Institute of Science, Bangalore. He received his Ph.D. degree from the Biomedical Imaging Group at the Swiss Federal Institute of Technology. He was a Beckman postdoctoral fellow at the University of Illinois at Urbana Champaign.
Dr. Jacob is the recipient of the CAREER award from the National Science Foundation in 2009, the Research Scholar Award from American Cancer Society in 2011, and the Faculty Excellence Award for Research from University of Iowa in 2021. He is currently the associate editor of the IEEE Transactions on Medical Imaging and has served as the associate editor of IEEE Transactions on Computational Imaging from 2016-20. He was the senior author on two best paper awards (2015 & 2021) and one best machine learning paper award (2019) from IEEE ISBI. He was the general chair of IEEE International Symposium on Biomedical Imaging, 2020. He was elected as a Fellow of the IEEE (2022) for contributions to computational biomedical imaging.

PhD Oral Examination of Subhas Chandra Das (ERP)
2024-07-29 16:00 - 17:00
Name of the Student

SUBHAS CHANDRA DAS

Programme / Degree

Ph.D. (Engg) in Electrical Engg

Name of the Department of IISc

Electrical Engineering

Name of the Research Supervisor

Narayanan G

Date & Time of the Oral Examination /Thesis Defense

29.07.2024 /16:00:00 /Scheduled

Venue / Mode

Multi Media Class Room (MMCR), EE Department (Hybrid mode)

Team Link
Abstract
Insulated gate bipolar transistors (IGBTs) are the dominant power semiconductor devices in high power applications, such as, locomotive traction and megawatt-level renewable energy systems. Power electronic converters in such applications are expected to have a long-life span of about 20-30 years. Hence, efficiency and reliability of these converters are very important. IGBT switching behavior has a direct influence on both power conversion efficiency and system reliability.
The various switching characteristics parameters of IGBTs, which are available in the respective device datasheets, are limited to certain operating conditions. For an example, the switching characteristic parameters are available for only one or two DC link voltages; however, in applications such as diesel-electric locomotives, IGBTs have to operate over a wide range of the DC link voltages. Similarly, the characteristic parameters are available at only one or two junction temperatures (e.g. 25 oC and 125 oC); but, the IGBTs in traction and wind energy systems have to operate over wide range of temperatures including sub-zero ambient temperatures.
In this work, switching behavior of IGBTs of four different makes are studied experimentally over a wide range of operating conditions. The load current is considered upto 1.667p.u., where 1 p.u corresponds to the rated current of the IGBTs. The range of DC link voltage considered is from 0.571 p.u. to 1.321p.u., where 1.0 p.u. is the nominal voltage of the application. The junction temperature range is considered from -35 oC to +125 oC. The following are the major highlights of the research work:
1. Generation of experimental data on switching behavior of IGBTs over wide range of operating conditions as mentioned above.
2. The experimental data, which are generated, complement the technical information available in device datasheets.
3. The experimental investigation are carried out on four traction-grade IGBTs of different makes and of comparable ratings to ensure that the findings of the study are applicable to reasonable cross-section of the available commercial devices.
4. Experimental study on the switching behavior of an IGBT converter leg, having top and bottom devices of two different makes, and its comparison with the switching behavior of a converter leg, having complementary devices of the same make.
5. Experimental study of the rise and fall times of the device switching voltages and currents, both during turn-on and turn-off, over the complete range of operating conditions.
6. Evaluation of turn-on and turn-off switching energy losses as functions of load current, DC link voltages and junction temperatures, which are valid over the complete operating range.
7. Experimental study of reverse recovery characteristics of anti-parallel diode of IGBTs with varying DC link voltage, load current and junction temperatures.
8. Experimental investigation on the effect of variations in DC link voltage, load current and junction temperatures on device peak stress parameters, namely, peak device voltage, peak device current, peak rate of change of device voltage, and peak rate of change of device current.
9. Experimental study of sub-intervals of the turn-on switching delay, turn-off switching delays and parameters related to the switching delay intervals over the complete operating range.
10. Correlation of the various turn-on and turn-off switching parameters with junction temperatures based on the experimental data generated.
11. Study of the consistency of the above correlations across different traction-grade devices of comparable ratings and different makes.
12. Critical review of various thermo-sensitive electrical parameters (TSEPs) already reported in literature.
13. Identification of new TSEPs that can be obtained from the measured gate-emitter voltage during switching delay times.
ALL ARE WELCOME

Colloquium
2024-07-26 14:30 - 17:00
Investigations on Pulse Width Modulation Techniques for Split-Phase Induction Motor Drives
Speaker: LALGY GOPI . of Ph.D. (Engg) in Electrical Engineering under Electrical Engineering
Date/Time: Jul 26 / 14:30:00
Location: Multi Media Class Room (MMCR), EE Department Team Link
Research Supervisor: Narayanan G
Abstract:
A split-phase induction motor (SPIM) has two sets of identical three-phase windings separated by 30° in space, typically fed by two- level voltage-source inverters. This configuration reduces the voltage rating of the windings and the DC-link voltage of the inverters. SPIMs are advantageous for high-power variable-speed applications due to reduced torque pulsations, lower voltage-rated power converters, higher torque per ampere, and increased reliability. However, they may require more semiconductor switches and circuitry. Although the winding structure avoids harmonic torques of the order 6k (k=1, 3, 5…), small voltages of harmonic order 6h±1 (h=1,3,5…) can cause large currents and increase copper loss. Properly designed pulse width modulation (PWM) techniques can improve SPIM drive performance by reducing stator copper loss and pulsating torque. In triangle comparison (TC) based PWM techniques for SPIM drives, two sets of modulating signals, which are phase-shifted by 30° from each other, are compared against a common carrier wave. In contrast, space vector (SV) based PWM techniques use the reference voltage vector to calculate the dwell times of each voltage vector, which are then applied in a specific sequence. TC-based PWM techniques are renowned for their simplicity in implementation, whereas SV-based techniques offer improved performance but come with increased computational complexity. While the unified understanding of these two types of PWM techniques is well established for three-phase induction motors, this thesis aims to enhance the unified understanding between TC-based and SV-based PWM techniques for SPIM drives. Several SV-based PWM techniques have been introduced for SPIM drives to enhance harmonic performance. Four-dimensional 24-sector SVPWM techniques outperform 12-sector methods but are more complex to implement. This thesis performs a per-phase analysis of these techniques to develop an efficient implementation scheme. It evaluates and analyses the switching cycle averaged pole voltages to determine the common mode voltage (CMV) for each inverter, showing that CMV relates to the fundamental voltage of different phases in different sectors. This leads to understanding the offset voltages needed for the two sets of three-phase sinusoidal modulating signals to generate equivalent signals for the two inverters driving the SPIM. Adding the derived zero-sequence signal to the sinusoidal modulating signals results in a computationally efficient implementation method. Equivalent carrier waves are derived based on the switching sequences, requiring discontinuous carrier waves for improved harmonic performance. This carrier-based implementation significantly reduces computation time on a TMS320F28377S DSP platform. Experimental results of stator current waveforms under steady-state and various dynamic conditions from a 6kW, 200V, 50Hz SPIM drive are presented. A comparative study based on the stator flux ripple analysis is carried out to evaluate the stator current harmonic distortion and rms torque ripple. The comparison of analytically evaluated torque ripple factor, simulated instantaneous torque ripple and harmonic spectra of torque are presented to validate the performance of different PWM techniques. The proposed discontinuous PWM method offers lower total harmonic distortion (THD) of stator current at high speeds. The equivalent modulating signals of the discontinuous PWM technique helped to evaluate the switching loss of semiconductor devices used. A comparison based on switching loss factor is carried to demonstrate the reduced switching loss due to this PWM technique. The discontinuous PWM technique is shown to have reduced switching losses at high power factors than the continuous PWM techniques with significantly low computational effort. An indirect field-oriented control scheme has also been presented to demonstrate the dynamic performance of the proposed implementation scheme. Two advanced bus-clamping pulse width modulation (ABCPWM) techniques are proposed in this thesis for SPIM drives to enhance their performance further. These techniques employ special switching sequences which apply the null vector once and one of the active vectors twice in each sub-cycle. Stator flux ripple-based analysis brings out the superior performance of the proposed special sequences over the conventional sequences at high modulation indices. Switching loss factor-based analysis shows that the inverter switching loss gets significantly reduced with the proposed PWM techniques at high power factors. Simulations and experiments on a 6kW, 200V, 50Hz SPIM drive show that the THD of stator current is reduced significantly at high speeds by the proposed PWM techniques at the same average switching frequency. In particular, one of the proposed techniques improves the no-load stator current THD by 32% at rated frequency, compared to a state-of-the-art SVPWM technique.
Team Link

Colloquium
2024-07-24 15:00 - 17:00 | Multi-Media Class Room (MMCR), EE Department (Hybrid mode)
Title: Modelling, Analysis and Control of Switched Reluctance Motors

