Hybridization of energy storage units is a topic of interest in the nowadays context of transition towards more sustainable ways of energy production and consumption. Extensive research continues to be devoted to this topic, whereas various technical solutions have already been successfully implemented for a plethora of applications. This paper aims in a first step at overviewing the necessity of storage units in an increasingly renewable-based, decentralized energy production, then at explaining the role of hybridization of different storage technologies for more versatility and flexibility in what is generally known as a smart grid context. Then, the focus is on how to make the different energy storage sources to optimally and robustly cooperate towards a common goal. It is about obtaining a “fusion” of different heterogeneous sources. The answer to this problem obviously requires advanced control approaches being employed. An overview of most effective and widely used control strategies is envisaged – accompanied by some illustrative application results – out of which robust control techniques are given a special attention. This paper ends by attempting a look towards the future, namely by identifying some open questions and research directions worthy to further investigate.
To make possible powering all appliances installed into a camper van room, an efficient power supply system must be designed. It should be able to collect energy from either the power grid or the solar panel system or other renewable energy, when the camper is parked into a camping spot. The energy is also needed when the camper is stopped into the wild. Moreover, the battery can be charged from the car alternator, while the camper van is moving from one place to another. This paper aims to provide necessary information about constructing a charging system for the battery which powers the electronics into the camper van room, focusing on comparing different approaches. It is demonstrated that using only three solar panels with a cumulative power of 250Wh, enough energy for powering all appliances of high necessity for a camper van is obtained.
Increasing energy demand requires the application of smart Direct current [DC] grids. To empower the creation of these DC systems the need of a smart converter is required. This paper proposes a smart and configurable educational code using a half-bridge topology as a converter. The Universal One Leg and Universal Four Leg are used as the configurable hardware, the universal code will be implemented on an Arduino Internet of Things [IoT] and can be configurable Over-The-Air [OTA]. This combination of flexible hardware and software allows bidirectional energy flow to control and manage appliances. In code, a selection of the functionality can be made. Such as basic buck or boost mode to have a stable voltage or current flowing through the converter. But also smarter functions such as Battery Management Systems [BMS] and Maximum Power Point Trackers [MPPT] systems can be selected. The converter can behave as such a converter and adding more of these converters in a system parts a system response can be measured. All data through this converter will be collected on the server side and can be analyzed through a simple dashboard. Main goal for this converter is to use it as a way to implement a DC micro-grid, although it can also be used to teach students about micro-grids in practical lessons. This document will discuss the architecture and functionality of the code and show results measured in a lab environment.
In this paper the results of research in optimizing a waveguide antenna, by applying optimization techniques based on genetic algorithms, are presented. The optimization process consists in identifying the radiating elements that have to be eliminated from a fully populated configuration (elements that cancel receive the excitation value equal to 0, and those that remain active receive the excitation value equal to 1).
Low Noise Block (LNB) circuits are an essential component of satellite receiving systems in televisions. LNB converts high-frequency satellite signals into a lower frequency range for transmission to the receiver. Also, LNB ensures low-noise signal reception, enables polarization control, supports multiple frequency bands, and amplifies signals. The LNB power circuits provide power to the LNB. Voltage-controlled boost converters are commonly used in these circuits; the current limiting feature used in these circuits can be insufficient to handle sudden current spikes, leading to feedback from end users. They are not immune to short circuits because of installation problems with satellite cables, which are a common failure mode that potentially damages the LNB power or other components in the television, resulting in a loss of satellite signal. Hence, leading to a poor user experience and harming the manufacturer’s reputation. Replacing a damaged LNB power circuit is also difficult b ecause i t i s o ften i ntegrated i nto t he T V’s d esign and is not easily replaceable. To mitigate this problem, a parallel resonant converter approach is introduced that limits the output current up to a pre-defined l evel b y f requency c ontrol, which provides an alternative to voltage-controlled boost converters. Parallel resonant converter circuits operate as current sources so maximum current cannot exceed this defined operation frequency point under any circumstances. In this study, the mathematical equations of the proposed circuit were obtained, and then the operating conditions were determined. The operation frequency ranges were interpreted graphically using Matlab, and the parallel resonant converter design was evaluated using simulation model by using MATLAB’s Simulink Toolbox. These results show that the parallel resonant converter approach maintaining a stable current and reducing the risk of short circuit damage. The proposed design is expected to reduce repair costs due to LNB power circuits for TV manufacturers.
