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This study of patent applications and scientific publications related to batteries is unique as it includes the volume of as well as qualitative indicators for both types of publications. Using carefully elaborated strategies to identify publications relating to batteries, this study provides data to discuss the critical balance to strike between investments in research and the more innovation-related aspects. The results show that China's dominance in publication volumes increases and that research with Chinese involvement is highly cited, whereas patent applications are slightly less valued than the world average. Quality-related indicators for Canada and the United States are very high for both scientific publications and patent applications. National differences in the proportions of patent applications and scientific publications are large, with Japan at one end with three patent applications per scientific paper and Canada at the other with almost seven scientific papers per patent application. On an actor level, data for Sweden indicate how the automotive industry started to file many patent applications in the decade starting in 2010. Finally, it is noted that this new approach to study a technological field appears promising as it gives new perspectives of relevance for policy actors and others. [ABSTRACT FROM AUTHOR]

This study of patent applications and scientific publications related to batteries is unique as it includes the volume of as well as qualitative indicators for both types of publications. Using carefully elaborated strategies to identify publications relating to batteries, this study provides data to discuss the critical balance to strike between investments in research and the more innovation-related aspects. The results show that China’s dominance in publication volumes increases and that research with Chinese involvement is highly cited, whereas patent applications are slightly less valued than the world average. Quality-related indicators for Canada and the United States are very high for both scientific publications and patent applications. National differences in the proportions of patent applications and scientific publications are large, with Japan at one end with three patent applications per scientific paper and Canada at the other with almost seven scientific papers per patent application. On an actor level, data for Sweden indicate how the automotive industry started to file many patent applications in the decade starting in 2010. Finally, it is noted that this new approach to study a technological field appears promising as it gives new perspectives of relevance for policy actors and others.

The present paper uses scientometric indicators to examine the Li-ion battery research in India as reflected through Web of Science Core Collection (WoS) data of 32 years (1989-2020). India produced 2864 publications during the period but the publication activity increased manifold during the last decade. The output was scattered among 1346 institutions. However, 28 institutions produced 1% or more of the total output. One third (34.5%) of the output emerged out of international collaboration. About 71.5% of the output were in journals with impact factor >=2. The paper also identifies the aspects/direction of research through keyword analysis besides identifying preferred journals and prolific authors. [ABSTRACT FROM AUTHOR]

Recycling lithium-ion batteries (LIBs) have become increasingly important in response to expanding electromobility. This paper is focused on evaluating the environmental impacts (EIs) of recycling pre-treatment of three types of LIBs with black mass as its product. A detailed gate-to-gate Life Cycle Assessment study was conducted to obtain EIs of the recycling process. The benefits of LIBs recycling pre-treatment and significant recovery of secondary aluminum for compared battery types are highlighted in the analysis. This paper points out that the varying chemistry of the compared LIBs does not affect the resulting EIs of the recycling pre-treatment procedures. [ABSTRACT FROM AUTHOR]

With the accelerated construction of 5G and IoT, more and more 5G base stations are erected. However, with the increase of 5G base stations, the power management of 5G base stations becomes progressively a bottleneck. In this paper, we solve the problem of 5G base station power management by designing a 5G base station lithium battery cloud monitoring system. In this paper, first, the lithium battery acquisition hardware is designed. Second, a new communication protocol is established based on Modbus. Third, the windows desktop upper computer software and the cloud-based monitoring system are designed. Finally, this paper designs the improved ResLSTM algorithm which is fused with ResNet algorithm based on Stacked LSTM. The algorithm designed in this paper is tested in comparison with SVM and LSTM. The performance of the algorithm designed in this paper is better than SVM and LSTM. Furthermore, the communication test, as well as the training and testing of the ResLSTM algorithm are outstanding. The 5G base station lithium-ion battery cloud monitoring system designed in this paper can meet the requirements. It has great significance for engineering promotion. More importantly, the ResLSTM algorithm designed in this paper can better guide the method of lithium-ion battery SOC estimation. [ABSTRACT FROM AUTHOR]