Speaker: THIRUMALASETTY MOULI . of Ph.D. (Engg) in Electrical Engineering under Electrical Engineering
Date/Time: Jul 24 / 15:00:00
Location: Multi Media Class Room (MMCR), EE Department
Research Supervisor: Narayanan G
Abstract:
Switched 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. Hence this thesis focuses on the modelling, analysis 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. However, in applications where shaft temperatures are very high, 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. 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. Further, mutually coupled winding connection is shown to enhance the torque output of both solid- and slitted-rotor SRMs, compared to conventional winding. 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. An experimental method for determining the moment of inertia and frictional torque characteristics of SRMs is proposed. Using these identified parameters, a PI-based speed controller is designed and validated through simulations and experiments, demonstrating its effectiveness in enhancing the performance of SRM drives.
Meeting Link

Ph.D. Thesis Colloquium
2024-07-23 10:00 - 12:00 | MMCR, Hall C 241, 1st floor, EE department
Colloquium Announcement

Title of the Thesis : Power Swing Blocking Protection in Presence of Large Scale Grid Following PV Generation
Name of the Student : Meenu Jayamohan
Name of the Advisor : Dr. Sarasij Das
Degree Registered : PhD (Eng.)
Date and Time : 23rd July, 2024, 10 AM
Location : C 241, MMCR, Electrical Engg Dept

Abstract:
The penetration of Inverter-Based Resources (IBRs) is increasing in power grids due to environmental concerns. The fault behaviour of IBR is quite different than that of Synchronous Generators (SGs). In addition, IBRs usually do not have inherent inertia. As a result, the existing protection schemes, which are traditionally developed for SG-dominated systems, can become ineffective. Stable power swings (SPS) and Unstable Power Swings (UPS) caused by oscillations generated during system disturbances may trigger undesired relay operations. Power swing Blocking (PSB) and Out-of-Step Tripping (OST) techniques have been employed to stop distance relays from malfunctioning during SPS and UPS, respectively. PSB schemes commonly use the magnitude of the rate of change of positive sequence impedance (|dZ/dt|) for SPS detection. This research work focuses on the PSB protection issues in the
presence of large-scale Grid-Following (GFOL) PV generation. A modified IEEE-39 bus system is used for all the studies presented in this thesis.

As the converter controls determine how PV generators behave during transients, the behaviour of SGs used in conventional power systems differs significantly from that of PVs. As a result, existing protection methods, including PSB methods, must be modified to protect the IBR-integrated power systems. This work examines how integrating GFOL PV generation affects power swing impedance (Z) trajectories and |dZ/dt|. The research reveals that the
GFOL PV systems can significantly alter the Z trajectories observed during power swings compared to that of an SG-dominated system. The results presented demonstrate that the penetration of GFOL PV may increase the speed of Z trajectories and, hence, |dZ/dt|, which may, in turn, cause maloperations of the PSB and OST functions. The findings emphasize the critical need to revisit and potentially adapt existing PSB and OST schemes to account for the growing presence of IBRs in power grids.

In the GFOL control strategy, the injected power is controlled with respect to the grid voltages measured at the terminal by the Phase-Locked Loop (PLL). Considering a PLL bandwidth in the range of 2−15 Hz for a weak grid, the PLL dynamics play a significant role in the power swing dynamics. In this work, the impact of various types and control parameters of PLLs on |dZ/dt| and Z trajectories are analyzed using mathematical analysis. Synchronous Reference Frame PLL with additional Low pass filter (LSRF PLL), Multiple Reference Frame (MRF) PLL and Dual Second-Order Generalized Integrator (DSOGI) PLL are used for the study. The impacts of varying penetration of PV and relay locations are also investigated. This study shows that the PLL parameters and bandwidth influence the operation/maloperation of the PSB during SPS.

During Fault Ride-Through (FRT), the PV system can provide additional reactive power to the grid to maintain the voltage at its terminals. This is achieved through the dynamic voltage or reactive power support and is provided in proportion to the drop in terminal voltage using the K-factor. The study also highlights the importance of considering the active power recovery rate to mitigate the oscillatory behaviour of IBR during the fault recovery process. The findings reveal that, following fault removal, the dynamic behaviour of inverters would be significantly influenced by both the K-factor and the active power recovery rate, which may affect the power swing characteristics. This work emphasizes the need for a comprehensive understanding of how dynamic voltage support features and active power recovery interact with the power swing dynamics and influence PSB operation.

Auto-Reclosing (AR) of a circuit breaker is a technique that attempts to re-energize the faulted line after a predetermined time delay. While IEEE Std C37.104-2012 provides guidelines for minimum AR dead time based on arc de-ionization, these may not be sufficient for grids with a high penetration of IBRs. This work explores how varying the three-phase AR dead time can influence the severity of power swings that may occur after consecutive Low-Voltage Ride-Through (LVRT) events in a GFOL PV plant. This finding highlights the potential need to revise
existing minimum AR dead time standards for grids with high IBR penetration levels to ensure reliable system operation.
The studies presented in the previous sections show that existing impedance-based PSB methods might fail in the presence of GFOL PV generation. The lack of inherent inertia of the GFOL PV is one of the reasons behind the increased |dZ/dt| which may cause maloperation of the existing impedance-based PSB schemes. Hence, a novel PSB method is proposed, which uses nodal inertia to re-evaluate the |dZ/dt| values. The effectiveness of the proposed method is verified for both the SG-dominated system and the GFOL PV-integrated system using PSCAD simulations.

EE Talk on Analog Semiconductor innovations in the era of Artificial Intelligence
2024-06-25 10:00 - 17:00
Title: Analog Semiconductor innovations in the era of Artificial Intelligence

Speaker: Dr Sombuddha Chakraborty

Analog Design Manager, TI Kilby Labs (Power)
Date 25/6/2024

Time: 10:00 am

Venue: MMCR EE

Abstract: With the dramatic rise of computation related to the proliferation of AI, powering the GPU hardware poses new challenges and opportunities for power and analog semiconductor companies. This talk will discuss the various semiconductor innovations in development across the industry and how they are shaping data-centre power delivery solutions.
Bio:
Sombuddha Chakraborty (Senior Member, IEEE) received his M.S. and Ph.D. in electrical engineering from the University of Minnesota, Minneapolis, MN, USA, in 2003 and 2006, respectively. Before this, he received his BE from Bengal Engineering College in 2001.
Since 2014, he has been the Design Manager of Power Technology at Texas Instrument’s advanced product development team called Kilby Labs in Santa Clara, CA. His work and research interests include high-density AC/DC and DC/DC power management systems for computing, automotive, and industrial applications using leading-edge processes, package, integration, and circuit techniques to enhance power delivery efficiency.
Sombuddha holds around 30 US Patents and around like number of IEEE publications. He is involved in various IEEE consortiums and serves in IEEE editorial boards.

PhD Thesis Colloquium of Nareddy Kartheek Kumar Reddy
2024-06-24 16:30 - 17:30 | MMCR, Hall C 241, 1st floor, EE department
Name of the Candidate: Mr. Nareddy Kartheek Kumar Reddy

Research Supervisor: Prof. Chandra Sekhar Seelamantula

Date and time: June 24, 2024; 4.30 PM
Coffee/tea will be served during the talk.

Venue: Multimedia Classroom (MMCR), EE Department, IISc.

Title: Tight Frames, Non-convex Regularizers, and Quantized Neural Networks for Solving Linear Inverse Problems

Abstract:
The recovery of a signal/image from compressed measurements involves formulating an optimization problem and solving it using an efficient algorithm. The optimization objective involves data fidelity, which is responsible for ensuring conformity of the reconstructed signal to the measurement, and a regularization term to enforce desired priors on the signal. More recently, the optimization based solvers have been replaced by deep neural networks.

This thesis considers three aspects of inverse problems in computational imaging: (i) Choice of data-fidelity term for compressed-sensing image recovery; (ii) Non-convex regularizers in the context of linear inverse problems; and (iii) Explainable deep-unfolded networks and the effect of quantization of model parameters.

Part-1: Tight-Frame-Based Data Fidelity for Compressed Sensing
The choice of the sensing matrix is crucial in compressed sensing. Random Gaussian sensing matrices satisfy the restricted isometry property, which is crucial for solving the sparse recovery problem using convex optimization techniques. However, tight-frame sensing matrices result in minimum mean-squared-error recovery given oracle knowledge of the support of the sparse vector. If the sensing matrix is not tight, could one achieve the recovery performance assured by a tight frame by suitably designing the recovery strategy? This is the key question addressed in this part of the thesis. We consider the analysis-sparse l1-minimization problem with a generalized l2-norm-based data-fidelity and show that it effectively corresponds to using a tight-frame sensing matrix. The new formulation offers improved performance bounds when the number of non-zeros is large. One could develop a tight-frame variant of a known sparse recovery algorithm using the proposed formalism. We solve the analysis-sparse recovery problem in an unconstrained setting using proximal methods. Within the tight-frame sensing framework, we rescale the gradients of the data-fidelity loss in the iterative updates to further improve the accuracy of analysis-sparse recovery. Experimental results show that the proposed algorithms offer superior analysis-sparse recovery performance. Proceeding further, we also develop deep-unfolded variants, with a convolutional neural network as the sparsifying operator. On the application front, we consider compressed sensing image recovery. Experimental validations on Set11, BSD68, Urban100, and DIV2K datasets show that the proposed techniques outperform the state-of-the-art techniques, where the performance is measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM).

