647 research outputs found

    Solar Thermal Collector Output Temperature Prediction by Hybrid Intelligent Model for Smartgrid and Smartbuildings Applications and Optimization

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    Currently, there is great interest in reducing the consumption of fossil fuels (and other non-renewable energy sources) in order to preserve the environment; smart buildings are commonly proposed for this purpose as they are capable of producing their own energy and using it optimally. However, at times, solar energy is not able to supply the energy demand fully; it is mandatory to know the quantity of energy needed to optimize the system. This research focuses on the prediction of output temperature from a solar thermal collector. The aim is to measure solar thermal energy and optimize the energy system of a house (or building). The dataset used in this research has been taken from a real installation in a bio-climate house located on the Sotavento Experimental Wind Farm, in north-west Spain. A hybrid intelligent model has been developed by combining clustering and regression methods such as neural networks, polynomial regression, and support vector machines. The main findings show that, by dividing the dataset into small clusters on the basis of similarity in behavior, it is possible to create more accurate models. Moreover, combining different regression methods for each cluster provides better results than when a global model of the whole dataset is used. In temperature prediction, mean absolute error was lower than 4 ∘ C.info:eu-repo/semantics/publishedVersio

    Analysis, Development And Design For Early Fault Detection And Fire Safety In Lithium-Ion Battery Technology

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    Energy storage technologies in its natural form play a key role in the electrical infrastructure, renewable and mobility industry. This form includes the material nomenclature for cell. technology, battery module design, Battery enclosure system design, control, and communication strategy, chemistry profile of various cell technologies, formation and formfactors of cell structure, electrical and mechanical properties of a lithium-ion cell, behavior of the cell under high voltage, low voltage, elevated temperature and lower temperature, multiple charging of a lithium-ion batteries. Energy storage industry is growing rapidly, and the industry is experiencing an unprecedented safety concern and issues in terms of fire and explosion at cell and system level. There has been. other research conducted with proposed theories and recommendations to resolve these issues. The failure modes for energy storage systems can be derived using different methodologies such as failure mode effects analysis (FMEA). Early detection mode and strategies in lithium-ion batteries to overcome the failure modes can be caused by endothermic reaction in the cell, further protection. devices, fire inhibition and ventilation. Endothermic safety involves modifications of materials in anode, cathode, and electrolyte. Chemical components added to the battery electrolyte improve the characteristics helping in the improvement of solid-electrolyte interphase and stability. Traditional energy storage system protection device fuse at the cell level, and contactors at the rack level and circuit breakers, current interrupt devices, and positive temperature coefficient devices at the system level. This research will employ classical experimental methods to explore, review and evaluate all the five main energy technologies and narrow down to electrochemical energy storage technologies. with the two main market ready lithium-ion battery technology (LiFePO4/ G and NMC/G) technology cells and why are they valuable in the energy storage and E-mobility space. Also, will focus on the electrical, mechanical design, testing of the battery module into a rack system, advancements in battery chemistries, relevant modes, mechanisms of potential failures, and early detection strategies to overcome these failures. Finally, how the problems of fires, safety concerns and difficulty in transporting already fully assembled energy storage systems can be resolved and be demystified in lithium-ion technology. Keywords Control strategy, Energy storage system, electrolyte, failure mode, early detection, Lithium-Ion cell technology, Battey system

    Battery Management System in Electric Vehicles

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    Here this document provides the data about the batteries of electric vehicles. It consists of numerous data about various energy storage methods in EVs and how it is different from energy storage of IC-engine vehicles. How electric vehicles will take over ICEngine vehicles due to advancement in battery technology and the shrink in its prices. Various types of batteries are listed in the document with their specifications. Possible future battery technology which will have more or same energy density than current gasoline fuels and also with the significant reduction in battery weights; which will make EVs cheaper than current condition. Some examples are listed showing current battery capacities of various EVs models. Some battery parameters are shown in the document with introduction to BMS (Battery Management System). Then a brief introduction about the charging of these EV batteries and its types displaying variations in charging time in different types of EVs according to their charger type and manufacturers. How DC charging is more time saving method than AC and how smart charging will help to grid in case of peak or grid failure conditions