The production and consumption of non-renewable energy resources have disrupted the environment's biodiversity cycle. Global climate change, including worldwide warming, has made human life both now and in the future. The construction industry in the world has a significant share in the demand for energy consumption in these challenges. Therefore, the primary purpose of this paper is to implement standards to save and prevent energy loss to control and limit the demand for energy requested from the power network. Constructing a building with self-sufficient energy production that meets its energy needs by producing clean energy becomes more important. It also sells the excess energy to the grid, known as zero energy buildings. In the present paper, the issue is a constrained optimization problem that aims to minimize the total annual cost, including the initial investment cost for PV and batteries and their maintenance costs, as well as the cost of network exchanges. Among the limitations, the proposed model can mention the restrictions governing the battery, such as the limitations of the battery state of charge (SoC). The problem under optimization is a mixed integers nonlinear programming (MINLP) that will be solved by a particle swarm optimization (PSO) algorithm considering the total cost minimization. [ABSTRACT FROM AUTHOR]

Introduction. Solar photovoltaic (PV) has recently become very important especially in electrical power applications for countries with high luminosity because it is an effectively unlimited available energy resource. Depending on solar radiation and temperature, the PV generator has a non-linear characteristic with a maximum power point (MPP). The novelty is the efficiency improvement of a PV energy module, it is necessary to track the MPP of the PV array regardless of temperature or irradiation circumstances. Purpose. This paper presents the modeling and the digitally simulation under MATLAB/Simulink of a Fuzzy Logic Controller based on Voltage Perturbation Algorithm (FLC-VPA) applied to PV battery charging system, which consists of PV module, DC-DC boost converter, MPP tracking (MPPT) unit and battery storage. Methods. The DSP1104 is then used to experimentally implement this MPPT algorithm for real-time driving. The obtained results show the high precision of the proposed FLC-VPA MPPT around the optimal point compared to the conventional VPA under stable and changing meteorological conditions. Practical value. The experimental results approve the effectiveness and validity of the proposed total control system in the PV system. References 30, tables 3, figures 17. [ABSTRACT FROM AUTHOR]

Demand flexibility plays a crucial role in mitigating the intermittency of renewable power sources. This paper focuses on an active distribution grid that incorporates flexible heat and electric demands, specifically heat pumps (HPs) and electric vehicles (EVs). Additionally, it addresses photovoltaic (PV) power generation facilities and electrical batteries to enhance demand flexibility. To exploit demand flexibility from both heat and electric demand, along with the integration of PVs and batteries, Control and Communication Mechanisms (CCMs) are formulated. These CCMs integrate demand flexibility into the distribution grids to obtain economic benefits for private households and, at the same time, facilitate voltage control. Concerning EVs, the paper discusses voltage-based droop control, scheduled charging, priority charging, and up-/down-power regulation to optimize the charging and discharging operations. For heat demands, the on-off operation of the HPs integrated with phase change material (PCM) storage is optimized to unlock heat-to-power flexibility. The HP controllers aim to ensure as much self-consumption as possible and provide voltage support for the distribution grid while ensuring the thermal comfort of residents. Finally, the developed CCMs are implemented on a small and representative community of an active distribution grid with eight houses using Power Factory software and DIgSILENT simulation language (DSL). This scalable size of the active distribution network facilitates the careful study of symbiotic interaction among the flexible load, generation, and different houses thoroughly. The simulation results confirm that the integration of flexible demands into the grid using the designed CCMs results in the grid benefiting from stabilized voltage control, especially during peak demand hours. [ABSTRACT FROM AUTHOR]

A lithium-ion battery–ultracapacitor hybrid energy storage system (HESS) has been recognized as a viable solution to address the limitations of single battery energy sources in electric vehicles (EVs), especially in urban driving conditions, owing to its complementary energy features. However, an energy management strategy (EMS) is required for the optimal performance of the HESS. In this paper, an EMS based on the particle swarm optimization (PSO) of the fuzzy logic controller (FLC) is proposed. It aims to minimize battery current and power peak fluctuations, thereby enhancing its capacity and lifespan, by optimizing the weights of formulated FLC rules using the PSO algorithm. This paper utilizes the battery temperature as the cost function in the optimization problem of the PSO due to the sensitivity of lithium-ion batteries (LIBs) to operating temperature variations compared to ultracapacitors (UCs). An evaluation of optimized FLC using PSO and a developed EV model is conducted under the Urban Dynamometer Driving Schedule (UDDS) and compared with the unoptimized FLC. The result shows that 5.4% of the battery's capacity was conserved at 25.5 °C, which is the highest operating temperature attained under the proposed strategy. [ABSTRACT FROM AUTHOR]