Part 2: Proximal Averaging Methods for Image Restoration and Recovery
Sparse recovery methods are iterative and most techniques typically rely on proximal gradient methods. While the commonly used sparsity promoting penalty is the l1-norm, which is convex, alternatives such as the minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalty have also been employed to obtain superior results. Combining various penalties to achieve robust sparse recovery is possible, but the challenge lies in optimal parameter selection. Given the connection between deep networks and unrolling of iterative algorithms, it is possible to unify the unfolded networks arising from different formulations. We propose an ensemble of proximal networks for sparse recovery, where the ensemble weights are learnt in a data-driven fashion. The proposed network performs superior to or on par with the individual networks in the ensemble for synthetic data under various noise levels and sparsity conditions. We demonstrate an application to image denoising based on the convolutional sparse coding formulation.

Part 3: Deep Unfolded Networks, Quantization, and Explainability

Deep-unfolded networks (DUNs) have set new performance benchmarks in compressed sensing and image restoration. DUNs are built from conventional iterative algorithms, where an iteration is transformed into a layer/block of a network with learnable parameters. This work focuses on enhancing the explainability of DUNs by investigating potential reasons behind their superior performance over traditional iterative methods. Our findings reveal that the learned matrices in DUNs are unstable because their singular values exceed unity. However, the overall DUN gives rise to a recovery accuracy higher than the optimisation techniques. This goes to show that although the linear/affine components of the DUN are unstable, the overall network is stable, which leads us to conclude that it is the nonlinearities, more precisely, the activation functions, that are responsible for restoring stability. This study illustrates an intriguing property of deep unfolded networks, which is not observed in standard optimization schemes.

We also consider quantization of the network weights for efficient model deployment in resource-constrained devices. Quantization makes neural networks efficient both in terms of memory and computation during inference and also renders them compatible with low-precision hardware deployment. Our learning algorithm is based on a variant of the ADAM optimizer in which the quantizer is part of the forward pass. The gradients of the loss function are evaluated corresponding to the quantized weights while doing a book-keeping of the high-precision weights. We demonstrate applications for compressed image recovery and magnetic resonance image reconstruction. The proposed approach offers superior reconstruction accuracy and quality than state-of-the-art unfolding techniques, and the performance degradation is minimal even when the weights are subjected to extreme quantization.

Impact of the research: The novel techniques proposed in this thesis led to improved accuracy in linear inverse problems — sparse signals recovery, compressed image recovery, image deconvolution, and image denoising. The tight-frame based algorithms require fewer iterations to converge, thus reducing the reconstruction time. The quantized neural networks, on the other hand, improved the inference time and reduced the model footprint for efficient deployment on the edge. Analysis of deep-unfolded networks has shown that the learnt weights follow a Gaussian distribution suggesting more efficient initialisation schemes than weights derived from ISTA. We also identified potential local instabilities in a deep learning setting, which are avoided in a conventional optimization setting. The role of the nonlinearity is to restore stability. The analysis showed that while deep unfolded networks have potential instabilities, they can be useful for solving inverse problems.

Biography of the Candidate:
Nareddy Kartheek Kumar Reddy is a PhD student in the Spectrum Lab, Department of Electrical Engineering at the Indian Institute of Science (IISc). He received a Bachelor of Technology (Honors) degree from Indian Institute of Technology Kharagpur in 2016. Subsequently, he worked as a Senior Engineer at Honeywell Technology Solutions from 2016 to 2018, where he focused on developing device drivers for SD card and NAND Flash devices which went into production in Honeywell’s flagship weather radar RDR7000.

Kartheek joined IISc as a Masters student in Signal Processing, and subsequently upgraded to PhD after receiving the prestigious Prime Minister’s Research Fellowship in 2019. He is twice recipient of the Qualcomm Innovation Fellowship, once during 2020 & again in 2023. Kartheek enjoys traveling, reading books and manga, watching anime, and playing video games in his leisure time.

EE Talk on Advancements in Power Electronics for Sustainable and Resilient Energy Systems.
2024-06-13 16:00 - 17:30 | MMCR, Hall C 241, 1st floor, EE department
Title: Advancements in Power Electronics for Sustainable and Resilient Energy Systems.

Speaker: Prof Avik Bhattacharya
IIT Roorkee

Date 13/6/2024

Time: 4:00 pm

Venue: MMCR EE

Abstract: This talk delves into the pivotal role of power electronics in advancing the sustainability, reliability, and efficiency of modern energy systems. Key topics include sustainable microgrids, which utilize advanced power electronic converters to seamlessly integrate renewable energy sources and storage systems for resilient, self-sufficient power solutions. The presentation addresses power quality improvement techniques, leveraging power electronics to mitigate issues such as voltage sags, harmonics, and frequency variations, ensuring stable and high-quality power delivery. The development of multilevel solar inverters, which enhance photovoltaic system efficiency and reduce electromagnetic interference, will be explored, showcasing their design and operational benefits. The rapid expansion of electric vehicles (EVs) underscores the necessity for efficient fast charging infrastructure, where power electronics play a crucial role in reducing charging times and enhancing the reliability of charging networks. Lastly, the discussion highlights resilient space converters, emphasizing innovative power electronic designs that ensure robustness against extreme conditions and cyber threats. Integrating these cutting-edge power electronic technologies significantly advances the pursuit of a more sustainable, reliable, and resilient energy future.

Thesis defense on Estimation of flashovers in the EHV/UHV lines on the east coast due to lightning produced by the Bay of Bengal cyclones
2024-06-10 11:00 - 13:00 | Multi-Media Class Room (MMCR), EE Department (Hybrid mode)
Name of the Candidate: Anirban Chatterjee
Title of the Thesis: Estimation of flashovers in the EHV/UHV lines on the east coast due to lightning produced by the Bay of Bengal cyclones
Degree Registered: MTech (Res) in Electrical Engineering
Time and date: 11.00 AM, 10th June 2024
Venue : MMCR Seminar Hall of EE Department
Meeting Link
Research Supervisor: Udaya Kumar
Abstract
The Bay of Bengal produces a considerable number of cyclones. Many of them invade the east coast of India. They can cause structural damage to towers, substation flooding, and conductor snapping. In many cases, lightning causes several flashovers on the EHV/UHV grid and they are much more in numbers than the former. However, no serious effort was made to estimate the possible number of flashovers caused by the lightning produced by such cyclones. The present work aims to fill this serious gap.
Estimating such lightning-induced flashovers requires several aspects, both electrical and cyclone-related. The lightning strike could be intercepted by the tower/ground wire, or it can strike the phase conductor. The electro-geometric model (EGM), suggested in IEEE standards, is employed to assess the normalized number of strokes striking the phase conductor and intercepted by the tower/ground wire. The associated probabilities are also estimated for typical EHV and UHV lines.
The simulations are carried out by modeling the lines in EMTP with a multi-story model for the tower and the voltage rise in the system is evaluated. Using this information and the BIL of the line, the possibility of flashovers is assessed.
The cyclone’s trajectory, the speed, and the number of lightning flashes produced by them are assimilated from different sources. Modeling the cyclone as a disc like structure,, the line length shadowed as a function of time is calculated. In addition, equivalent ground flash density per square km per hour is also calculated. Combining all this information, the possible number of lighting-induced flashovers in the EHV/UHV grid along the East Coast is estimated. It amounts to 100s of flashover in 400 kV lines and 1000s of flashover in 220kV line.
For engineering purposes, the maximum number of possible flashovers are required. Based on the maximum number of ground flashes per hour across the cyclones for five years, it was estimated. It amounts to a few to a few tens of flashovers in 765kV grid, a few tens to a few hundred in 400kV grid and that for 220kV grid, it amounted to a few hundred to a few thousands.

Faculty Candidate Talk on Blind speaker separation from noisy speech mixtures
2024-06-04 15:00 - 17:00 | Multi-Media Class Room (MMCR), EE Department (Hybrid mode)
Faculty Candidate Talk
Title: Blind speaker separation from noisy speech mixtures
Date and Time: 3:00 PM: 4th JUNE, 2024.
Location: MMCR, EE dept (Online link)

Abstract:
Blind separation of speech mixtures into individual speaker signals is crucial for several speech processing applications, including teleconferencing. These applications require blind speech separation (BSS), i.e., without any additional information about the speakers in the mixture or their count, for both transcription and communication. This task becomes particularly difficult when the number of speakers in the mixture is unknown and recordings are made using a single microphone. In a recent work, we developed a deep-learning-based system for BSS from noisy single-channel mixtures, with an unknown number of speakers in the mixture. The work employs a transformer-based neural network architecture with an attractor generation scheme, allowing it to count the speakers and separate their signals simultaneously. In my presentation, I will share the results from experimental validation on simulated speech mixtures. Our findings show that the system can achieve 18 dB or more improvement in signal-to-distortion ratio and 99% accuracy in speaker counting for mixtures with up to three speakers. Additionally, I will also discuss the insights gained into the model’s internal mechanics, by examining the attention patterns computed in the transformers. We also observed that these findings apply universally across different transformer configurations used in other tasks, such as ambisonic-to-ambisonic and multi-channel speech separation.

