This paper presents an allocation planning approach to optimally allocate DSTATCOM to improve the operational performance of microgrids (MGs) with plug-in electric vehicle charging stations (PEVCSs). A two-stage optimisation problem is formulated for this. The first stage is used to minimise the total cost of MG to optimally design MG and the second stage is used to optimally allocate PEVCSs and DSTATCOM in MGs by minimising the operational performance index, which is a weighted sum of energy loss and voltage deviation indices. Differential evolution (DE) and particle swarm optimisation (PSO) algorithms are used to solve the MG design optimisation problem. An exhaustive search-based approach is also employed to show the impact of the placement of a PEVCS in sub-optimal locations (one at a time) of MGs on the operational parameters of MGs. A case study is also conducted with multiple placements of PEVCSs in MGs. The proposed approaches are validated on 33-bus, 69-bus and 52-bus Indian practical distribution networks. The results show that the placement of PEVCS in remote locations greatly deteriorates the operational parameters of MGs. With the optimal allocation of DSTATCOM, a significant reduction in the operational performance index of MGs with PEVCSs is observed.

This paper presents an AC-DC converter system tailored for grid-to-vehicle (G2V) applications, aimed at facilitating efficient power flow while achieving a Unity power factor (UPF). The system employs a rectifier for AC-DC conversion, which effectively steps up a 230V AC input to a 380V DC output. This DC output can be further regulated using a buck converter to meet specific load requirements. A Proportional-Integral (PI) controller is implemented to oversee the voltage and current regulation, thereby minimizing harmonic distortion and enhancing the overall power factor. By actively managing the input voltage and current, the controller ensures that the system operates within desired parameters, thus optimizing power quality. Comprehensive simulation results validate the system's performance, demonstrating its capability to maintain a UPF in G2V mode. The findings indicate significant reductions in total harmonic distortion (THD), reinforcing the system's effectiveness in managing power quality. This AC-DC converter design not only enhances the efficiency of power flow in electric vehicle charging systems but also contributes to the stability of the grid by minimizing reactive power and harmonics. Overall, this work represents a significant advancement in converter technology for sustainable transportation and energy management.

The research presents a novel Bidirectional Switched Capacitor DC-DC (BSCD) Converter and demonstrates its application in integrating a battery with an electric vehicle's (EV) traction motor. During discharging, the motor is powered by the battery through the converter, and during charging, the traction motor functions as a generator, returning the recovered energy to the battery via the converter. The recommended converter employs a two-duty cycle operation to enhance voltage gain while minimizing circuit components. It utilizes a switched capacitor (SC) cell, enhancing the voltage transfer ratio by operating capacitors CS1 and CS2 in parallel or series. The work includes analysis of the converter's steady state, mathematical approach, state-space modelling, stability, and efficiency. The proposed converter achieves an efficiency of 90.66 % in charging mode and 96.6 % in discharging mode, with a Gain Margin of 54.4 dB and Phase Margin of 8.09°, indicating stability. Comparative evaluations with existing BDCs are also provided. The implementation of a closed-loop simulation using MATLAB/Simulink and dSpace software validates the performance of the suggested converter-based drive. Furthermore, an experimental investigation of a 200 W, 30 V/430 V configuration confirms the converter's practical viability.

Sensorless control of Brushless DC (BLDC) motors is a cost-effective and reliable alternative to traditional Hall sensor-based methods, eliminating the need for additional hardware while enhancing system robustness. This study integrates a proportional-integral (PI) controller with a robust closed-loop sensorless speed control strategy for a BLDC motor. Back-EMF Zero-Crossing Detection (ZCD). By introducing a 30° phase delay for exact commutation and collecting rotor position information from the back-EMF of the unexcited phase, the suggested method eliminates the need for position sensors. By dynamically modifying the PulseWidthModulation (PWM) duty cycle of the VoltageSource Inverter (VSI) based on real-time speed error, an API controller is built to control motor speed. MATLAB/Simulink is used to model and simulate the system, which consists of a BLDC motor, VSI, DClink capacitor, and AC rectifier. Real-time implementation using dSPACE further validates the suggested control strategy by demonstrating stable speed control, fast dynamic response, and decreased steady-state error. The sensorless control method provides a cost-effective, efficient, and reliable solution, making it highly suitable for industrial automation, electric vehicles, and renewable energy applications.