The population growing faster than before, and availability of transportation options is increasing. Automobiles require combustion engines, which require fuel obtained from underground storage. This underground fuel storage is limited and depleting day-by-day. Many nations have set deadlines up to 2040 to stop producing automobiles that run on underground fuels. Researchers have concentrated on alternative modes of fuel for transportation. The world's largest Sedan marketplaces will transition to all-electric vehicles by 2035, providing a glimpse of greener future other than a significant financial prospect. Not only Sedan, the entire world is focussing on only green electric vehicles to maintain sustainability. However, electric vehicle charging stations are operated by using many conventional resources. Therefore, this paper aims to show how self-charging electric vehicles can help to reduce emissions caused by the direct use of conventional resources in charging stations along with the up-to-date status quo of the EV market. The key descriptions of electric vehicles on top of the battery's type which is randomly used in EVs, how the batteries are proficient in preserving and supplying power continuity itself in vehicles are talked about. Finally, the paper is consulting about charging-discharging system of electric vehicles to make the environment cleaner. [ABSTRACT FROM AUTHOR]

Batteries play a crucial role as energy storage devices across various industries. However, achieving high performance often comes at the cost of safety. Continuous monitoring is essential to ensure the safety and reliability of batteries. This paper investigates the advancements in battery monitoring technology, focusing on fiber Bragg gratings (FBGs). By examining the factors contributing to battery degradation and the principles of FBGs, this study discusses key aspects of FBG sensing, including mounting locations, monitoring targets, and their correlation with optical signals. While current FBG battery sensing can achieve high measurement accuracies for temperature (0.1 °C), strain (0.1 μ ε ), pressure (0.14 bar), and refractive index (6 × 10−5 RIU), with corresponding sensitivities of 40 pm/°C, 2.2 pm/ μ ε , −0.3 pm/bar, and −18 nm/RIU, respectively, accurately assessing battery health in real time remains a challenge. Traditional methods struggle to provide real-time and precise evaluations by analyzing the microstructure of battery materials or physical phenomena during chemical reactions. Therefore, by summarizing the current state of FBG battery sensing research, it is evident that monitoring battery material properties (e.g., refractive index and gas properties) through FBGs offers a promising solution for real-time and accurate battery health assessment. This paper also delves into the obstacles of battery monitoring, such as standardizing the FBG encapsulation process, decoupling multiple parameters, and controlling costs. Ultimately, the paper highlights the potential of FBG monitoring technology in driving advancements in battery development. [ABSTRACT FROM AUTHOR]

Batteries as a power source are the basis for all major hand tool manufacturers as vide variety of portable products became battery powered for more convenient usage. Manufacturers disable unapproved battery applications in their products by designing batteries specific for these products. In practice, the life of power tool batteries depends on two parameters: natural aging and the type of use. In a case study of a Battery Powered Grass Trimmer which battery broke after four years, the repair procedure for the package is shown. However, shortly after the repair, the Battery Powered Grass Trimmer suffered a bearing deformation that rendered it unusable. Due to its age and the unavailability of replacing electric engine, the Trimmer was scrapped and a detailed Life Cycle Analysis (LCA) applying SimaPro methodology is provided. Since the product under study is no longer on the market, a properly functioning, refurbished battery with significantly increased capacity is used in a new battery-powered grass trimmer from another manufacturer. The paper's final consideration underscores the need for an international standard that regulates battery compatibility and reduces waste, especially electronic waste. [ABSTRACT FROM AUTHOR]

Battery pack provides the backup power supply for DC system of power substations. In the event of an AC power outage or other accidents, it is an important guarantee for the reliable operation of power substation. To prevent possible failures, batteries usually require careful maintenance. Common methods are online monitoring, condition assessments, and health management. Among these, model-based techniques are widely used for battery monitoring and prognostics optimization. Data-driven methods are a good alternative solution when no mathematical models are available. As substations develop towards intelligent and unmanned modes, this paper proposes an online battery monitoring and management system based on the "cloud-network-edge-end" Internet of Things (IoT) architecture. Firstly, advanced battery monitoring system based on IoT architecture is reviewed in depth. It provides basis for later designing. Secondly, the battery online monitoring and management system is designed considering functional requirements and data link. Designing functions include ledger management, basic battery information display, real-time display of battery monitoring data, and the visualization of battery alarm information. It can implement online monitoring and intelligent maintenance management for battery operating status. Finally, the designed and developed system is applied in a 110 kV offshore substation, mainly providing battery maintenance suggestions and fault alarm prompts. Typical results of ledger information management, key parameter monitoring and alarm prompt are presented. This verifies the effectiveness and convenience of IoT-based system for the monitoring and management of batteries. [ABSTRACT FROM AUTHOR]