Bio: Srikanth Raj Chetupalli received the Master of Engineering and Doctor of Philosophy degrees from the Division of Electrical Sciences, Indian Institute of Science (IISc.) Bengaluru, India, in 2011 and 2020, respectively. He is currently a Postdoctoral Researcher with the International Audio Laboratories Erlangen (a joint institution of the Friedrich-Alexander-Universität Erlangen-Nürnberg and Fraunhofer Institute for Integrated Circuits IIS), Erlangen, Germany. His research interests include speech processing, multimicrophone processing, spatial audio processing, and in particular, source extraction, speech dereverberation, acoustic parameter estimation, and speaker diarization. He was the recipient of the Tata Consultancy Services Research Scholarship from 2015 to 2019.

Ph.D. Thesis Colloquium of Baby Sindhu A. V.
2024-05-24 10:00 - 12:00 | High Voltage Lab Seminar Hall (Hybrid mode)
Colloquium

Candidate’s Name : BABY SINDHU A V
Degree Registered : Ph.D.
Date & Time : 24th May 2024 @ 10.00 AM
Venue : Seminar Hall, High Voltage Lab and in Teams Link
Title : Developmental Studies on Polymeric Nano/Micro Composite
Insulation for Various High Voltage Power Applications

Abstract

The demand for electrical power is increasing day by day necessitating a higher voltage level for power transmission. Also the development of high speed rails , electric vehicles, more electric aircrafts and all electric ships call for improvement in electric motor capacity in those vehicles. Also the use of cast resin type dry transformers in high moisture area and confined area is increasing since it is more reliable in extreme conditions and also they require less maintenance. All these applications demand for better insulating materials which can address all the above issues cost effectively. In recent years, the use of polymeric insulating material in HV power apparatus is increasing. Hence this study focuses on the development of polymeric composite insulating material with better performance for various electrical power applications.
Silicone rubber is a preferred material for use as weathershed material in outdoor polymeric insulators used in high voltage power transmission lines. The tracking & erosion on the insulator surface due to the electrical discharges and corona cutting of the insulator surface are the main issues related to outdoor polymeric insulators and these are addressed in this study. Tracking and erosion performance of silicone rubber filled with nano/micro fillers of different loadings is analysed using Inclined Plane Test (IPT) as per IEC 60587. A computational study on the behavior of the samples subjected to tracking is also done and the same is verified with the experimental results obtained in this work. Corona ageing studies are done by ageing the samples in a corona chamber for 25 hours. Hydrophobicity changes, crack width formation and erosion performance after corona ageing are evaluated. An effort is made to correlate the value of leakage current to the eroded mass and a reliable online condition monitoring tool is also developed as a part of the thesis work.
Again, epoxy is extensively used in many electrical power apparatus such as ground wall insulation of the high voltage rotating machines, as spacer material in Gas Insulated Substations (GIS), as solid insulation in dry type transformers etc. Heat dissipation is an important area of concern when using epoxy as ground wall insulation in rotating machines and as an insulation in cast resin dry type transformer. The performance of epoxy filled with nano/ micron sized fillers are investigated in this study in terms of their heat removal capacity and at the same time retaining their dielectric properties. The improvement in thermal conductivity is correlated with the performance of various composites developed. The formation of track in the ground wall insulation and the failure of the machine is a major issue as far as rotating machines are considered. Hence the tracking time of various epoxy composites are observed and compared. The initiation of a faint track on the surface of the insulator is monitored with the help of a ratio of third harmonic component to the fundamental component. This ratio can be used as an efficient condition monitoring tool for rotating machines by measuring the leakage current online.
In summary polymeric composite insulating materials based on silicone rubber and epoxy with different fillers and loadings and having better electrical and thermal performance than the conventional materials are developed in this study.

PhD Colloquium
2024-05-20 11:00 - 13:00 | MMCR, Hall C 241, 1st floor, EE department
Title of Thesis: Frequent Episode Mining: Efficient Discovery Algorithms and Significance Analysis
Speaker: Mr. Santhosh B. Gandreti
Date/Time: Monday 20th May 2024
11:00 AM
Venue: MMCR, EE Department
Research Supervisor: Prof. P. S. Sastry
Abstract:
Frequent Pattern Mining is a popular area of data mining aimed at discovering interesting patterns that occur often in a given data. These patterns represent structures encapsulating correlations and dependencies among data elements. This thesis focuses on frequent episode mining which is aimed at discovering temporal patterns known as episodes in sequential data of event sequences.
Episodes are collections of event-types constrained by a partial order. An episode is frequent if its number of occurrences exceeds a user-defined threshold. Techniques for mining episodes employ either Breadth-First Search (BFS) or Depth-First Search (DFS) approaches to navigate the episode space. The talk begins by giving a brief introduction to frequent episode mining and various algorithms dealing with discovery of frequent episodes.
The talk next discusses a novel DFS algorithm for discovering injective general episodes and chain episodes, which are two broad subclasses of episodes. The proposed algorithms are more efficient compared to the state-of-art as demonstrated by empirical results. The talk next considers more complex patterns called episodes with simultaneous events, where the episodes contain multiple event-types at the same time instant. A novel BFS algorithm is presented for discovering serial episodes with simultaneous events. Through simulations on both synthetic and real data sets, the effectiveness and efficiency of the proposed algorithm is demonstrated.
The next part of the talk discusses significance analysis that assesses the statistical relevance of episodes and presents two novel approaches for significance analysis; one for non-overlapped occurrences under Markov-null hypothesis and the other for minimal occurrences under IID-null hypothesis. This analysis helps determine an episode-specific frequency threshold for the episode to be statistically significant, providing a more nuanced understanding of pattern relevance. For both the above mentioned cases, specialized Markov chains capturing the occurrences of interest are derived for a given episode, which help in computing episode-specific thresholds on frequency, to access its significance. Effectiveness of the proposed methods is confirmed through empirical studies.

Open Ph.D. Thesis Defense of Mr. Ranashree Ram
2024-05-08 10:30 - 11:30 | High Voltage Lab Seminar Hall (Hybrid mode)
Ph.D. Thesis Open Defense
Student Name : Ranashree Ram
Thesis Title : Developmental Studies on a Multistage Induction Coilgun-Based Electromagnetic
Launcher
Place : High Voltage Lab Seminar Hall / MS Teams
Date & Time : 8th May 2024, 10.30 AM
Microsoft Teams Link
Abstract
The archetypal chemical propellant-based launchers (e.g., guns, missiles, spacecraft launchers, etc.) with their hot trailing plume has been widely deployed over the decades for various applications. However, because of certain disadvantages of these systems and the physical limitations associated with their designs, electromagnetic launchers (EMLs) seem to offer an alternative way forward as the next-generation hypervelocity (>3 km/s) launchers. The multistage induction coilgun is one such futuristic class of EMLs that works on the principle of electromagnetic induction between an array of coils (or drive coils), which are wound on a long barrel of appropriate length, and an electrically conducting projectile (or armature) placed inside the barrel. Previously charged high-voltage capacitor banks are sequentially discharged into the coils through solid-state switches leading to the generation and flow of very high pulsed currents (kA) through the coils. Time-varying magnetic flux thus produced by the pulsed currents through the coils interact with the projectile inside and induce a resultant current on it. The propulsive electromagnetic force exerted on the projectile is a product of the current through the coil, the induced current on the projectile, and the mutual inductance. The “turn on” and “turn off” of the coils of the various stages must be precisely and appropriately synchronized during the multistage operation to achieve a higher projectile velocity and this makes its successful design and operation a challenge. Owing to its high confidentiality in defense and space applications, not much can be known from the published works. In the present work a four-stage induction coilgun has been designed and developed in the laboratory. The research work presented in the thesis aims to understand the factors contributing to achieving a higher muzzle velocity for a projectile of a given mass while launching a payload with the coilgun. The projectile of a coilgun can be either sleeve-type (ring-shaped projectile) or solenoid-type (multi-turn projectile).
The author also designed and fabricated a high-speed infrared transmitter-receiver-based sensor (with 25 ns rise and fall time) to quickly sense the moving projectile (or armature) inside the barrel. The triggering instant of the subsequent stage coils of a multistage coilgun critically depends on the projectile’s position inside the barrel. The projectile will fail to achieve the highest muzzle velocity if the subsequent stage coils are not optimally triggered in a sequence. The fast-moving projectile through the barrel necessitates the fast sensing of its position inside the barrel. In addition, the author has also designed, developed, and fabricated a high-speed gate driver circuit with a peak 25 kV DC isolation for the signal circuit from the high voltage power circuit within a compact space of the printed circuit board (PCB) to trigger the high-voltage SCRs used for triggering the pulsed power source of each stage of the coilgun..
The large current flowing through each stage coil creates EMI problems in the coilgun. The EMI issues corrupt the sensor data, which prevents successful sensing of the projectile’s position. Also, EMI causes the SCRs to trigger the coils spuriously even when the projectile has not reached its optimal triggering position inside the coil. Synchronizing the triggering of stages by preventing the EMI issues is a significant challenge and is very important in successfully operating a multistage induction coilgun. The author could successfully synchronize the stages of the coilgun by preventing spurious triggering of the SCRs using appropriate EMI mitigation techniques.
The influence of the capacitance of the capacitor bank used in the high voltage pulsed power supply on the optimum triggering position of the projectile inside the drive coil of the coilgun has been analyzed. An empirical relationship between the projectile velocity and the charging voltage of the capacitor bank has been formulated for the first time in this thesis. The subject of the study presented in this thesis also focuses on analyzing the parameters on which the efficiency of an induction coilgun depends and how it can be optimized. Study has been performed to optimize the shape and dimensions of the projectile to achieve the highest muzzle velocity. The dependency of the projectile motion on the flow of induced current in the subsequent stages has been analyzed. The study also focuses on establishing an approach to choosing a proper distance between the stages in a multistage induction coilgun.
A comprehensive and explicit analysis has been performed to study and explain the reasons behind the differences in the optimum triggering positions of the projectile inside each stage coil and the achieved muzzle velocities for different arrangements of the drive coil current directions in a multistage induction coilgun.