This study examines the integration of permanent magnet synchronous motors (PMSM) with renewable energy sources, focusing on solar photovoltaic (SPV) arrays to improve efficiency and sustainability in electric vehicle (EV) applications. PMSM, renowned for its high efficiency, silent operation, and precise control, is managed using a proportional-integral (PI) controller to handle variable load conditions, including fluctuations in torque and current. By fine-tuning the PI controller's gains, the desired motor speed is achieved efficiently. A DC-DC Buck-Boost converter serves as an intermediary power conditioning unit, optimizing energy extraction from the SPV array and enhancing system efficiency. This setup ensures that PMSM meets the power and operational demands of EVs. Additionally, a voltage source inverter (VSI) facilitates electronic commutation of the PMSM, providing accurate control using fundamental frequency pulses. The system is modelled and simulated in MATLAB/Simulink, demonstrating its reliability under diverse load conditions. The findings underscore the potential of this approach in promoting renewable energy integration in EVs, paving the way for cleaner and more sustainable transportation solutions.

The rapid rise in electric vehicle (EV) adoption highlights the critical need for a reliable charging infrastructure to ensure the stability of power distribution networks. This research introduces a fuzzy inference system (FIS) designed to forecast daily EV loads essential for developing microgrids to meet the increasing demand for EVs. The present work considers four factors for FIS designing: travel distance, parking duration, battery state of charge (SoC), and expected arrival times at charging stations. By developing fuzzy logic rules for these variables, a probabilistic charging is generated, improving both the precision and adaptability of load forecasts. This study also explores the impact of future EV adoption on microgrid load demand, analyzing adoption rates of 53%, 68%, and 84%, providing crucial insights for planning microgrids. The discrepancy between estimated and actual EV loads is found to be 0.078, demonstrating a reduction in prediction error. This effectively mitigates uncertainties related to EV user behavior and supports the design of resilient and flexible microgrid systems.

Due to environmental concerns, renewable energy has gained significant popularity over the past two decades. Integrating distributed generation and renewable energy sources, particularly through microgrids in power distribution systems, has become feasible. Additionally, there has been a notable increase in the adoption of electric vehicles (EVs) driven by environmental initiatives and their advantages over internal combustion engines. As a result, the planning and operation of microgrids in distribution systems have become more complex. To address these complexities, computational evolutionary algorithms have emerged as effective solutions. The Differential Evolution (DE) algorithm stands out for its speed and user-friendly simplicity The proposed study uses the Fuzzy Adaptive Differential Evolution (FADE) analysis for microgrid planning integrated with EV charging infrastructure, using the IEEE 33-bus system. The FADE algorithm combines the power of fuzzy logic and adaptive strategies within the DE framework to tackle the planning and optimization challenges of microgrids integrated with Electric Vehicle Charging Stations (EVCS) The findings provide valuable insights into the effectiveness of the FADE algorithm in addressing the challenges associated with the planning and operation of microgrids with EVCS in modern power systems.

Accurate wind power forecasting is essential for the effective integration of wind energy into power grids. Yet, the inherent variability of wind and the intricate interplay of meteorological factors make prediction a challenging task. This study introduces a novel short-term wind power forecasting method, improving the traditional convolutional neural network and long short-term memory (CNN-LSTM) model through two significant innovations. First, we introduce a parallel convolutional architecture that employs both 1dimensional (1D) and 2-dimensional (2D) convolutions to simultaneously capture temporal patterns and inter-variable relationships in wind power data. This structure, inspired by Explainable-CNNs, enables more comprehensive feature extraction. Second, we integrate an attention mechanism that dynamically weights the importance of different input features and time steps, improving both forecast accuracy and model interpretability. The proposed model is evaluated using data from two wind farms in Croatia, comparing its performance against benchmark models including standard CNN-LSTM, LSTM, and gated recurrent unit (GRU) networks. Results demonstrate that our enhanced CNN-LSTM model achieves superior forecasting accuracy, with improvements in Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 15% and 12% respectively, compared to the best-performing benchmark. Furthermore, the attention mechanism provides valuable insights into the relative importance of different features over time, offering a new level of interpretability in wind power forecasting models. This work contributes to the advancement of accurate and explainable wind power prediction, supporting more efficient renewable energy integration and grid management.

