Search

Over the years, an increase in the traffic of electric and hybrid electric vehicles and vehicles with hydrogen cells is being observed, while at the same time, self-driving cars are appearing as a modern trend in transportation. As the years pass, their equipment will evolve. So, considering the progress in vehicle equipment over the years, additional technological innovations and applications should be proposed in the near future. Having that in mind, an analytical review of the progress of equipment in electromobility and autonomous driving is performed in this paper. The outcomes of this review comprise hints for additional complementary technological innovations, applications, and operating constraints along with proposals for materials, suggestions and tips for the future. The aforementioned hints and tips aim to help in securing proper operation of each vehicle part and charging equipment in the future, and make driving safer in the future. Finally, this review paper concludes with a discussion and bibliographic references. [ABSTRACT FROM AUTHOR]

The flour milling industry—a vital component of global food production—is undergoing a transformative phase driven by the integration of smart devices and advanced technologies. This transition promises improved efficiency, quality and sustainability in flour production. The accurate estimation of protein, moisture and ash content in wheat grains and flour is of paramount importance due to their direct impact on product quality and compliance with industry standards. This paper explores the application of Near-Infrared (NIR) spectroscopy as a non-destructive, efficient and cost-effective method for measuring the aforementioned essential parameters in wheat and flour by investigating the effectiveness of a low-cost handle NIR spectrometer. Furthermore, a novel approach using Fuzzy Cognitive Maps (FCMs) is proposed to estimate the protein, moisture and ash content in grain seeds and flour, marking the first known application of FCMs in this context. Our study includes an experimental setup that assesses different types of wheat seeds and flour samples and evaluates three NIR pre-processing techniques to enhance the parameter estimation accuracy. The results indicate that low-cost NIR equipment can contribute to the estimation of the studied parameters. [ABSTRACT FROM AUTHOR]

This paper presents a study on a sensorless decoupled P-Q control for a doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) with intelligent controllers via Matlab/Simulink. In the absence of mechanical sensors, an algorithm based on modified phase locked loop (MPLL) can estimate the rotor speed and position. An experimental validation of the proposed speed algorithm in steady state was conducted and is presented. In addition, this study focuses on the implementation of fuzzy logic controllers combined with the conventional PI (Proportional-Integral) for the adjustment of active power, reactive power, rotor speed and voltage in dc-link. The combination of fuzzy logic and PI concerns the use of the first as gain tuner of the second one, bearing in mind the significance and simultaneously the difficulty of gain finding. The simulation results of this study are presented to clarify the enhanced effectiveness of the combination of fuzzy logic with PI controllers. Finally, a comparative study between three control strategies, namely, case 1 – ‘with mechanical sensors and PI controllers’, case 2 – ‘sensorless with PI controllers’ and case 3 – ‘sensorless with fuzzy logic controllers’ was conducted and is also presented. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to review and summarize past work on how humidity, salinity, and water droplets affect offshore wind turbines electrical stator winding insulation. Partial discharges (PD) could be both the reason of the insulation's deterioration as well as the result of this deterioration and they are linked with the aging of the insulation system. The presence of humidity, salt, and water environment offshore can exasperate the occurrence of PD. The proliferation of wind turbines both onshore and offshore has resulted in a significant amount of research into their construction, operation, and maintenance. Offshore wind turbines have to operate in harsh environments such as marine environment that could affect even more of their lifetime. [ABSTRACT FROM AUTHOR]

In Power Systems, Synchronous Generators (SGs) are mostly used for generating electricity. Their insulation system, of which epoxy resin is a core component, plays a significant role in reliable operation. Epoxy resin has high mechanical strength, a characteristic that makes it a very good material for reliable SG insulation. Partial Discharges (PDs) are a constant threat to this insulation since they cause deterioration and consequential degradation of the aforementioned material. Therefore, it is very important to detect PDs, as they are both a symptom of insulation deterioration and a means to identify possible faults. Offline and Online PDs Tests are described, and a MATLAB/Simulink model, which simulates the capacitive model of PDs, is presented in this paper. Moreover, experiments are carried out in order to examine how the flashover voltage of epoxy resin samples is affected by different humidity levels. The main purpose of this manuscript is to investigate factors, such as the applied voltage, number, and volume of water droplets and water conductivity, which affect the condition of epoxy resin, and how these are related to PDs and flashover voltages, which may appear also in electrical machines' insulation. The aforementioned factors may affect the epoxy resin, resulting in an increase in PDs, which in turn increases the overall Electrical Rotating Machines (EMs) risk factor. [ABSTRACT FROM AUTHOR]