Defense Talk on Investigating Neural Mechanisms of Word Learning and Speech Perception
2024-04-23 10:30 - 11:30 | Multi-Media Class Room (MMCR), EE Department (Hybrid mode)
Title
Investigating Neural Mechanisms of Word Learning and Speech Perception: Insights from Behavioral, Neural, and Machine Learning Perspectives
Speaker: Ms. Akshara Soman
Time: 1030am-1130am
Venue: MMCR, EE, C241 and on the Teams-Meeting-Link

Abstract
The process of language learning and speech perception is a remarkable feat of the human brain, involving complex neural mechanisms that allow us to understand and communicate with one another. By employing a multidisciplinary approach, this talk sheds light on the underlying processes involved in word learning and speech perception.
The talk begins by examining how imitation of sounds influences language learning and language discrimination using EEG signals. Results show that time-frequency features and phase in the EEG signal contain information for language discrimination. Further experiments confirm these findings and analyse improvements in pronunciation over time, identifying frontal brain regions involved.
The talk then discusses how learning patterns change when semantics are introduced. Participants learn Japanese words and undergo ERP analysis, revealing distinct EEG patterns for newly learned words. Notably, a delayed P600 component emerges, suggesting short-term memory processing. Based on the above neuro-behavioural experiments, a machine model is proposed to compare human-machine performances in audio-visual association learning. The model performs comparable to humans in learning with few examples, with slightly inferior generalisation abilities.
Moving to naturalistic stimuli, the talk analyses continuous speech perception using a deep learning model. This model achieves 93% accuracy in stimulus-response modelling on a speech-EEG dataset, surpassing previous efforts. It demonstrates the role of word-level segmentation during speech comprehension in the human brain. We further extend this study to investigate speech perception in complex listening environments where multiple speech streams are heard simultaneously. Our proposed model, based on Long Short-Term Memory (LSTM), reveals that the human brain prioritises understanding the semantics rather than the acoustics under such challenging listening conditions. The proposed model has potential applications in speech recognition, brain-computer interfaces, and attention studies.
Overall, the thesis enhances our understanding of language learning, speech comprehension, and the neural mechanisms involved. It provides insights into familiar and unfamiliar language processing, semantic effects, audiovisual learning, and word boundaries in sentence comprehension. These findings have implications for both human language learning and the development of machine systems aimed at understanding and processing speech.
Coffee/Tea will be served before the talk.

Colloquium On Plasma activated/assisted solid wastes in diesel exhaust treatment: a case study with agricultural, industrial and composite wastes
2024-04-23 09:30 - 11:30 | HV seminar Hall
Name of the candidate: Ms. Apoorva Sahu
Research Supervisor: BS Rajanikanth
Degree Registered: PhD
Department: Electrical Engineering
Title of the Thesis: Plasma activated/assisted solid wastes in diesel exhaust treatment: a case study with agricultural, industrial and composite wastes
Time and Date: 9.30 AM, 23rd April 2024 (tuesday)
Venue: High Voltage building seminar hall
Synopsis
The consumption of crude oil is increasing every day particularly in developing countries like India which is the third largest consumer of crude oil in the world, utilizing on an average around 160 million litres per annum of which 30% constitutes diesel fuel. More than 50% of the NOx and hydrocarbons in air come from the diesel exhaust affecting the health of human beings, vegetation, and environment. While the solid particulate in the exhaust is taken care to a greater extent by the mechanical filters it is the gaseous pollutants such as oxides of nitrogen (NOx), oxides of carbon, hydrocarbons (HC) etc., that need to be addressed as they cause several health-related ailments in addition to acid rain, global warming, smog etc. It is timely to work on the development of economical and efficient pollution control strategies. On the other hand, issues that is affecting our country India currently are accumulation of wastes from utility industry, mariculture industry and agriculture industry. The prominent amongst them are fly ash, red mud, foundry sand, iron ore tailings, lignite ash, rice husk, wheat straw and sugarcane bagasse etc. Accumulation of these wastes are in several million tons per annum in India. Any proposition in recycling waste is a welcoming step.
Efforts are continuously being made for the past three decades to mitigate these gaseous pollutants, particularly NOx, at various levels by changing the fuel composition, engine modifications, pre-combustion techniques and post-combustion (aftertreatment) techniques. The existing post-combustion mode technique “catalyst-based converters and adsorbent based techniques” are becoming expensive owing to the short life, dependency on noble metals, more vulnerability to acidic coating, bulk usage of adsorbents etc. In this regard the application of non-thermal plasma or electric discharge plasma for pollution control aided by additional techniques is slowly gaining popularity in the past few years. Discharge plasma ionizes the atoms at normal temperature and atmospheric pressure (NTP) thus creating an oxidative environment resulting in chemical reactions such as reduction, oxidation, decomposition etc. However, among these reactions it was observed that oxidation was dominating, to a certain extent the oxidised by-products in the plasma appeared to be less hazardous to humans than to nature. This led to the redesigning of plasma reactors with the intention of enhancing the energy in the charged species favouring reduction reactions instead of oxidation ones but not without serious limitations with respect to the gas flow.
Application of electrical discharges for environmental purposes lies in the basic concept of treating the pollutants, particularly the gaseous ones, with plasma excited species. It is observed that plasma alone is insufficient for the successful treatment of any of the gaseous pollutants due to the oxidative environment prevailing in the discharge plasma at atmospheric conditions. This necessitated inclusion of additional treatment technique along with plasma leading to the origin of plasma catalysis/plasma adsorption methods where in the catalytic materials were kept inside the plasma environment (plasma catalysis) or the adsorbent materials are cascaded with plasma (plasma adsorption). It should be noted here that the total cost involved in the proposed technique, should be lower than that associated with conventional catalyst-alone or adsorbent-alone techniques so that the proposed ones can be a promising economic alternative to the conventional ones. That said, cascading commercially available catalysts/adsorbent with plasma can never be a cheaper alternative. Several research works, therefore, started by blending plasma with other lab made catalysts/adsorbents but the DeNOx efficiency was not significant.
Present work aimed at studying the NOx abatement in diesel engine exhaust at controlled laboratory condition using electrical discharges. The intention of the study is to provide not only an efficient but also an economical solution for reduction of the NOx pollutants. Keeping this in mind, it was decided to utilize electrical discharge technique in association with abundantly available solid wastes in India be it from industrial, mariculture or agriculture domains. Given the whole spectrum of parametric variations the thesis plan was carefully drawn to touch upon the following variations: type of corona electrodes, type of applied high voltage, type of solid wastes, type of gas treatment. Four types of electrodes were studied that include needle plate, metal film, helical wire and pipe type. Type of voltage involves fast rising repetitive pulses at 80 Hz, power frequency and high frequency AC. The solid wastes comprise of three categories namely (a) industrial/mariculture wastes that include namely iron tailings, lignite ash, red mud, foundry sand, waste tiles and copper slag, oyster shell (b) agricultural wastes including coffee husk, sugarcane waste, mulberry husk, rice husk, ragi husk, corn husk, wheat husk, pine, ground nut and areca nut husk and (c) composite wastes which include a blend of waste tiles + foundry sand, copper slag + red mud, iron tailings + waste tiles, red mud + waste tiles, foundry sand + red mud and foundry sand + iron tailings. The type of gas treatment involves treating the exhaust with only plasma/plasma catalysis/plasma adsorption/thermal catalysis utilizing catalytic properties of metal oxides present in the industry wastes or porous nature of the industry wastes. A comparison was also made by replacing the industrial wastes with commercial NOx catalysts. Important contribution of this research work can be summarized as: (a) with plasma catalysis approach the NOx removal efficiency gets enhanced by a factor of 5.3-6.7 compared to only plasma. (b) with plasma adsorption approach the NOx removal efficiency gets enhanced by a factor of 4-6 compared to only plasma. (c) Fe2O3/TiO2 present in red mud can act as photo catalysts in oxidizing NO through plasma generated ethyl nitrate in the plasma cascaded red mud adsorption process (d) Amongst the agricultural wastes, ground nut husk-based pellets exhibited 83% NOx removal efficiency (e) The newly developed metal film based DBD reactor enhances surfaces discharges far better than the helical wire reactor (f) commercial catalysts performed much better in NOx removal under plasma catalysis mode when compared to thermal catalysis mode. Further, plasma catalysis with industrial wastes such as iron tailings and oyster shell yielded better/similar DeNOx efficiency when compared to that with commercial NOx catalysts thus, justifying the usage of cheaper industrial wastes instead of expensive commercial ones.