The reduction of electricity consumption in the field of lighting requires the use of lamps with LED technology in order to replace incandescent bulbs and neon tubes. Their power sources, which contain controlled semiconductor elements, allow precise adjustment of the light intensity, which enables the integration of these systems in areas related to the comfort parameters of a living space. On the other hand, the switching of the semiconductor elements included in such systems called dimmers produces a change in the waveform of the voltage applied to the lamps, by introducing unwanted frequency harmonics, which can disturb other electrical or electronic elements placed nearby.This paper aims to compare the harmonics produced by 2 commercial dimmer systems, based on TRIAC-type elements, with those produced by a dimmer made in the laboratory, based on IGBT-type elements. The analysis was performed via a digital oscilloscope starting from the waveform of the electric current and using Fast Fourier Transformation. The experimental results allow a comparative analysis in tabular form and also the calculation of total harmonic distortion parameter in each case.
This paper explores alterations in the thermal behavior of rewound induction motors with the aim of achieving functional characteristics different from those initially established during the design process. Through the utilization of Motor-CAD software, the distribution of temperatures within the induction motor structure is analyzed. It is revealed that when rewinding is performed to attain alternative functional characteristics while maintaining the required magnetic field strength, induction motor forces, and current density, the resulting thermal regime differs significantly from the reference version. This divergence can profoundly impact the motor’s operational lifespan.
The aim of the work is to make an evaluation of two versions of Particle Swarm Optimization (PSO), in the framework of signal analysis and model parameters estimations. The versions of PSO are with constraint coefficients and inertia (PSO-COIN) and the version based on quantum models (QPSO). Both versions are members of the evolutionary computation domain and have bioinspired roots. Two case studies are considered. The first case study is represented by two test functions, chosen from a benchmark suite used for the evaluation of the optimization algorithms. The second case is the parameter estimation problem, in the context of the signal analysis framework, and under various signal-to-noise ratios to study the effects on the converge rates of the estimation processes. The computer-based experiments show comparable performances for PSO algorithms, for short time simulation, e.g., 100 iterations. After that, the version of PSO-COIN gives better results.
This paper introduces V-CNN, a versatile structure inspired from previously introduced light models such as NL-CNN. What makes the V-CNN structure efficient is the process of optimizing its hyper-parameters. Consequently, several aspects in proper design for building of efficient (validation accuracy near state of the art while keeping the complexity of the structure) V-CNN structures, are considered and detailed in this paper. While V-CNN includes as particular cases several previously defined models such as NL-CNN and XNL-CNN, it can be better tailored for efficient deployment given a specific dataset. A V-CNN model with 1.5 million parameters obtained 91.55% validation accuracy on CIFAR-10 dataset, surpassing the previous result of 90.60% using the NL-CNN. The V-CNN model offers the following advantages: i) using optimization hints described herein it allows maximal efficiency (good accuracy at low complexity) for a wide variety of datasets; ii) has a low number of layer primitives, thus making easier their specific design for deployment on various TinyML or EdgeAI platforms, including FPGAS.
A significant role in electronics and not only is represented by the vibration’s variable. The paper aims to present an electronic solution for measuring and recording vibrations on a Secure Digital (SD) card. The data collected on the SD card can be used to analyze the condition of the vehicle engine by performing a vibration analysis. The hardware solution is based on an ESP8266 microcontroller, an accelerometer sensor, display and SD memory card. With the proper software the hardware can be turned into an Internet of Things (IoT) solution for future research. This paper covers the implemented hardware solution, real time data reading and processing, data storing using an SD memory card and testing on different car engines. After testing, differences were observed in the vibrations generated by an engine operating in normal parameters compared to a used engine or one with technical problems. Based on vibration analysis a preventive maintenance program can be made for different engines and not only.