Depending on the PV power, load power, and battery status, the system may operate in different modes. The control loop may have to switch between operating modes. In practice, it is difficult to implement control loop switching because the transition and dynamic process are difficult to control. As a result, this paper presents a generalized mode control method that avoids loop switching across modes. First, system structure and topology are introduced. The operating conditions for both grid-connected and off-grid modes are then divided into six sub-cases. Furthermore, the control architecture, control loop, and reference transition for various scenarios are described. Finally, an experimental platform is built, and the results are presented to verify the proposed method. [ABSTRACT FROM AUTHOR]

The use of renewable energy presents a viable alternative to fossil fuels. However, their intermittent nature does not allow for an immediate response to energy demand. Thus, it is necessary and beneficial to harness various renewable sources and integrate a storage system as an auxiliary source to mitigate this intermittency. The hybridization of energy sources requires efficient management of power flows to ensure the proper functioning of the overall system, regardless of changing weather conditions. In this paper, we propose an intelligent power management control for hybrid wind-solar-battery systems connected to micro-grids based on fuzzy logic. The proposed control approach addresses several specific challenges compared to conventional methods in the intelligent energy management of renewable hybrid systems. It effectively manages the uncertainties and nonlinearities inherent in weather variations, optimizes performance by dynamically adjusting the operations of energy sources and storage systems, and ensures efficient realtime utilization of available energy resources, thus providing greater flexibility and adaptability. Additionally, it enhances the stability and reliability of micro-grids by integrating more flexible and adaptive decision-making mechanisms. The simulation results using MatLab/Simulink demonstrate the significant advantage of this intelligent management lies in its ability to precisely control the state of charge of the battery across five distinct levels, which is not achievable using traditional management practices that rely solely on the maximum and minimum levels of the state of charge. [ABSTRACT FROM AUTHOR]

The energy management system of a fuel cell electric robot should be highly responsive to provide the required power for various tactical operations, navigation of different routes, and acceleration. This paper presents a new multi-level online energy management strategy for a fuel cell electric robot based on the proposed functions of equivalent hydrogen fuel value evaluation, classification of the battery state of charge via the squared combined efficiency function, identification of the robot maneuver condition based on the proposed operation state of robot function, improvement of the overall energy efficiency based on the proposed function of the battery overcharge control, and separation of the functional points of the fuel cell based on the operational mode control strategy. The simulation study of the proposed online multi-level energy management strategy was carried out with MATLAB R2018b software to verify its superiority by comparing with other strategies. The results indicate a reduction in hydrogen consumption, reduction in fuel cell power fluctuations, prevention of battery overcharging, and incrementation in the total energy efficiency of energy storage systems compared to other energy management strategies. [ABSTRACT FROM AUTHOR]

In this work, we consider a problem from the field of power-aware scheduling in which a fleet of electric vehicles have to be charged in a minimum time. Each vehicle is equipped with a lithium-ion battery of a given capacity. The initial power used for charging each battery is known, whereas it is assumed that the power drops to zero at the moment when the battery gets fully loaded. The power usage function is linear and decreasing. The charging jobs are nonpreemptable and independent, whereas the total available amount of power is limited. The objective is to minimize the schedule length. In this paper, we analyze the case of a problem with identical jobs that already cover a wide variety of practical situations. By employing inverses of natural numbers, similar to harmonic series, we prove two properties of this case, and we also discuss the phenomenon of the stabilization of the difference between the start times of two successive jobs in a schedule. We also take under examination a few special cases of the problem. Some conclusions and directions for future research are given. [ABSTRACT FROM AUTHOR]

The paper presents a normalized, varying step size-based least mean square-based control for a standalone microgrid and Ant Lion optimization-based maximum power point tracking. This modified version of the incremental conductance algorithm addresses issues like slow dynamic response, fixed step size issues, and steady state oscillations. Comparative analysis with well-known techniques shows that Ant Lion optimizes the tracking of maximum power points more accurately, with fewer oscillations and increased efficiency. Power management and power quality are maintained through proposed adaptive voltage source converter control. The proposed voltage control shows better performance under various dynamic and steady conditions. [ABSTRACT FROM AUTHOR]