Abstract: This paper is a review of work performed on a subject that is relatively novel, that of wind generators in conjunction with power electronics arrangements. It is known that power electronics arrangements may give rise to unwanted spikes that may stress unnecessarily high the insulating systems of motors and generators. The influence of various waveforms of different rise times on the insulating system''s lifetime is investigated as well as the influence on the PD activity. The present paper offers also some proposals for future research. [Copyright &y& Elsevier]

State-of-the-art Predictive Maintenance (PM) of Electrical Machines (EMs) focuses on employing Artificial Intelligence (AI) methods with well-established measurement and processing techniques while exploring new combinations, to further establish itself a profitable venture in industry. The latest trend in industrial manufacturing and monitoring is the Digital Twin (DT) which is just now being defined and explored, showing promising results in facilitating the realization of the Industry 4.0 concept. While PM efforts closely resemble suggested DT methodologies and would greatly benefit from improved data handling and availability, a lack of combination regarding the two concepts is detected in literature. In addition, the next-generation-Digital-Twin (nexDT) definition is yet ambiguous. Existing DT reviews discuss broader definitions and include citations often irrelevant to PM. This work aims to redefine the nexDT concept by reviewing latest descriptions in broader literature while establishing a specialized denotation for EM manufacturing, PM, and control, encapsulating most of the relevant work in the process, and providing a new definition specifically catered to PM, serving as a foundation for future endeavors. A brief review of both DT research and PM state-of-the-art spanning the last five years is presented, followed by the conjunction of core concepts into a definitive description. Finally, surmised benefits and future work prospects are reported, especially focused on enabling PM state-of-the-art in AI techniques. [ABSTRACT FROM AUTHOR]

Summary: The expected significant growth in global electricity demand, followed by the adoption of green energy sources, led to the modernization of the energy distribution grids, such as the development of microgrids that can improve the reliability of the electric power system. Meanwhile, the increased integration of electric vehicles is expected to have a negative impact on power quality, normal operation, and investment costs of the microgrid. In this paper, a microgrid topology was studied for the islanded operation of a low‐voltage distribution network. The deployment of such energy management systems is essential to guarantee the safe and reliable operation of isolated microgrids. Hence, a decentralized energy management system, based on multi‐agent systems, was developed for the efficient charging of electric vehicles, by expanding a state‐of‐the‐art fuzzy logic controller‐based energy management strategy, in combination with a charging power controller, based on fuzzy cognitive maps. According to the authors' best knowledge, this is the first time that fuzzy cognitive maps theory is introduced in EVs' charging management problems. The performance of the proposed multi‐agent decentralized energy management system presented significant reduction in the investment costs of the microgrid, as compared with the use of a sole fuzzy logic controller‐based energy management strategy. The total cost of the microgrid for a 20‐year investment period is decreased by approximately 8.8%. Furthermore, the incorporation of the fuzzy cognitive maps‐based charging power controller leads to a significant amount of chargeable EVs. The mean chargeable EVs increased by 31%. Finally, the proposed energy management system reduces the peak load and load variances approximately 17% and 29%, respectively, without shifting and delaying the charging of the EVs. Hence, the proposed novel charging management system offers an intelligence approach for islanding distribution grids including the high penetration of electric vehicles by presenting operational and financial benefits. [ABSTRACT FROM AUTHOR]

Currently, environmental and climate change issues raise a lot of concerns related to conventional vehicles and renewable energy generation methods. Thus, more and more researchers around the world focus on the development and deployment of Renewable Energy Sources (RES). Additionally, due to the technological advancements in power electronics and electrical batteries, Electrical Vehicles (EVs) are becoming more and more popular. In addition, according to the Vehicle-to-Grid (V2G) operation, the EV batteries can provide electrical energy to the power grid. In this way, many ancillary services can be provided. A Direct Current (DC) nanogrid can be composed by combining the aforementioned technologies. Nanogrids present high efficiency and provide a simple interaction with renewable energy sources and energy storage devices. Firstly, the present study describes the design considerations of a DC nanogrid as well as the control strategies that have to be applied in order to make the V2G operation feasible. Furthermore, the provision of voltage regulation toward the power grid is investigated though the bidirectional transfer of active and reactive power between the DC nanogrid and the power grid. Afterwards, the voltage regulation techniques are applied in an Alternating Current (AC) radial distribution grid are investigated. The proposed system is simulated in Matlab/Simulink software and though the simulation scenarios the impact of the voltage regulation provided by the DC nanogrid is investigated. [ABSTRACT FROM AUTHOR]

