Frequency Adaptive Parameter Estimation of Unbalanced and Distorted Power Grid

Grid synchronization plays an important role in the grid integration of renewable energy sources. To achieve grid synchronization, accurate information of the grid voltage signal parameters are needed. Motivated by this important practical application, this paper proposes a state observer-based approach for the parameter estimation of unbalanced three-phase grid voltage signal. The proposed technique can extract the frequency of the distorted grid voltage signal and is able to quantify the grid unbalances. First, a dynamical model of the grid voltage signal is developed considering the disturbances. In the model, frequency of the grid is considered as a constant and/or slowly-varying but unknown quantity. Based on the developed dynamical model, a state observer is proposed. Then using Lyapunov function-based approach, a frequency adaptation law is proposed. The chosen frequency adaptation law guarantees the global convergence of the estimation error dynamics and as a consequence, ensures the global asymptotic convergence of the estimated parameters in the fundamental frequency case. Gain tuning of the proposed state observer is very simple and can be done using Matlab commands. Some guidelines are also provided in this regard. Matlab/Simulink based numerical simulation results and dSPACE 1104 board-based experimental results are provided. Test results demonstrate the superiority and effectiveness of the proposed approach over another state-of-the art technique

An analysis of the thermal interaction between components in power converter applications

Accurately predicting the temperature of semiconductor devices is very important in the initial design of power electronics converter. RC thermal models derived from well-known methods have some ability to predict the temperature. However, the accuracy is boundary condition specific, hence, these methods cannot be used in the reliability analysis. To make the thermal model more accurate and robust the factors contributing to discrepancies need to be analyzed carefully. These are power-module-materials’ non-linear properties, thermal grease layer and the cooling system (i.e., liquid-cooled cold plate). In this work, estimation of accurate RC parameters from FEA thermal model is demonstrated in COMSOL. The electrical model having temperature dependent power loss model is coupled to refined thermal model and solved in a circuit simulator, PLECS. The proposed method is applied in two applications: assessing thermal interaction between IGBTs and anti-parallel diodes in a half-bridge power module, and assessing thermal interaction among the discrete switches in an interleaved bidirectional DC-DC converter. Results show that the impact of material non-linearity, thermal grease layer and cooling boundary conditions are significant for accurate prediction of IGBT and diode temperatures. The proposed model is consistent to FEA results and differs by 2-6.5% comparing to the experimental results

Coordinate Transformation-Free Observer-Based Adaptive Estimation of Distorted Single-Phase Grid Voltage Signal

© 2013 IEEE. This paper studies the phase and frequency estimation problem of single-phase grid voltage signal in the presence of DC offset and harmonics. For this purpose, a novel parameterized linear model of the grid voltage signal is considered where the unknown frequency of the grid is considered as the parameter. Based on the developed model, a linear observer (Luenberger type) is proposed. Then using Lyapunov stability theory, an estimator of the unknown grid frequency is developed. In order to deal with the grid harmonics, multiple parallel observers are then proposed. The proposed technique is inspired by other Luenberger observers already proposed in the literature. Those techniques use coordinate transformation that requires real-time matrix inverse calculation. The proposed technique avoids real-time matrix inversion by using a novel state-space model of the grid voltage signal. In comparison to similar other techniques available in the literature, no coordinate transformation is required. This significantly reduces the computational complexity w.r.t. similar other techniques. Comparative experimental results are provided with respect to two other recently proposed nonlinear techniques to show the dynamic performance improvement. Experimental results demonstrate the suitability of the proposed technique

Hand Sign to Bangla Speech: A Deep Learning in Vision based system for Recognizing Hand Sign Digits and Generating Bangla Speech

Recent advancements in the field of computer vision with the help of deep neural networks have led us to explore and develop many existing challenges that were once unattended due to the lack of necessary technologies. Hand Sign/Gesture Recognition is one of the significant areas where the deep neural network is making a substantial impact. In the last few years, a large number of researches has been conducted to recognize hand signs and hand gestures, which we aim to extend to our mother-tongue, Bangla (also known as Bengali). The primary goal of our work is to make an automated tool to aid the people who are unable to speak. We developed a system that automatically detects hand sign based digits and speaks out the result in Bangla language. According to the report of the World Health Organization (WHO), 15% of people in the world live with some kind of disabilities. Among them, individuals with communication impairment such as speech disabilities experience substantial barrier in social interaction. The proposed system can be invaluable to mitigate such a barrier. The core of the system is built with a deep learning model which is based on convolutional neural networks (CNN). The model classifies hand sign based digits with 92% accuracy over validation data which ensures it a highly trustworthy system. Upon classification of the digits, the resulting output is fed to the text to speech engine and the translator unit eventually which generates audio output in Bangla language. A web application to demonstrate our tool is available at http://bit.ly/signdigits2banglaspeech

A critical review on charging technologies of electric vehicles

The enormous number of automobiles across the world has caused a significant increase in emissions of greenhouse gases, which pose a grave and mounting threat to modern life by escalating global warming and polluting air quality. These adverse effects of climate change have motivated the automotive sector to reform and have pushed the drive towards the transformation to fully electric. Charging time has been identified as one of the key barriers in large-scale applications of Electric Vehicles (EVs). In addition, various challenges are associated with the formulation of a safe charging scheme, which is concerned with appropriate charging converter architecture, with the aim of ensuring a safe charging protocol within a range of 5–10 min. This paper provides a systematic review of thharging technologies and their impacts on battery systems, including charger converter design and associated limitations. Furthermore, the knowledge gap and research directions are provided with regard to the challenges associated with the charger converter architecture design at the systems level