This paper presents a bidirectional AC-DC converter system designed for seamless power exchange between electric vehicles (EVs) and the utility grid. The proposed converter facilitates the conversion of 230 V, 50 Hz AC input to 380 V DC during grid-to-vehicle operation, allowing for efficient battery charging through a bidirectional DC-DC converter. Conversely, during vehicle-to-grid operation, it converts the 380 V DC input from the DC-DC converter to 230 V, 50 Hz AC output for grid supply. The system employs PI controllers to ensure precise voltage and current regulation, ensuring stable and efficient operation during grid interaction. Simulation results demonstrate the system’s effectiveness in managing power conversion for both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) applications.

This work presents an optimization approach for optimal operation of a grid connected microgrid (MG) considering EV charging station, renewable-based generators, DSTATCOM, load shifting, and both active and reactive power loads. DSTATCOM is used to supply the reactive power loads locally instead of purchasing it from the grid. Load shifting strategy is used to reduce dependency on the grid during high electricity pricing hours. The minimization of total annual operating cost of MG is considered as the objective function which includes cost of buying/selling active power from/to the grid, costs related to PV, wind power generator, and DSTATCOM, cost of reactive power purchase from the grid, and operating cost of EV charging station. EV charging station load profile is generated using fuzzy-based approach considering number ofEVs, SOC levels of EVs, and arrival time of EV s to the charging station. The proposed optimization problem is solved using CPLEX solver of GAMS. The simulation results show that the uses of load shifting and DSTACOM facilities significantly reduce the total annual operating cost of MG.

In electric vehicles (EVs), the type of electric motor and converter technology have a significant impact on regulating the operational characteristics of the vehicle. Therefore, in this work, the modified bi-directional KY converter (BKYC) is proposed for EV applications. The main contributions of the proposed converter are high step-up/step-down conversion gain, bi-directional power flow, simplified control structure, continuous current, common ground, low volume, and high efficiency. An inductor on either side of the converter ensures continuous current flow and passive components are arranged to operate in series to offer high step-up/step-down conversion. The charging and discharging operations, steady-state analysis, and design process of the proposed converter are discussed in detail and compared with similar bi-directional converter topologies. Further, the efficiency analysis of the proposed converter is presented and found that the efficacy of 95.51 % in charging operation and 96.52 % in discharging operation of operation. The simulations are carried out using MATLAB/Simulink environment. Further, a prototype of a modified bi-directional KY converter is implemented with a TMS320F28335 processor and validated with theoretical and simulation counterparts.

Bi-directional DC-DC converters (BDC) are required for power flow regulation between storage devices and DC buses in renewable energy based distributed generation systems. The fundamental requirements of the BDC are simple structure, reduced switching components, a wide range of voltage gain, low voltage stress, high efficiency, and reduced size. There are different BDC topologies for various applications based on their requirements in the literature. Various BDC are categorized according to their impedance networks. Isolated BDC converters are large due to high-frequency transformers and hence used for static energy storage applications whereas non-isolated BDC is lightweight and suitable for dynamic applications like electric vehicles. This paper reviews types of non-isolated BDC topologies. The performance of five non-isolated BDC converters under steady state condition is evaluated by using theoretical analysis. On this basis, suitability of BDC for different applications is discussed. Further advantages and limitations of converters are discussed by using comparative analysis. The optimization of BDC for distributed generation systems from the perspectives of wide voltage gain, low electromagnetic interference, low cost with higher efficiency is identified. Theoretical analysis of the converters is validated by simulating 200W converters in MATLAB Simulink.

