SJEE

Lossless Direct Path Reinforced Bidirectional DC-DC Converter for On-Board Charger in Electric Vehicle

2024-11-30T00:17:29+00:00

A DC-DC converter plays a vital role in the On-Board Charger for Electric Vehicles (EVs). Also, having the capability for bidirectional power flow for a DC-DC converter is essential for EVs to transfer power from Vehicle-to-Grid (V2G) and Vehicle-to-Vehicle (V2V). In this context, this paper proposes a bidirectional DC-DC converter for the On-Board Charger for Electric Vehicles (EVs). The proposed DC-DC converter has two paths: a lossy partial path through two bridges, a high-frequency transformer, and a lossless direct path directly connecting the source to the output. A 7.8 kW DC-DC converter is developed in MATLAB/Simulink. The performance of the converter is analysed for various operating scenarios. Further, a scaled-down hardware prototype of the proposed converter with a power rating of 600 W has been developed. The dSPACE controller is used to control the power flows. The prototype is tested under various operating conditions. The experimental and simulation results show that the power flow through the direct path is around 58 % and through the partial path around 42 %. Due to this, the overall converter efficiency of 97.8% during charging and 95.6 % during discharging cycles has been achieved. Also, as only 42 % of power flows through the partial path, all the components' ratings and sizes are significantly reduced. Also, the distinguishing feature is its bidirectional power flow capability, making the EV capable of V2V and V2G power transfer. Hence, the proposed DCDC converter is an efficient and compact solution for an On-Board Charger for EVs.

An Intelligent Protection Scheme based on Support Vector Machine for Fault Detection in Microgrid Using Transient Signals in Protection Scheme

2024-11-30T00:17:30+00:00

Fault detection in the microgrid is a crucial task due to the diversified fault conditions, and it must be rapidly identified to reduce any serious hindrance to the system. The fault current behaviour due to change in fault resistance of the touching point can damage the switches of integrated converters. In addition to the above, sporadic conditions can also affect the profile of voltage and current, in the system. Traditional protection schemes need modification to prevent relay maloperation of the microgrid. This paper presents a protection scheme based on support vector machines to detect faults under such tedious conditions. In this protection scheme, acquired samples of voltage and current from selected bus have been used and processed through the data processing tool discrete wavelet transform. The protection scheme is operating in two dissimilar operating modes, where initially mode was identified then fault detection/classification was done. Section identification task was performed to identify faulty sections under varying operating scenarios. The uncertain conditions of the renewable sources can affect the performance of the system, therefore some random cases have been considered to validate the protection scheme.

Calculator of Some Special Mathematical Functions

2024-11-30T00:17:30+00:00

This paper presents the implementation of a calculator of certain special mathematical functions in the form of an efficient web application with a simple and intuitive GUI (graphical user interface). This application aims to enable accurate numerical approximations of the most frequently used special mathematical functions in engineering and science, eliminating the need to acquire additional notational knowledge or programming language syntax experience. The investigation can be divided into three larger units. The initial section offers brief overview of the special mathematical functions of which numerical approximations are implemented in the subject application. For the time being, this application provides approximations for the following special mathematical functions: Bessel functions of the first kind, gamma and beta functions, and some orthogonal polynomials – Legendre, Laguerre, Hermite (physicist’s and probabilist’s) polynomials, Chebyshev polynomials of the first and the second kind, as well as Jacobi polynomials. The middle section presents a description of the computer implementation – an overview of the used technology and implemented algorithms, while the final section includes a discussion of the solution, as well as a comparison with existing software that provides the same features as the subject application.

Experimental Study of the Shadow Effect on a Monocrystalline Silicon Photovoltaic Module

2024-11-30T00:17:31+00:00

The ultimate component of photovoltaic energy conversion into electrical power is the solar cell. The best efficiency of this conversion is obtained for a group of few cells in parallel or in series, forming what is called “a solar module”. This grouping requires special precautions in order to avoid panel degradation, occurring when the amount of incident radiation received by a photovoltaic module is not the same (Shading Effect). This results in a dispersion of cell parameters, some cells become resistive and heat up (hot spots), thus producing significant power dissipation and reducing the characteristics of the PV module. In order to preserve the solar panel and lessen the shadow affect, bypass diodes are utilized. In the present research, a Matlab/Simscape model is used to plot I-V and P-V panel characteristics, under different numbers of shaded cells, with and without bypass diodes to illustrate the effects of partial, total and random shading on the PV module performance. Furthermore, our aim is to show how adding bypass diodes changes the performance of a partially shaded solar system. Experimental tests were carried out within the Frères Mentouri Constantine 1 University of Constantine / Electrical Engineering Laboratory (LEC) in order to study the effects of total, partial and non-uniform shading of mono crystalline silicon photovoltaic module (80W) with 36 cells connected in series (every 18 cells in the panel have one bypass diode). The obtained experimental data indicate that the PV module power decreases up to almost 50% in case of full shading, and up to 30% in case of application of partial shading.