The existing battery management systems perform many functions, such as simply monitoring the battery's voltage, current, and temperature for the most basic and compensating energy imbalances between battery cells for the most advanced systems. In this last example, the function balancing helps protect the battery from obtaining a better lifespan. However, these systems with such functions remain complex because they involve techniques specific to power electronics and energy conversion. The number of components, implementation complexity, and cost increased. The work presented in this paper fits directly into this context. The main objective is to provide a solution to the problem of battery management and careful pack cell balancing. The proposed system aims to balance the battery pack cells based on the intermediate state of charge by charging or discharging the imbalanced cell. The implementation of the proposed control strategy was for a battery pack composed of five cells under MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are becoming very popular nowadays to reduce the consumption of oil and environmental pollution. The use of battery and super-capacitor is increasing as the power-source of EVs. The bi-directional DC-DC converter is essential to integrate the battery and super-capacitor with the motor of the vehicle. However, a conventional second-order bi-directional DC-DC converter cannot give very high/low output voltage due to its efficiency reduction at extreme duty cycles, which is prerequisite for EVs. The problems of achieving high efficiency in wide-input-wide-output (WIWO) voltage range bidirectional operation using a conventional bidirectional converter are summarized in this paper. Additionally, the available converters from the literature for WIWO voltage range operation are discussed in detail. The various wide voltage range DC-DC converters are classified into different categories based on their operating principle. Additionally, the advantage and disadvantages of these various wide voltage range converter topologies are explained for the EV application. Finally, a general conceptual solution to achieve a WIWO converter with high efficiency is proposed. It is essential to change the voltage level of the motor input as per the speed requirement. Hence, this paper presents a clear idea for the WIWO bi-directional converters for EV application. [ABSTRACT FROM AUTHOR]

The increasing global warming problem has pushed the community to implement emission reduction measures in almost every segment of human life. Since the major source of anthropogenic Greenhouse Gases (GHGs) is fossil fuel combustion, in the shipping sector, these measures are oriented toward a reduction in tailpipe emissions, where the replacement of traditional internal combustion marine engines with zero-carbon technologies offers the ultimate emission reduction results. According to the International Maritime Organization (IMO) GHG strategy, vessels involved in international shipping must achieve a minimum 50% reduction in their GHG emissions by 2050. However, this requirement does not extend to fishing vessels, which are significant consumers of fossil fuels. This paper deals with the full electrification of two types of fishing vessels (purse seiners and trawlers), wherein different Lithium-ion Batteries (LiBs) are considered. To investigate their environmental footprint and profitability, Life-Cycle Assessments (LCAs) and Life-Cycle Cost Assessments (LCCAs) are performed. The comparison of all-electric fishing vessels with existing diesel-powered ships highlighted the Lithium Iron Phosphate (LFP) battery as the most suitable alternative powering option regarding environmental and economic criteria. [ABSTRACT FROM AUTHOR]

We are coming across cases, where the education system is being distorted and perverted. As the present security of our education system has several loopholes that can be exploited to obtain access to the locations were question papers are being kept, posing a significant threat to society, to address this problem we engineered an intrusion detection recording system with a biometric lock. Our project is a result of combination of two already existing methodologies - Wireless Biometric Lock and Noise detector with automatic recording system. This combination provides us with a more secure system than the existing individual implementation. Thus, our project is a noise sensor-based device with an automatic recording system that can also lock the locker or door using a fingerprint-based biometric interface which not only detects intrusion but also traps the person who tries to intrude. [ABSTRACT FROM AUTHOR]

The battery needed to store electricity is an essential element of a photovoltaic energy production system. The place where this system element is located, during its operation, will thermally influence the way the battery works. The specialized literature presents studies on the influence of temperature on the electrical working capacity of the battery, but through this scientific paper we want to study a concrete case of a LiFePO4 battery and quantify the influence of temperature differences in the working space on the differences in the energy capacities generated by the same battery. The experimental setup allowed recording the temperature of the space where the battery is placed for a long time, so we ensured that the temperature of the battery is approximately equal to that of the working space, just like in a real case of a photovoltaic system. The monitoring of the electric power of the battery in operation was carried out only during its discharge, by imposing a constant discharge current simultaneously with the recording of the voltage at the battery terminals throughout this cycle. At the end of the experiments, we associated the average temperatures during the discharge cycles with the average powers discharged by the battery in each thermal frame. The quantification was achieved by relating the power differences generated to the temperature differences of the different thermal situations experienced. The importance of this study resides into the highlighting of importance to maintain an optimal temperature for the space where the batteries are stored, having as technical effect the maintaining the power's functioning optimal rate of these. The design of a photovoltaic system must be oriented to a long term calculus regarding power's rate depending by battery's working space temperature. [ABSTRACT FROM AUTHOR]