High efficiency, high voltage transfer ratio (VTR), and low input ripple current is required in any bidirectional DC-DC converter (BDC) that plays a major role in interfacing batteries in applications like dc microgrids and electric vehicles (EVs). For meeting these requirements, a switched capacitor-based BDC is proposed to interface the battery with a propulsion system via DC Link. It has a simple circuit with only a set of switching operations, High VTR, and lesser ripple current on the low voltage (LV) side are advantages of the proposed High Gain Switched-Capacitor Bi-directional DC-DC Converter (SC-BDC) making it appropriate for use in EVs. The steady-state analysis, design consideration of passive components, loss and efficiency analysis are presented. Finally, the proposed High Gain SC-BDC is compared with few of the existing BDC in the literature. The feasibility of the converter was demonstrated by simulating a 200 W converter and validating results produced in a MATLAB environment.

Energy storage systems with a high voltage transfer ratio (VTR) play an important role in integrating modern electric power systems with large-scale renewable energy integration. This article suggests a modified Switched Capacitor non-isolated Bidirectional DC–DC Converter (SCBDC) topology to achieve a high VTR. The presented converter has a simple circuit, simple control, a switched capacitor structure that increases the voltage-gain range, and low-voltage stress on switches, making it suitable for renewable and hybrid energy source electric vehicle applications. Continuous conduction mode is used for the operation principles, steady-state analysis, and extraction of voltage and current equations. Simulation results for the proposed converter were obtained in a MATLAB environment, demonstrating the converter's feasibility.

The increasing focus on environmental sustainability has led to a significant rise in the use of renewable energy within distributed generation systems. Microgrids play a crucial role in facilitating the integration of renewable energy into distribution networks, making effective strategic planning essential for achieving the best financial and environmental results. Advanced software tools for microgrid planning and design, such as HOMER, are vital in this context. HOMER stands out for its ability to incorporate contemporary factors such as demand-side management, generator reliability, and Electric Vehicle Charging Fleets (EVCF). The proposed work investigates the planning process for a campus microgrid that includes EVCF, exploring various renewable energy configurations and tariff options. It offers a thorough assessment of different planning scenarios, emphasizing both the potential benefits and challenges associated with incorporating EVCF into university microgrids. The analysis determined that the optimal sizes for the microgrid components could yield annual energy charge savings of $12,027, annual utility bill savings of $281,905, and a payback period of 5.2 years.

This paper proposes BKY converter, which is made to run in continuous conduction mode during both the charging and discharging cycles for low power EV applications. An analysis is conducted on the converter's dynamic behavior, and an approach to control is put forth to manage the power transfer between the traction system and battery in an electric vehicle. The suggested converter is designed using an extracted small-signal model. A significant ripple in the detected current causes switching instability in the current-mode control approaches at low duty ratios. A computation delay occurs when the controller is implemented in the microcontroller. The control algorithm's design takes this into account. A theoretical framework for current and voltage loop gain transfer functions are created using the realistic parameters of a BKY converter. Further, dynamic performance under load variations is explained and validated by simulations.

Over the past 20 years, the popularity of renewable energy has sharply increased due to environmental concerns. Integrating Distributed Generation (DG) and renewable energy sources, particularly through microgrids, into power distribution systems has become increasingly feasible. Simultaneously, there has been a notable surge in the adoption of electric vehicles (EVs), driven by environmental initiatives and their advantages over internal combustion engines. Consequently, the planning and management of microgrids within distribution networks have grown increasingly complex. To tackle these complexities, computational evolutionary algorithms have emerged as effective solutions. Among these algorithms, the Differential Evolution (DE) algorithm stands out for its speed and user-friendly simplicity. The proposed work analyzes Hybrid Differential Evolution (HDE) integrated with EV charging infrastructure for microgrid planning. The HDE algorithm combines the power of fuzzy logic and adaptive strategies within the DE framework to address the planning and optimization challenges of microgrids integrated with Electric Vehicle Charging Stations (EVCS). The paper gives insights into the effectiveness of the HDE algorithm in addressing the challenges related to the planning and operation of microgrids with EV charging stations in modern power systems. Furthermore, the optimization results are compared with those achieved using the DE algorithm.