Colloquium on Development of Pulsed Power Systems and Tooling Coils for Electromagnetic Manufacturing Applications
2024-04-15 15:00 - 17:00 | HV seminar Hall
Title: Development of Pulsed Power Systems and Tooling Coils for Electromagnetic Manufacturing Applications
Speaker: DEEPAK KAUSHIK . of Ph.D. (Engg) in Electrical Engineering under Electrical Engineering
Date/Time: April 15 / 15:00:00
Location: HV Lab Seminar Hall
Research Supervisor: Joy Thomas M
Abstract:
Electromagnetic pulse manufacturing is an emerging non-conventional manufacturing technique used for the forming of workpieces at very high strain rates. The manufacturing assembly consists of the tooling coil (or actuator), the workpiece, a pulsed power source, and finally, a suitable die as per the required final shape that needs to be achieved. In this work, the author focuses on developing high voltage and high current pulsed power sources as well as the tooling coils required for the electromagnetic forming applications. The study encompasses theoretical simulations and practical experiments pertaining to electromagnetic forming applications involving workpieces made of sheet metal and tubular structures. Electromagnetic forming is a complex multi-physics process that involves electromagnetic, thermal, and mechanical fields which are strongly coupled to each other. Initially, the author focused on understanding the interaction between various physical fields involved and development of fast analytical methods to predict the deformation in the workpiece due to their interaction. Impact velocity and the pressure applied to the workpiece are critical aspects that determine the workpiece’s deformation. Based on the developed coupled models, the author has proposed techniques to control the impact velocity and the applied pressure on the workpiece and designed the Pulsed Power Systems to achieve the same. The tooling systems are the most vital components in the electromagnetic forming process. This is because they generate the necessary pressure on the workpiece to achieve the final desired shape. The author has designed and developed various tooling coil assemblies for sheet metal forming and operations on tubular workpieces. The author has developed a novel clamp-on type electromagnetic tooling coil for agile manufacturing of tubular components. The designed actuator offers several advantages over conventional helical tooling systems, including a pressure distribution which does not produce any end effects as opposed to the pressure on the workpiece dropping to 58% of the peak in a conventional helical actuator. It is also marginally less sensitive to standoff distance, where the reduction in the peak pressure is only 13% as compared to the conventional actuator, which shows a drastic drop of 56% as the standoff distance varies from 2 mm to 5 mm. The proposed clamp-on tooling coil is also robust to failure as the stress on the proposed actuator is compressive and reinforces it against the toroidal former. In contrast, the stress on the conventional helical actuator coil is repulsive, requiring external reinforcements. The proposed actuator is openable and can be reused easily for repeated applications. For sheet metal forming, the author optimized the uniform pressure actuator and proposed a high-efficiency dual-channel uniform pressure tooling coil (UPTC). The salient features of the designed dual-channel actuator are as follows. The designed tooling coil draws 6.2% more current and applies 24.9% more force than the conventional UPTC for the same pulsed power source parameters. The spatial distribution of the pressure is identical in both the tooling coils, but the magnitude of the pressure in the proposed dual-channel tooling coil is about 23% higher. In addition, the proposed tooling coil also has better capabilities for handling electromagnetic stress during the forming process. For the first time, the author has integrated attractive and repulsive sheet metal forming technology into a single assembly. The author introduces a novel design and analysis of a dual-mode universal uniform pressure tooling coil that integrates both forming techniques, simplifying the requirements for the pulsed power system. Finally, the author has studied the effect of tooling coil designs on the efficiency of the forming process. The study aims to find the effect of coil design on the forming efficiency and compares the performance of multi-turn and multi-layer coils over the existing tooling coils. The study has been validated using the development of multi-layered uniform pressure tooling coils with experiments performed on free bulging of AA-6061-T6 sheets. The author found that the multi-layered tooling coils outperformed the single-layered wire-wound coils for all values of the system capacitances used.
Meeting Link

Talk On Making Machine Learning Models Safer and Better: Data and Model Perspectives
2024-04-12 16:00 - 17:30 | B306 , EE Dept
Abstract: As machine learning systems are increasingly deployed in real-world settings like healthcare, finance, and scientific applications, ensuring their safety and reliability is crucial. However, many state-of-the-art ML models still suffer from issues like poor out-of-distribution generalization, sensitivity to input corruptions, requiring large amounts of data, and inadequate calibration – limiting their robustness and trustworthiness for critical real-world applications.
In this talk, I will present a broad overview of different safety considerations for modern ML systems. I will then proceed to discuss our recent efforts in making ML models safer from two complementary perspectives – (i) manipulating data and (ii) enriching the model capabilities by developing novel training mechanisms. First, I will discuss our work on designing new data augmentation techniques for object detection followed by demonstrating how, in the absence of data from desired target domains of interest, one could leverage pre-trained generative models for efficient synthetic data generation. Next, I will introduce a new paradigm of training deep networks called model anchoring and show how one could achieve similar properties to an ensemble but through a single model. I will specifically discuss how model anchoring can significantly enrich the class of hypothesis functions being sampled and demonstrate its effectiveness through its improved performance on several safety benchmarks. Finally, I will present our efforts in proactively identifying samples on which a model would fail through a novel model counterfactual synthesis technique by leveraging foundation models (e.g., GPT family and CLIP). I will then conclude by highlighting exciting future research directions for producing robust ML models through leveraging multi-modal foundation models.

Bio: Kowshik Thopalli is a Machine Learning Scientist and a post-doctoral researcher at Lawrence Livermore National Laboratory. He is currently mentored by Dr. Jay Thiagarajan. His research focuses on developing reliable machine learning models that are robust under distribution shifts. He has published papers on a variety of techniques to address model robustness, including domain adaptation, domain generalization, and test-time adaptation using geometric and meta-learning approaches. His expertise also encompasses integrating diverse knowledge sources, such as domain expert guidance and generative models, to improve model data efficiency, accuracy, and resilience to distribution shifts. He received his Ph.D. in 2023 from Arizona State University under the mentorship of Dr. Pavan Turaga.
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All are welcome.

Colloquium on Estimation of flashovers in the EHV/UHV lines on the east coast due to lightning produced by the Bay of Bengal cyclones
2024-04-12 09:30 - 11:00 | HV seminar Hall
Name of the Candidate: Anirban Chatterjee
Title of the Thesis: Estimation of flashovers in the EHV/UHV lines on the east coast due to lightning produced by the Bay of Bengal cyclones
Degree Registered: MTech (Res) in Electrical Engineering
Time and date: 9.30 AM, 12th April 2024
Venue: High Voltage Laboratory Seminar Hall of EE Department
Research Supervisor: Professor Udaya Kumar
Abstract
The Bay of Bengal produces a considerable number of cyclones. Many of them invade the east coast of India. They can cause structural damage to towers, substation flooding, conductor snapping, etc. In many cases, through lightning, they cause several flashovers on the EHV/UHV grid. However, there is no serious effort to estimate the possible number of flashovers caused by the lightning produced by such cyclones. The present work aims to fill this serious gap.
The estimation of such lightning-induced flashovers requires several aspects, both electrical and cyclone-related. The lightning stroke could be intercepted by the tower/ground-wire, or it can strike the phase conductor. The electro-geometric model(EGM), suggested in IEEE standards, is employed for assessing the normalized number of strokes striking the phase conductor and intercepted by the tower/ground-wire. The associated probabilities are also estimated for typical EHV and UHV lines.
The relation between the peak stroke current and the rise time is made based on the literature. Then, by modelling the lines in EMTP with a multi-story model for the tower, simulations are carried out to deduce the corresponding voltage rise. Using this information and the BIL of the line, the possibility of flashovers is assessed.
The trajectory of the cyclone and the speed, along with the number of lightning flashes produced by them are assimilated from different sources. Modelling the cyclone as a disc above ground, the line length shadowed as a function of time is calculated. In addition, equivalent ground flash density per square km per hour is also calculated. Combining all these information, the possible number of lighting-induced flashovers in the EHV/UHV grid along the east coast is estimated. Within three to four days the number of such flashover incidents can range from a few to few tens of flashovers within a time span of two to four days.