The electric machines are the elements most used at an industry level, and they represent the major power consumption of the productive processes. Particularly speaking, among all electric machines, the motors and their drives play a key role since they literally allow the motion interchange in the industrial processes; it could be said that they are the medullar column for moving the rest of the mechanical parts. Hence, their proper operation must be guaranteed in order to raise, as much as possible, their efficiency, and, as consequence, bring out the economic benefits. This review presents a general overview of the reported works that address the efficiency topic in motors and drives and in the power quality of the electric grid. This study speaks about the relationship existing between the motors and drives that induces electric disturbances into the grid, affecting its power quality, and also how these power disturbances present in the electrical network adversely affect, in turn, the motors and drives. In addition, the reported techniques that tackle the detection, classification, and mitigations of power quality disturbances are discussed. Additionally, several works are reviewed in order to present the panorama that show the evolution and advances in the techniques and tendencies in both senses: motors and drives affecting the power source quality and the power quality disturbances affecting the efficiency of motors and drives. A discussion of trends in techniques and future work about power quality analysis from the motors and drives efficiency viewpoint is provided. Finally, some prompts are made about alternative methods that could help in overcome the gaps until now detected in the reported approaches referring to the detection, classification and mitigation of power disturbances with views toward the improvement of the efficiency of motors and drives. [ABSTRACT FROM AUTHOR]

Epoxy nanocomposites reinforced with glass fiber, have been prepared with various weight percentages (1, 3, and 5 wt.%) of MgO nanofillers to improve their electrical and thermal performance. An increase in MgO nanofiller content up to 3 wt.% tends to enhance surface discharge and corona inception voltages measured using fluorescence and UHF methods, under both AC and DC voltage profiles. Reduced initial surface potential along with increased decay rate is observed after inclusion of MgO nanoparticles. Before and after the polarity reversal phenomena, heterocharge formation is observed in the bulk of test specimens. In comparison with other test samples, the 3 wt.% sample had reflected lower electric field enhancement factor. After MgO filler was added to glass fiber reinforced polymer (GFRP) composites, the coefficient of thermal expansion (CTE) has reduced, with the 3 wt.% specimen having the lowest CTE value. TGA measurements revealed an improvement in thermal stability of the GFRP nanocomposites up on the inclusion of MgO nanofillers. Overall, the GFRP nanocomposite sample filled with 3 wt.% nano-MgO outperformed the other test samples in terms of electrical and thermal performance. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have become widespread during the last decade because of the distinct advantages they offer compared to the conventional ones. However, the increased penetration of EVs in the global transportation market has led increased electricity demands, which is expected to affect the operation of energy distribution systems. In the present paper, a demonstration about the effects of uncontrolled EVs charging in a case study low voltage (LV) network is demonstrated and a fuzzy energy management strategy for the coordination of EV charging in LV networks is presented, by including the distance of the EVs from the transformers in the fuzzy management systems for the first time. The Institute of Electrical and Electronics Engineers (IEEE) European Test Feeder is used as a case study low voltage distribution grid. In particular, the developed system configuration takes into consideration the architecture of the grid, the ampacities of the lines and the voltages at the system's buses. Moreover, electric vehicles are considered as agent-based models, which are characterized by the model of each EV, the state-of-charge of their batteries and the charging power. In particular, an investigation into the effects of uncontrolled charging is performed, in which two approaches are examined. The first approach investigates the maximum number of chargeable EVs in the case study network and how it is influenced by the grid's household loads. The second approach examines the number of network undervoltages and lines ampacity violations in a set of simulation scenarios. The results of the first approach show that the distance of the EVs from the networks substation affects the maximum number of chargeable EVs in a significant manner. Based on the observed results of the two approaches, a fuzzy management system is designed for the coordination of EV changing, which takes into account the distance from the EV charging points to the feeder substation, the state-of-charge of the EVs' batteries and the EVs' charging delay time. [ABSTRACT FROM AUTHOR]