Lithium ion batteries are a promising energy source for electric vehicles due to their high specific energy and power output. Overall system reliability and stability can be improved by effectively planning battery replacement intervals and monitoring their condition. To guarantee the battery system operates safely, steadily, and effectively, it is necessary to accurately assess the state of health (SOH) of the lithium-ion battery. Capacity might be used to anticipate it directly. To improve the accuracy of the SOH estimate, hyperparameter-optimized Gaussian process regression (GPR) is used. Gaussian process models have the advantage of being flexible, stochastic, nonparametric models with uncertainty forecasts, and may have variance around the mean forecast to account for the associated uncertainties in evaluation and forecasting. The lithium-ion battery data set made available by NASA is examined in this article. The outcomes demonstrate its efficacy and demonstrate that the algorithm may be successfully used for battery monitoring and prognostics. Additionally, the prediction for battery health has been improved through the comparison of predictions with various quantities of training data.

A compact Inertial Electrostatic Confinement (IEC) system is designed and fabricated for D-D fusion neutron generation. The IEC system consists of two concentric spherical grids connected to high voltage power supply inside a vacuum chamber filled with deuterium gas. The diameter of inner grid cathode is 40 mm and the diameter of outer grid anode is 120 mm. These grids are placed inside a SS304L cylindrical vacuum chamber of 300 mm diameter and 450 mm length. The IEC system has been operated at 24 kV in deuterium gas medium at 0.01–0.02 mbar, and the neutron yield of ~ 105n/s is measured with neutron monitor. The temperature inside the IEC system is also measured using Fiber Bragg Grating (FBG) during D-D gas discharges. Degradation in vacuum inside the chamber causes the instability in deuterium plasma which reduces the neutron yield and increases the cathode temperature.

An experimental investigation of surface flashover characteristics of PMMA and POM is studied in compressed nitrogen gas environment with nitrogen as the background gas. The operating pressure range is from 1kg/cm 2 to 4kg/cm 2 . It is observed that the breakdown voltage of PMMA is higher than POM owing to a higher permittivity mismatch between POM- nitrogen interface as compared to the PMMA- nitrogen interface. The reduction in spacer efficiency with pressure for PMMA is 11% as compared to POM which shows a higher reduction of 18%. This paper further emphasizes on the role of energy level and density of charge carrier trapping centers for a reduced breakdown voltage in POM as compared to PMMA.

Perspex (polymethyl methacrylate (PMMA)) and delrin (polyoxymethylene (POM)) are subjected to high voltages and then the surface potential decay is measured using an electrostatic voltmeter. The surface trapping parameters ofPMMAare calculated using isothermal current theory and a plot between trap density and energy level is obtained. It is observed that the maximum electron and the hole traps in the surface layer of PMMA are ∼1.5 × 1017 eV-1m3 and 0.8 × 1017 eV-1m3, respectively, and the energy level of its electron and hole traps are in the range of 0.60-0.90 eV and 0.78-0.9 eV, respectively. The introduction of roughness onPOMsurface leads to an increase in the energy level from 0.55-0.87 eV to 0.55-0.89 eV. It is also observed that there is an increase, both in peak surface potential and time to decay inPMMAas compared to POM. This holds true for positive as well as negative dc voltages and is caused by the charge retentivity in the material resulting from the length of the polymeric chain.

The presence of spacer in a spark-gap system leads to a reduction in breakdown voltage. This paper studies the effect of spacer surface profile and surface protrusions on the breakdown voltage in compressed gases. Different spacer profiles comprising of conical angled insulators, bush-bar insulators, and double ended frustum insulators are used to study the effect of spacer profile on spacer efficiency under nanosecond pulsed voltage using particle-in-cell simulation. The effect of protrusions on the surface of the insulators is modeled to study the effect of teeth height on spacer efficiency. An increase in spacer efficiency from 86% in case of cylindrical spacer to 97% with negative angled and bush bar spacer is observed for a 20-mm spacer length placed between the spark gap electrodes with nitrogen as background gas.