Colloquium On Investigation Of Direct Lightning Strike To High Voltage Transmission Lines
2024-04-10 09:30 - 11:30 | HV seminar Hall
Name of the Candidate : Mr. Sukesh A
Degree Registered : Ph.D.
Title of the thesis : Investigation Of Direct Lightning Strike To High Voltage Transmission Lines
Time and date : 9.30 AM, 10th April 2024
Venue : High Voltage Laboratory Seminar Hall
Research supervisor : Udaya Kumar
ABSTRACT
Lightning continues to be the single largest natural cause of line outages. With high voltage lines spanning millions of kilometres around the globe, it has been a serious concern to transmission line engineers. Quite unfortunately, the lightning performance of ultra-high voltage lines falls far below that estimated from the available models. There are two reasons for this difference, namely, inadequacy in the present standards in evaluating the lightning attachment process and in ascertaining the surge response of these tall lines.
The recent progress in simulating the attachment process is dealt with in the latest CIGRE technical brochure. It is shown that the simplified model proposed over there can account for the observed differences between estimated using older models and the field data.
Different modelling approaches have been employed to evaluate lightning surge response. The most popular approach in power engineering is a lumped current source in parallel with an impedance. However, there is no consensus among researchers regarding the value of impedance to be used in such models. Based on observations over tall towers, it has been inferred that the peak value of the lightning current depends on the strike object. Importantly, a seven years long study based on measurements on heavily instrumented UHV lines in Japan has provided additional information that is not in line with expectations.
An alternative modelling approach for evaluating the lightning surge response of lines is to make use of the return stroke models. Among the different categories of return stroke models available, only the transmission line and electrodynamic models can, in some sense, be employed for modelling a direct strike to the transmission line. Even though current is not assumed in the transmission line models, the mode of propagation is assumed as TEM mode, which is not true on the channel, at least in the initial stages of current evolution. Even though the mode of propagation is not assumed in electrodynamic models, usually, a lumped excitation is assumed.
Therefore, a model that does not assume the excitation and the mode of propagation is essential. A self-consistent return stroke model recently proposed by the group would be an ideal tool for the required investigation. It basically emulates basic essential physical processes along with accurate tracing of dynamic electromagnetic fields using time-domain thin-wire formulation.
In order to apply this model to simulate a direct strike scenario to a transmission line, the field computation methodology had to be extended from the axisymmetric to a fully three-dimensional wire geometry. Further, wire junctions need to be considered. These were achieved and for the latter, spatial basic function is borrowed by the Numerical Electromagnetic Code.
Using this extended self-consistent return stroke model, detailed simulations are carried out for a direct strike to the transmission line. The peak current during a strike-to-phase conductor and strike-to-ground (or simplified ground wire-tower structure) are deduced. Using this consistent modelling approach, it has been clearly shown by modelling that the peak current value for the same conditions reduces to half of that for a strike to ground/ground wire-tower structure. The physical reason for this difference has also been identified. Furthermore, the mode of propagation of the stroke current along the phase conductor is also assessed. In summary, this work has delved into some of the fundamental aspects of lightning strikes.

EECS Symposium
2024-04-04 09:00 - 2024-04-05 17:00 | IISc
The EECS division cordially invites you to the EECS Symposium on 4th & 5th April 2024.
For more details please see: https://eecs.iisc.ac.in/EECS2024
Registration link for the event: EECS Symposium 2024 Registration Form.

PhD Thesis defence on Imaging Inverse Problems
2024-03-26 09:00 - 11:00 | Multi-Media Class Room (MMCR), EE Department (Hybrid mode)
Title : Improved Derivative-based Regularizations for Imaging Inverse problems

Student : Manu Ghulyani

Advisor : Prof. Muthuvel Arigovindan

Thesis Examiner: Prof. Ajit Rajwade
Department of Computer Science and Engineering,
IIT Bombay.

Date and Time: 26.03.2024 (Tuesday), :.9:00 am

Venue : MMCR, Department of Electrical Engineering

Also online in Teams

Abstract:

Images undergo degradation during the capturing process due to physical limitations inherent to the capturing devices. Addressing this degradation and recovering high-quality images constitute the image recovery problem, a crucial concern with diverse applications across various fields such as biology, astronomy, and medicine. The enhancement of captured image resolution significantly influences these disciplines. Examples of this problem include tasks like reconstructing computed tomography images, magnetic resonance imaging, image deconvolution, and microscopic image reconstruction.

Image recovery is frequently approached using regularization techniques, with derivative-based regularizations being popular due to their ability to exploit image smoothness, yielding interpretable results devoid of introduced artifacts. Total Variation regularization (TV), proposed by Rudin, Osher, and Fatemi, is a seminal approach for image recovery. TV involves the norm of the image’s gradient, aggregated over all pixel locations. As TV encourages minimal values in the derivative norm, it leads to piece-wise constant solutions, resulting in what is known as the “staircase effect.” To mitigate this effect, the Hessian Schatten norm regularization (HSN) employs second-order derivatives, represented by the pth norm of eigenvalues in the image hessian vector, summed across all pixels. HSN demonstrates superior structure-preserving properties compared to TV. However, HSN solutions tend to be overly smoothed. To address this, we introduce a non-convex shrinkage penalty applied to the Hessian’s eigenvalues, deviating from the convex lp norm. While the analytical form of this penalty was unknown, we derived the algorithm using proximal operations. We established that the proposed regularization adhered to restricted proximal regularity, ensuring the algorithm’s convergence. The images recovered by this regularization were sharper than the convex counterparts.

In the subsequent work, we extend the concept of the Hessian-Schatten norm. By encompassing Schatten norms of the Hessian and introducing a smoothness constraint, we broaden the scope of Hessian Schatten norm. The resulting regularization can be derived as a Lagrange dual of the Hessian Schatten norm, akin to the total generalized variation. Furthermore, we present an efficient variable splitting scheme for solving image restoration challenges.

Total Generalized Variation (TGV) represents an important generalization of Total Variation. TGV involves multiple orders of derivatives, with higher-order TGV leading to improved recovered image quality. This enhancement has been validated through numerical experiments in image denoising. Consequently, a demand arises for an algorithm capable of solving TGV for any order. While various methods address TGV regularization, many are confined to second-order TGV, and only a few explore orders greater than three for image recovery with TGV regularization. To our knowledge, no algorithm resolves image recovery challenges employing TGV regularization for orders exceeding three under a general forward model. This challenge arises from the intricate nature of TGV representation. We surmount this obstacle by presenting two simple matrix based representations of TGV: the direct and compact forms. We prove the equivalence of both forms with the original TGV definition. Leveraging the compact representation, we propose a generalized ADMM-based algorithm to solve TGV regularization for any order.

ALL ARE WECOME.

PhD Oral Exam
2024-03-25 08:00 - 11:00
Title: Reduced Electrolytic Capacitor-Based Single-Phase Converters: Topologies, Control, and StabilityName of the Student: Anwesha MukhopadhyayName of the Advisor: Prof. Vinod JohnDegree Registered: Ph.D.Date and Time: 25th March, 2024, 08:00 AMTeams Meeting Link:Abstract: Single-phase power converters find wide applications as inverters. Applications ranging from a few hundred Watts for household solar micro-inverters, to multi-Megawatt levels for electric traction power train, single-phase converters are adopted worldwide.In single-phase power conversion, there is always a mismatch between the instantaneous input and output power, producing a second-harmonic ripple in the dc link current. Electrolytic capacitors are conventionally deployed for filtering the second-harmonic ripple due to their low cost and excellent energy density. However, their frequent premature failures often compromise the lifespan of the converters. In recent technologies demanding high power density, active filters have minimised the electrolytic capacitors in the circuit. However, the cost, efficiency, and power density trade-offs need scrutiny before adopting an active filter topology.Among the reported active filters (AF) for second-harmonic ripple mitigation, series capacitor stacked buffer (SSB) topology has emerged as a popular choice owing to its high efficiency and compactness. The use of low VA-rated switching devices enables achieving the high efficiency equivalent to passive filters. Despite its prospective utility in a range of applications, the model of the SSB, essential for implementing functional engineering control strategies under a wide range of operating conditions, is not discussed in existing literature.In the first part of the work, the plant model for controlling the buffer converter in voltage control mode as well as current control mode is developed. Using the proposed model, a closed-loop control scheme is developed, which ensures a fixed-frequency switching of the buffer converter. A step-by-step controller design procedure is elaborated, and the controller gain limit is identified to ensure closed-loop stability.Based on the developed SSB model, an average current mode control is implemented in the second part of the work. Unlike the existing methods of current mode control, in the proposed scheme, the current reference is estimated without using the dc-link current sensor, which is verified experimentally.The SSB-based existing topologies, though promising for many applications, are not realised with minimum switch counts. As opposed to four switch H-bridge-based buffer converter, two switch-based series capacitor stacked buffer converter topologies are synthesised in this part of the work. The generalised topology synthesis procedure and control challenges are identified. One of the proposed two-switch-based topologies named Series Capacitor Boost Hybrid Filter (SC-BOHF) is implemented and verified experimentally.Apart from the active solutions, an alternative dc bus filter structure, consisting of a combination of an inductor (L) and capacitor (C), tuned at the second harmonic (2ω) frequency, reduces the capacitance requirement, enhancing the likelihood of deployment of film capacitors. The proposed solid-state tuning restorer (SSTR) offers consistent filtering performance of the LC filter under frequency and parameter variations. As per the tuning requirement of the LC filter, SSTR acts as an electronic inductor or capacitor. It also ensures a graceful degradation in the filter characteristics during SSTR converter failure modes. The evolution of the SSTR configuration, analysis of its VA rating, and control requirements are studied in this work.The realisation that SSTR requires to behave as an electronic inductor and capacitor as per the sense of LC filter detuning motivated this part of the work, where a unified active capacitor and inductor (UACI) is proposed and implemented without using any dc capacitor. Based on the current reference, the proposed configuration emulates inductive or capacitive characteristics and smoothly transits from one characteristic to another. The operation of the proposed UACI is studied, and a closed-loop control scheme is developed.All the proposed methods are validated on hardware prototypes that have been developed as a part of the research. —————— ALL ARE WELCOME —————