This paper presents an assay of the dynamic state of charge characteristics of a Li-ion battery. It is proposed an approach of forecasting battery’s state of charge that can be used by battery management system to predict the remained quantity of charge within the battery at a certain time, based on real time data acquisition and using a simplified electrical circuit model that simulates, with small errors, the battery signal, with experimentally validation of the results.
This paper gives an overview of the journey from 5G towards 6G evolution. The 5G has been built across three main application verticals as defined by ITU, namely: Enhanced Mobile Broadband, Massive Machine Type Communications and Ultra-reliable Low Latency Communications (URRLC). To support these verticals, 5G has defined the following enablers: Massive MIMO, cloudification of network infrastructure, network automation, network slicing and edge cloud computing. It is expected that 5G will provide flexibility in terms of openness, mobility, programmability and agility and robustness in a standardized manner. The journey towards 6G will describe the limitations of 5G technologies and outlines the technology enablers for 6G. These enablers include smooth integration and interworking of Non-Terrestrial Networking technologies (NTN), use of Reconfigurable Intelligent Surfaces (RIS) and use of AI to orchestrate network and cloud resources. Additionally, the paper will give an overview of 6G research initiatives at both regional and international level.
In recent years, the integration of advanced technologies in industrial control processes has gained significant attention, particularly in the domain of wastewater systems. One emerging technology with promising potential is Distributed Ledger Technology (DLT), which offers secure and transparent data management through blockchain-based solutions. This paper presents an in-depth analysis of the performance impact that arises when incorporating DLT-based sensor authentication in industrial control processes of wastewater systems. The study aims to evaluate the benefits and challenges associated with this integration, providing insights into the effectiveness and efficiency of DLT-based sensor authentication in ensuring data integrity and enhancing the overall control process performance.
Diabetic Retinopathy (DR) is a condition caused by diabetes that affects the blood vessels in the retina. Detecting the disease early and providing appropriate treatment are crucial in slowing its progression. Therefore, there is great potential in utilizing Machine Learning (ML) to improve the identification and monitoring of DR development in patients. Our study aims to explore the performance of six ML algorithms, namely Random Forest (RF), Adaptive Boosting (AB), K-Nearest Neighbor (K-NN), Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), and Quadratic Discriminant Analysis (QDA), in two binary classifications involving three classes: non-diabetic retinopathy (NoDR), moderate retinopathy (MR), and severe retinopathy (SV). These ML algorithms were applied to ten features extracted using local binary patterns (LBP). The first classification task involved distinguishing between NoDR and MR, while the second task involved differentiating between NoDR and SV. The RF technique achieved the highest classification accuracy, with 0.912 for the first task and 0.94 for the second task.
In wireless communications the diversity techniques are used with success to mitigate de perturbations from the transmitted channel. These interferences can be generated by different sources and can be noises or multipath fading effect. The noise can be Gaussian or impulsive with various mathematical models. The impulsive noise degrades sever the signal quality, affecting groups of successive bits in data streaming. Using interleaver this effect can be decreased by rearrange the bit sequence before encoding. In this paper an Alamouti code with interleaver system is proposed to mitigate the impulsive noise with SαS distribution. Alamouti code is a spatial diversity technique, and it has good performances on Additive White Gaussian Noise channel. Data are transmitted on multiple antennas at the emitter and at the receiver. We considered 2x2 system with Binary-Phase-Shift-Keying modulation, Rayleigh fading and two types of interleavers: random and Takeshita-Costello. Both has smaller error rate, but the best is the last one. The results are presented for both cases: impulsive and gaussian noise. The model of impulsive noise is described and analyzed for different values of its parameters. This electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet. *CRITICAL: Do Not Use Symbols, Special Characters, Footnotes, or Math in Paper Title or Abstract. (Abstract)
The increasing complexity of today’s electronic systems requires efficient information exchange between their components. This is often achieved using shared memory locations, which in SoC devices, microcontrollers and other hardware components are called registers. This paper demonstrates how software mechanisms called semaphores can efficiently accomplish this information exchange. Long distance communication between electronic systems is also addressed, and a complex solution for transferring information over the Internet using state-of-the-art technologies is presented. In addition, since many critical applications require real-time functionality, this study explains both theoretically and practically the advantages of using a real-time operating system. For a better understanding of the concepts presented, the information in the article is validated by creating from scratch a physical device having a pet feeder functionality, designing its circuitry, software architecture and physical structure.