A comparative computational analysis of electrical breakdown is done by introducing imperfection or void in a dielectric inside a high-voltage cavity design with nitrogen as the background gas. The simulations have been carried out using 3D particle-in-cell tools. The partial discharge (PD) causes electric field strength variations along the dielectric and ionization of the gas inside the void that lead to breakdown of the gas and plasma formation with varied particle (ions and electrons) momenta within the dielectric. The PD effects in the dielectric rupture condition with an irregular void and fissure are compared with a smaller void enclosed by the dielectric. The charged particle dynamics in dielectric and its effect on the streamer present in the outside cavity are observed.

This paper reports the design methodology and implementation experiments for a solid-state-based triggering arrangement for the MARX generator of the KALI-30GW (1 MV, 30 kA, 80 ns) pulsed power system. The 15-stage bipolar MARX generator of the KALI-30GW system is triggered using a trigatron-type spark gap. An insulated-gate bipolar-transistor (IGBT)-based trigger supply is used to trigger the first spark gap, and the next two spark gaps are triggered by using internally-generated trigger pulses. Optically-isolated arrangements are provided for a human interface. The entire assembly was tested with a dummy copper sulphate load, and an excellent triggering range of 7–12 kV was achieved. The circuit diagram, analysis and experimental results of the triggering arrangement are presented in the paper.

The surface flashover behavior in ambient air and nitrogen are studied at a pressure of 1 kg/cm2 using optical emission spectroscopy. A high dc voltage is applied to Rogowski profile electrodes with polyoxymethylene as the insulator between the electrodes. Three different conditions of needle protrusion along the surface of polyoxymethylene are used to study the variation in spectral characteristics due to particle contamination. When the insulator is placed between the spark gap electrodes, the OES spectra are dominated by the Hα line in air and nitrogen medium. It was found that the intensity of N+2 (B-X) emission is less in air surrounding the insulator medium. The plasma temperature during bulk breakdown in air is 0.433 eV, which increases to 0.434 eV with the pressurized nitrogen, which further increases in the presence of insulator to 0.441 eV and 0.44 eV in nitrogen and air, respectively. The electron density is obtained from the N emission line at 746.8 nm and the estimated peak value is 2.85 × 1012 cm-3 in the presence of insulator. The plasma temperature decreases with increase in distance of particle contamination from cathode. The increase in electron density in air, as compared to nitrogen implies more material desorption in air which is also supported by the comparisons of Hα lines.

Relativistic electron beam generation studies have been carried out in LIA-400 system through explosive electron emission for various cathode materials. This paper presents the emission properties of different cathode materials at peak diode voltages varying from 10 to 220 kV and at peak current levels from 0.5 to 2.2 kA in a single pulse duration of 160-180 ns. The cathode materials used are graphite, stainless steel, and red polymer velvet. The perveance data calculated from experimental waveforms are compared with 1-D Child Langmuir formula to obtain the cathode plasma expansion velocity for various cathode materials. Various diode parameters are subject to shot to shot variation analysis. Velvet cathode proves to be the best electron emitter because of its lower plasma expansion velocity and least shot to shot variability.

This paper elaborates the effect of unmatched stored energy in high-voltage high-energy pulsed power systems. High-voltage insulation failure of KALI system is analyzed thoroughly for its occurrence. According to the simulations and analysis energy mismatch of MARX generator and Blumlein transmission line is found to be the most significant cause for high-voltage failure of the system. MARX generator and Blumlein of KALI are redesigned to attain better energy balance at same voltage level. Observations, simulation and analytical results are illustrated in the following sections.

The design, development and commissioning of 1 MV pulsed electron accelerator producing Flash X-Rays is described in this paper. This pulsed power system is based on bipolar MARX generator and Blumlein followed by Explosive electron emission diode assembly. The peak pulsed power is ∼ 30 GW. The electron energies in the range of 400 keV to 1030 keV are produced and delivered to experimental load of Industrial diode. Electrons are emitted from a stainless steel ring at ground potential by explosive field emission and bombard the anode tungsten pin for flash X-rays generation. The relativistic electron beam has been simulated within the diode chamber and pattern shows the beam propagation. Imaging plates are used to characterize the source size and optimization has been reported. © 2014 IOP Publishing Ltd and Sissa Medialab srl.