Phd Thesis Defense
2024-03-07 10:00 - 12:00
Title: Pulse Width Modulation Techniques of Two-level Inverter Fed Asymmetrical Six-phase Machine Drive in Linear and Overmodulation Regions
Name of the Student: Sayan Paul
Name of the Advisor: Dr. Kaushik Basu
Degree Registered: Ph.D.
Date and Time: 07th March, 2024, 10:00 AM
Teams Meeting Link
ALL ARE CORDIALLY INVITED.
Abstract:
Multi-phase machines (MPMs) have more than three windings in their stator, rotor, or both. With the broader adoption of power-electronic converters for efficient driving of the machines, MPMs are gaining attention in different applications due to their certain advantages over three-phase machines. One such advantage is higher fault tolerance due to having higher phase redundancy, which makes it suitable for safety-critical applications like electric vehicles (EVs), ship propulsions, electric aircraft, etc. Another advantage is that MPMs allow power splitting across multiple phases. Hence, the power rating per phase drive unit becomes low, making it suitable for high-power applications like railway traction, pumps, compressors, etc. Recent literature also proposes using the same multi-phase converter fed MPM, otherwise used for propulsion, as an onboard battery charger; it substantially reduces space, weight, and cost. During charging mode, the leakage inductance of the machine provides the required inductance for the grid connection, and MPM’s higher degrees of freedom are used to lock the rotor electronically. An asymmetrical six-phase machine (ASPM) is one of such MPMs and is very common in EVs. This thesis aims to devise the pulse-width modulation (PWM) techniques of a two-level six-phase inverter fed ASPM to improve the overall drive efficiency.
ASPM has two sets of balanced three-phase windings, which are spatially shifted by 30 degrees (electrical angle). In one of the popular configurations, the two three-phase winding sets are connected in star fashion with two isolated neutral points. This machine is conventionally analyzed in two two-dimensional (2D) orthogonal subspaces. One of these subspaces is associated with electromagnetic energy transfer and torque production. The other subspace doesn’t transfer energy through the air gap and the equivalent circuit in this plane, consisting of winding resistance and leakage inductance, provides a low impedance. Therefore, excitation of this non-energy-transferring subspace causes a large current and associated copper loss. Any PWM technique of ASPM aims to synthesize the desired voltages in the energy-transferring plane and minimize the applied voltage in the non-energy-transferring subspace.
Linear modulation techniques (LMTs) of ASPM apply zero average voltage in the non-energy-transferring subspace and synthesize the desired voltages in the energy-transferring plane on an average over a switching cycle. It is desired that these LMTs should avoid more than two switching transitions of an inverter leg within a carrier period to limit the instantaneous switching loss. Through an innovative approach, our work finds a way to account for all possible infinitely many LMTs that follow the rule of at most two transitions per leg. But each of them results in a different current ripple performance. Ripple current is inevitable in PWM converters and should be minimized through modulation to reduce the associated copper loss. The total ripple current RMS of ASPM is contributed by both energy-transferring and non-transferring planes. One machine parameter also impacts this performance, which is the ratio of high-frequency inductances in these two subspaces. For all reference voltage vectors and the whole feasible range of the machine parameter, our work finds the techniques with minimum current ripple RMS among the above infinite possible LMTs through numerical optimization. A hybrid PWM strategy is proposed with these optimal techniques, which outperforms all existing techniques in terms of current ripple performance.
Overmodulation (OVM) techniques of ASPM attain higher voltage gain in energy-transferring subspace than LMTs by applying non-zero average voltage in the non-energy transferring subspace. This operation doesn’t cause any torque ripple, but the applied voltage in non-energy transferring subspace should be minimized to reduce unwanted current and associated loss. The existing OVM technique in the literature minimizes this average voltage from the space-vector perspective with a pre-defined set of four active vectors. To find the best technique, one needs to perform the above minimization problem with all possible sets of active vectors, which can give higher voltage gain. So, this requires the evaluation of a large number of cases. In this thesis, we have formulated the above minimization problem in terms of average voltage vectors of two three-phase inverters, where active vectors need not be specified beforehand. Thus, the analysis is more general. Following the above analysis, eight switching sequences in one part and two in another part of OVM are derived, which attain the minimum average voltage injection in the non-energy transferring subspace.
Although the above OVM sequences apply the same average voltages in the two subspaces, they have different high-frequency ripple currents due to having different switching strategies. The current ripple study of the OVM techniques of ASPM is missing in the literature. Hence, one of our works in the thesis studies the current ripple performances of the above PWM sequences in the OVM region, which apply minimum average voltage in the non-energy-transferring subspace. The article finds the sequence with the best ripple performance for a given reference vector in the OVM region and the machine parameter. After that, a PWM technique is proposed, which substantially improves the high-frequency current ripple RMS compared to two existing OVM techniques for a feasible machine parameter.
Finally, simple carrier-comparison-based implementation methods of the proposed LMTs and OVM sequences will be discussed. The six-phase inverter is split into two three-phase inverters, and the proposed strategy implements the PWM sequences per three-phase inverter basis. In carrier-based implementations, the duty signal of the top switch of an inverter leg is compared with a triangular carrier. The bottom switch’s gating pulse complements the top switch’s pulse with a fixed dead time. The duty signal of the top switch of any leg has two components- a modulation signal and a common-mode signal. And two 180-degree phase-shifted carrier signals are required to implement the proposed sequences. The energy-transferring plane of ASPM is divided into twenty-four equivalent sectors; the carrier signals and the expressions of modulation and common-mode signals differ from one sector to another. Henceforth, a sector-independent algorithm is proposed in this thesis to derive these signals with a lower computational burden and smaller size of program memory.
The above theoretical analyses are validated through MATLAB Simulink simulation and experiments on a hardware prototype at a power level of 4 kW.

IISc EE Open Day 2024
2024-02-24 09:00 - 17:00 | IISc
Click here for IISc EE Open Day

EE Faculty Colloquium
2024-02-16 16:00 - 17:30
Title: Challenges & Opportunities in Dysarthric Speech ProcessingSpeaker: Dr. Prasanta Kumar Ghosh, Dept of Electrical Engineering, Indian Institute of ScienceVenue: MMCR, EETime: 4pm, Friday, 16 FebAbstract:Dysarthria is a speech condition caused by motor impairments. This talk will give an overview of Dysarthric Speech Processing (DSP) arising due to Amyotrophic Lateral Sclerosis (ALS) and Parkinson’s Disease (PD). It will present our latest research results and bring out the challenges and opportunities in DSP.Speaker’s Bio:Prasanta Kumar Ghosh received his Ph.D. in Electrical Engineering from University of Southern California (USC), Los Angeles, USA in 2011. Prior to that he obtained his M.Sc.(Engineering) in Electrical Communication Engineering from Indian Institute of Science (IISc), Bangalore and B.E.(ETCE) in Electronics from Jadavpur University, Kolkata in 2006 and 2003 respectively. He has been a Research Intern at Microsoft Research India, Bangalore in the area of audio-visual speaker verification from March to July in 2006. During 2011-2012 he was with IBM India Research Lab (IRL) as a researcher. Currently, he is an assistant professor in the department of Electrical Engineering (EE) at IISc. Before joining as assistant professor, he was a faculty fellow in the department of EE under the INSPIRE faculty fellowship program.Prasanta Kumar Ghosh was awarded the INSPIRE faculty fellowship from Department of Science and Technology (DST), Govt. of India in 2012. He was the winner of the first prize in Mr. BRV Varadhan Post-Graduate student paper contest in IEEE Bangalore chapter, in 2005. He received the best M.Sc. (Engg.) thesis award for the year 2006-07 in the Electrical Sciences division at IISc. He was awarded Center of Excellence in Teaching’s award for excellence in teaching in the category of EE for the year 2010-11 in USC. He has also received the best teaching assistantship (TA) awards for the years 2007-08 and 2008-09 and the honorable mention for the best paper award in the EE, USC. He was also awarded Ming Hsieh Institute (MHI) Ph.D. scholar for the year 2010-11 in EE, USC. His research interests include non-linear signal processing methods for speech and audio, speech production and its relation to speech perception, and automatic speech recognition inspired by the speech production and perception link.————–