Maritime domain agencies play a critical role in generating situational awareness to detect maritime anomalies and prevent illegal fishing, illegal migration, or even hostile naval activities. Traditionally, these tasks rely especially on human cognitive load, but the use of Artificial Intelligence (AI) can potentially enhance these processes. This paper proposes and analyses several AI-based approaches for vessel type classification based on their trajectory analysis. These approaches draw inspiration from various handwriting signature verification techniques such as deep learning, K-nearest neighbours, support vector machines and convolutional neural networks. Thus, different models were trained using AIS processed data collected from the Black Sea region (Romanian Exclusive Economic Zone). The goal was to obtain a model that classifies non-cooperative vessels when detected only by radar sensors. The trained models aim to identify situations such as illegal fishing, search and rescue operations, or law enforcement activities where vessels may have turned off their AIS transponders. These approaches could have significant implications for enhancing maritime surveillance, particularly in situations where conventional methods are ineffective. Overall, this paper represents a promising step towards improving the safety and security of oceans through advanced vessel type classification techniques.
Building-integrated/applied photovoltaic (PV) systems have been widespread recently in terms of electrical energy generation in buildings. These systems are applications with much lower power than land type large-scale systems, addressing the area/building where they are installed rather than centralized production. In this framework, maximum power point (MPP) tracking (MPPT) approaches at module level and sub-module level, balcony railing, Carport or solar tile etc. will be investigated in terms of building integrated PV systems (BIPV). Solar panels act as a building material, insulation material and energy generator in BIPV applications. In building-applied (BAPV) examples, the solar panel is mounted on the building. However, there is no difference between BIPV and BAPV in terms of electrical model. A unique method will be developed for MPPT at module level and sub-module level for such applications. Depending on the power processing strategy in the optimizer power stage, amplifier, synchronous reducer or bidirectional differential power processing topologies will be examined and the most suitable power converter for the module and sub-module level will be determined. Technically, comparisons of the performances of MPPT strategies were made in the MATLAB/Simulink program at the central, module level or sub-module level, and it was shown that the power that can be obtained from the PV module or sub-module increases with the MPPT at the module and sub-module level.
Given the massive movement towards hybrid power sources and electrification in the marine industry, power conversion systems are increasingly needed to support the flexibility and efficiency required by shipboard electrical grid. Electromagnetic compatibility has been considered as a matter of concern for special ships and for navy designs. The increase in the volume of power electronics systems relative to the installed power onboard the ship brings EMC compliance as a key factor for the good operation of the electrical installation. This paper addresses some EMC aspects that need to be considered in the design and installation of electrical systems incorporating power electronics equipment. Examples are used to highlight some of the solutions for limiting the electromagnetic interference that may occur during the operation of this equipment.
In this paper, electromagnetic transient processes in a three-phase cage induction motor due to sudden disconnection and subsequent fast reconnection of its electric power supply are analyzed using linear complex differential equations of the representative-space-phasor electromagnetic model of the motor. With this in view, it is assumed that the disconnection of the motor from the electric power supply (before its reconnection to the same power supply by rapid automatic reclosing) has a duration of just a few cyclic time-periods of the three-phase time-harmonic supply voltage system, so that, the motor speed remains unchanged over this very short duration. The electromagnetic transient analysis is corroborated by meaningful case-study numerical results.