Enhancing Heart Disease Prediction Accuracy by Comparing Classification Models Employing Varied Feature Selection Techniques

2024-11-30T00:17:32+00:00

ML (Machine Learning) is frequently used in health systems to alert physicians in real time. This helps to take preventive measures, such as predicting a future heart attack. This study presents ML combined with various forms of feature selection to identify heart disease. It includes the analysis of different algorithms such as Decision Tree, Logistic Regression, Support Vector Machine, Random Forest and hybrid models. This results in SVM and RM performing better after applying feature selection for individual ML models. Meanwhile, hybrid cases provide good results if the ensemble is done using a Voting Classifier. Our approach in this paper is based on our study of existing literature and methodologies. We can conclude that, for the used dataset, the Voting Classifier appears to be the most accurate and precise model out of all individual and hybrid classifiers that use feature selection techniques.

The Effect of Structural Changes on the Functional Properties of Fe65.5Cr4Mo4Ga4P12C5B5.5 Bulk Metallic Glass

2024-12-05T14:00:21+00:00

The ferromagnetic Fe_65.5Cr₄Mo₄Ga₄P₁₂C₅B_5.5 bulk metallic glass rods of 1.8 mm diameter were prepared prepared by the copper-mold casting technique. As-quenched and successive furnace annealed samples were examined by thermal analysis (DTA), X-ray diffraction (XRD), thermomagnetic, coercivity, and hardness measurements. The wide supercooled liquid region : The ferromagnetic Fe65.5Cr4Mo4Ga4P12C5B5.5 bulk metallic glass rods of 1.8 mm diameter were prepared prepared by the copper-mold casting technique. As-quenched and successive furnace annealed samples were examined by thermal analysis (DTA), X-ray diffraction (XRD), thermomagnetic, coercivity, and hardness measurements. The wide supercooled liquid region DTx of 57 K and reduced glass transition temperature T_rg of 0.57 indicate enhanced glass forming ability and high thermal stability against crystallization. After the third annealing at 673 K the most intensive stress relief is followed by an increase in the magnetic permeability of 23%, an increase in the Curie temperature (to 558 K), and an improvement in coercivity of about 40%. Coercivity abruptly increases after thermal treatment at 773 K, indicating the presence of crystalline inclusions that hinder stress relief. The XRD pattern of the rod annealed at 873 К shows several intermetallic compounds formed by crystallizing the amorphous phase, such as B₄₈B₂C₂, and iron-based compounds Fe₂Мо₄C and Fe₃B. The rods were explored for the increase in hardness which evolved due to stress relief and after transformation from the amorphous into crystalline phase.

A Novel Super Frame Flexible Macroblock Ordering Scheme for H.265 Video Transmission with Unequal Error Protection

2024-11-30T00:22:55+00:00

One of the most popular video coding standards in use today is High Efficiency Video Coding (HEVC), also known as H.265. In this paper, a novel Flexible Macroblock Ordering (FMO) scheme known as Super frame FMO (SFMO) is proposed for HEVC video compression. The SFMO scheme is combined with a concealment aware Unequal Error Protection (UEP) scheme using RS codes and interleaved to improve the performance of the RS decoder. Moreover, Multiple Description Coding (MDC) is used to further improve its performance. The simulation results have shown that the proposed system surpassed an Equal Error Protection (EEP) scheme by an average gain of 3.02 dB in the range of 0.1 <= Packet Loss Rate <= 0.5 with FLI (Frame Level Interleaving)- SFMO. Additionally, the FLI- SFMO scheme outperformed Explicit ChessboardWipe (ECW) FMO by an average gain of 1.48 dB.

Salt and Pepper Denoising Filters for Digital Images: A Technical Review

2024-12-01T15:27:28+00:00

Noise in images refers to random variations in pixel intensities that alter the original pixel intensities of the image. Among the various noises present in the image, salt and pepper noise corrupts images due to a defect in the device’s hardware or the camera’s faulty sensor. This leads to misinterpretation of pixels and deterioration of image quality during visualization of natural images and diagnosis of medical images. Up until now, researchers have presented several cutting-edge filters to overcome and lessen the impact of this noise. This article presents a comprehensive investigation into three different domains of impulse denoising of digital images. These domains are based on the spatial domain, the fuzzy logic domain, and the deep learning-based category. In this study, many techniques of image denoising were categorized and analyzed, along with their respective motivations, principles of execution, and comparative analysis. We carefully explain and implement a few significant approaches, considered stateof-the-art in each subject, in MATLAB. When doing simulations, the filters are analyzed and quantitatively evaluated using three metrics that are frequently utilized. These parameters are the peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM). Finally, we provide a comparison of each study category to enhance our comprehension of each domain. We conclude by outlining the challenges each domain poses and providing a detailed explanation of the rationale for future research.