A Numerical Thermal Analysis of a Battery Pack in an Electric Motorbike Application

Today, electric driven motorbikes (e-motorbikes) are facing multiple safety, functionality and operating challenges, particularly in hot climatic conditions. One of them is the increasing demand for efficient battery cooling to avoid the potential thermal stability concerns due to extreme temperatures and the conventional plastic enclosure of the battery pack. A reliable and efficient thermal design can be formulated by accommodating the battery within an appropriate battery housing supported by a cooling configuration. The proposed design includes a battery pack housing made of high conductive materials, such as copper (Cu) and aluminum (Al), with an adequate liquid cooling system. This study first proposes a potted cooling structure for the e-motorbike battery and numerical studies are carried out for a 72 V, 42 Ah battery pack for different ambient temperatures, casing materials, discharge rates, coolant types, and coolant temperatures. Results reveal that up to 53 °C is achievable with only the Cu battery housing material. Further temperature reduction is possible with the help of a liquid cooling system, and in this case, with the use of coolant temperature of 20◦ C, the battery temperature can be maintained within 28 °C. The analysis also suggests that the proposed cooling system can keep a safe battery temperature up to a 5C rate. The design was also validated for different accelerated driving scenarios. The proposed conceptual design could be exploited in future e-motorbike battery cooling for optimum thermal stability

Thermal analysis of Si-IGBT based power electronic modules in 50kW traction inverter application

Estimation of accurate IGBT junction temperature is crucial for reliability assessment. The well-known RC lumped approach can help predict junction temperature. However, this method suffers from inaccuracy while characterizing the thermal behaviour of several IGBT modules mounted to the liquid-cooled heatsink. Specifically, the thermal challenge originates from the thermal cross-coupling and module-to-module heat spreading and the converter cooling condition. This article demonstrates a methodology to study the impact of heat spreading, thermal interface material, and massive size liquid cold-plate on the overall thermal behaviour. A case study of 50 kW traction inverter is chosen to demonstrate the benefit of early assessment of electro-thermal simulation before making costly prototype design. Power loss is initially estimated using an analytical loss model and later the estimated power loss is used in FEA (Finite Element Analysis) thermal model. This paper also compares the performance of single-phase and two-phase liquid cooling and various thermal interface materials (TIM) to determine which type of cooling system and TIM is most suitable for real applications. Simulation results suggest that combination of two-phase liquid cooling and TIM can improve the thermal performance and reduce junction temperature by 4.5%, 4.2%, 4.6% for the traction power load 30 kW, 40 kW, and 50 kW, respectively. The proposed methodology can be used as useful reference guidance for thermal design and modelling of IGBT based power converter applications

Workplace Violence Among Health Care Professionals in Public and Private Health Facilities in Bangladesh

Objectives: The main objectives of this study were to examine the prevalence of workplace violence (WPV), its associated factors and explore the experiences of healthcare workers. Methods: A hospital-based cross-sectional study design used a nationally representative sample of 1,081 healthcare workers covering eight administrative divisions of Bangladesh. Logistic regression analysis was employed to estimate the adjusted effect of independent factors on WPV among healthcare workers. Results: Of the participants, 43% (468) experienced some form of WPV. Of those, 84% reported experiencing nonphysical violence, and 16% experienced physical violence in the past year. About 65% of victims claimed no action was taken to investigate the incident, and 44% reported no consequence for perpetrators. Four factors: being married (AOR = 1.63; CI: 1.12–2.39); public sector healthcare worker (AOR = 2.74; CI:1.99–3.76); working in an emergency department (AOR = 2.30; CI:1.03–5.12); and undertaking shift work (AOR = 1.52; CI: 1.10–2.11) were found to be significantly associated with WPV. One-third of the participants were worried about violence in their workplace. Conclusion: WPV is highly prevalent among healthcare workers in Bangladesh. Formal guidelines for reporting and managing WPV are urgently needed at the individual, hospital, and national levels

Novel micro-structured carbon-based adsorbents for notorious arsenic removal from wastewater

The contamination of groundwater by arsenic (As) in Bangladesh is the biggest impairing of a population, with a large number of peoples affected. Specifically, groundwater of Gangetic Delta is alarmingly contaminated with arsenic. Similar, perilous circumstances exist in many other countries and consequently, there is a dire need to develop cost-effective decentralized filtration unit utilizing low-cost adsorbents for eliminating arsenic from water. Morphological synthesis of carbon with unique spherical, nanorod, and massive nanostructures were achieved by solvothermal method. Owing to their intrinsic adsorption properties and different nanostructures, these nanostructures were employed as adsorption of arsenic in aqueous solution, with the purpose to better understanding the morphological effect in adsorption. It clearly demonstrated that carbon with nanorods morphology exhibited an excellent adsorption activity of arsenite (about 82%) at pH 3, remarkably superior to the two with solid sphere and massive microstructures, because of its larger specific surface area, enhanced acid strength and improved adsorption capacity. Furthermore, we discovered that iron hydroxide radicals and energy induced contact point formation in nanorods are the responsible for the high adsorption of As in aqueous solution. Thus, our work provides insides into the microstructure-dependent capability of different carbon for As adsorption applications