This paper deals with the discharge along the surface of angled insulators in compressed gases using 3D finite difference particle-in-cell simulation. The simulation is carried in pure nitrogen at atmospheric pressure. The spacer angle 'θ' is measured between the inclined surface and line vertical to the electrode. The angle is positive when narrow end is connected to the anode and negative when the narrow end is connected to the cathode. The positive spacer angle shows a reduced discharge voltage for a 20mm gap length as compared to the negative spacer angle. © 2013 IEEE.

This paper presents PIC simulations of spark gap discharge, filled with Argon gas at atmospheric pressure. The rogowsky profile electrodes having an inter-electrode gap distance of 20mm were used in this study. The model is based on explosive electron emission from cathode, secondary emission and neutral Argon gas ionization. The phase space profiles, current density, ionization, temperature are presented. Results show that some simulations are in good agreement with existing experimental data. The simulation data of argon discharge was also compared with our previous work of nitrogen gas discharge. The difference between the two gases for using them as a dielectric medium in spark gaps is presented. © 2013 IEEE.

This paper presents the design and development of a compact Marx generator based on pulse forming network (PFN) along with a peaking capacitor rated at 300 kV and 64 J. Proposed scheme consists of identical PFNs connected across the charging and grounding resistors according to the Marx generator scheme. Modular construction of the Marx generator is useful in altering the stage capacitance to obtain varying pulse rise time and wave shapes at the output. A peaking capacitor connected at the output of the Marx generator significantly improves the rise time from 25 to 5 ns suitable for driving an antenna load. The effect of peaking capacitor on the intensity of far-field radiation is simulated using finite integration technique for a distance of 15, 20, 30, 40, and 50 m and the results are presented and discussed. © 2013 IEEE.

This paper presents the theoretical analysis of the variations in the drift velocity and ionization coefficient of electrons in the presence of an insulator in gases at high pressure. The model is developed taking into consideration the variation of parameters like drift velocity, ionization coefficient, transit time of travel of electron and streamer length in the presence of insulator which are responsible for flashover of insulator in gases at a reduced voltage unlike the plain gas gap conditions. Some of the parameters calculated theoretically are found to be in close agreement with the existing experimental data. © 2013 IEEE.

A new computational model to understand the mechanism of discharges along the gas/solid interface at high voltage and high pressure is made based on the models of explosive electron emission, secondary emission, and neutral gas ionization by using finite-difference time domain-based particle-in-cell code. The charge particle movement at different durations is obtained at a pressure of 1 atmosphere. The profiles of phase space, the net charge density along the gap, and the effect of the dielectric on the characteristics of the gas discharge are presented. The ionization coefficient (α) and drift velocity (ve) calculated from simulation data closely match with the existing experimental results. © 1973-2012 IEEE.

A numerical model employing FDTD based particle-in-cell code (PIC) is used to study the discharge mechanism across a gas/solid interface. The simulation is carried out with and without an insulator in the anode cathode gap at a pressure of 1atmosphere and a ramp voltage with a rise time of 5ns and pulse duration of 50ns is used as the input pulse. The profiles of electron densities, avalanche growth, phase profile of electrons, and the gap voltage are calculated with and without an insulator to study the mechanism of discharge in presence of an insulator. Spacer efficiency of 81%is obtained which closely agrees with the existing experimental data.

This paper proposes a method of minimization of torque ripple of brushless dc (BLDC) motors, with un-ideal back EMF under MATLAB 7.1/Simulink environment. An idealized BLDC motor has trapezoidal back EMF waveform. However, for practical reasons like non-uniformity of magnetic material and design trade-off it is hard to produce desired trapezoidal wave shape. Therefore torque ripple appears in conventional control. In this paper, the duty cycle of the pulses is calculated in the torque controller in both normal conduction period and commutation period and in combination with a given commutation sequence fed to the inverter gates so as to minimize ripple. Moreover, the influence of finite dc supply voltage is considered in commutation period. Simulation results show that compared with conventional control, this method results in apparent reduction of torque ripple. © 2009 IEEE.