    Energies and Its Worldwide Research

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    Energy efficiency and management is certainly one of the key drivers of human progress. Thus, the trends in the energy research are a topic of interest for the scientific community. The aim of this study is to highlight global research trends in this field through the analysis of a scientific journal indexed exclusively in the energy and fuels category. For this purpose, a journal has been selected that is in the center of the category considering its impact factor, which is only indexed in this category and of open access, Energies of the publisher MDPI. Therefore, a bibliometric analysis of all the contents of the journal between 2008 and 2020, 13,740 documents published, has been carried out. Analyzing the articles that are linked to each other by their citations, 14 clusters or research topics have been detected: smart grids; climate change–electric energy community; energy storage; bioenergy sources; prediction algorithms applied to power; optimization of the grid link for renewable energy; wind power; sustainability of power systems; hydrocarbon improvements; conversion of thermal/electrical energy; electric motor advancements; marine renewable energy; hydropower and energy storage; and preventive techniques in power transformers. The main keywords found were electric vehicle, renewable energy, microgrid, smart grid, and energy efficiency. In short, energy research remains necessary to meet the future challenge of sustainable energy with high efficiency and the exploration of new renewable resources, all for increasingly sustainable cities

    A smart high-voltage cell detecting and equalizing circuit for LiFePO4 batteries in electric vehicles

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    A battery management system (BMS) plays an important role in electric vehicles (EVs) in order to achieve a reasonable-lasting lifetime. An equalizing method is essential in order to obtain the best performance. A monitoring system is required to check if any cell voltage is high or low. In this paper, an equalizing and monitoring system for an ultra-light electric vehicle is proposed. The monitoring system detects if one cell is fully charged or all cells are fully charged and the equalizing system tops each cell at the desired voltage. To solve this issue, a light-emitting diode (LED) band gap is used as a voltage reference to inform the user if any cell is at its high voltage. A smart monitoring displays on the liquid crystal display (LCD), if one cell is high or all cells are high. This detection also provides a signal to the microcontroller to turn on/off the charger if all cells are high. Also, a Bluetooth module was designed to command the microcontroller the charger to turn on/off via voice/text message by using a smartphone. Additionally, a new smart monitoring system based on the Bluetooth model (HC05) and mobile app has been made in order to monitor individual cell voltage. A major feature of the system is to draw a very-low current, so that the system does not contribute significantly to the self-discharge of the battery and the circuit does not need sophisticated control. Manufacturers of large electric vehicles may have more intelligent systems that may require a permanent connection to the grid and allow high standby losses, where more state of charge (SOC) may be lost per day. The paper is rather focused on reducing the standby losses, and to activate the equalizer only when charging and/or driving. The experimental results are performed in order to verify the feasibility of the proposed circuit

    New Perspectives on Electric Vehicles

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    Modern transportation systems have adverse effects on the climate, emitting greenhouse gases and polluting the air. As such, new modes of non-polluting transportation, including electric vehicles and plug-in hybrids, are a major focus of current research and development. This book explores the future of transportation. It is divided into four sections: “Electric Vehicles Infrastructures,” “Architectures of the Electric Vehicles,” “Technologies of the Electric Vehicles,” and “Propulsion Systems.” The chapter authors share their research experience regarding the main barriers in electric vehicle implementation, their thoughts on electric vehicle modelling and control, and network communication challenges

    Data Science-Based Full-Lifespan Management of Lithium-Ion Battery

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    This open access book comprehensively consolidates studies in the rapidly emerging field of battery management. The primary focus is to overview the new and emerging data science technologies for full-lifespan management of Li-ion batteries, which are categorized into three groups, namely (i) battery manufacturing management, (ii) battery operation management, and (iii) battery reutilization management. The key challenges, future trends as well as promising data-science technologies to further improve this research field are discussed. As battery full-lifespan (manufacturing, operation, and reutilization) management is a hot research topic in both energy and AI fields and none specific book has focused on systematically describing this particular from a data science perspective before, this book can attract the attention of academics, scientists, engineers, and practitioners. It is useful as a reference book for students and graduates working in related fields. Specifically, the audience could not only get the basics of battery manufacturing, operation, and reutilization but also the information of related data-science technologies. The step-by-step guidance, comprehensive introduction, and case studies to the topic make it accessible to audiences of different levels, from graduates to experienced engineers
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