Battery health assessments are essential for roadside energy storage systems that facilitate electric transportation. This paper uses the samples from the charging and discharging data of the base station and the power station under different working conditions at different working hours and at different temperatures to demonstrate the decay of the battery health of a roadside energy storage system under different cycles. In this paper, for the first time, the predicted state-of-health values are obtained by extracting the characteristic quantities affecting the battery health based on three indicators: the internal resistance, the rate of change of voltage, and the change of temperature. Data on state of health are clustered by K-Means, GMM, K-Means++ and divided into high, medium, and low levels. Using a comparison of the three methods, GMM clustering appears to be the best at reflecting the charging and discharging capacity of the battery. [ABSTRACT FROM AUTHOR]

This paper reports the development of a 10Ah lithium-ion pouch battery cell using stainless-steel laminated film as the casing material for JAXA's SLIM lunar lander. By selecting the pouch format, the mass ratio of the case and electrode terminals is significantly reduced, which is superior to conventional space batteries using prismatic metal cases. A high specific energy of approximately 130Wh/kg was achieved. In addition, unlike standard batteries using aluminumlaminated film, the battery developed during this study deforms little when subjected to a vacuum. It can thus be mounted on a spacecraft with a simple, lightweight bracket, contributing to higher specific energy as a module. This paper reports the results of environment tests for the SLIM mission and the basic electrical characteristics of the battery. [ABSTRACT FROM AUTHOR]

This paper proposes and evaluates the behavior of a new health indicator to estimate the capacity fade of lithium-ion batteries and their state of health (SOH). This health indicator is advantageous because it does not require the acquisition of data from full charge–discharge cycles, since it is calculated within a narrow SOC interval where the voltage vs. SOC relationship is very linear and that is within the usual transit range for most practical charge and discharge cycles. As a result, only a small fraction of the data points of a full charge–discharge cycle are required, reducing storage and computational resources while providing accurate results. Finally, by using the battery model defined by the Nernst equation, the behavior of future charge–discharge cycles can be accurately predicted, as shown by the results presented in this paper. The proposed approach requires the application of appropriate signal processing techniques, from discrete wavelet filtering to prediction methods based on linear fitting and autoregressive integrated moving average algorithms. [ABSTRACT FROM AUTHOR]

The performance of electric vehicle (EV) drivetrains depends on the power capability of individual components, including the battery pack, motor drive, and electric motor. To ensure safety, maximum power must be limited by considering the constraint of the weakest component in the drivetrain. While there exists a large body of work that discusses state-of-power (SoP) estimation for individual components, there is no work that considers all the components' limiting factors at once. Moreover, research on how to use these limits to adjust the performance at the system level has been rare. In this paper, the SoPs of the components are used to estimate the state-of-function (SoF) of the EV drivetrain. The SoF is defined as the maximum charge/discharge power that can be sourced and/or sunk by the drivetrain without violating the safety limits of its components. The component-level SoP estimations are fulfilled using several digital algorithms based on recursive least-squares (RLS) and Kalman filters (KFs), as well as by taking into account specific limiting conditions such as high driving altitude and ambient temperatures. An EV driven by a hybrid energy storage system based on a battery/supercapacitor, and a permanent-magnet synchronous motor is considered the use case. Based on the drivetrain SoF estimation, we propose two de-rating schemes to ensure that the drivetrain safety limits will be respected: adaptive cruise control and adaptive adjustment of pedal sensitivity. The de-rating schemes are introduced to a so-called recommender system that is implemented in MATLAB/STATEFLOW. The recommender system provides advisory feedback to the driver to switch to a different driving mode to ensure safety. The simulation results over a standard drive cycle using MATLAB/SIMULINK and STATEFLOW show the effectiveness of the proposed design at both component and system levels. The paper also proposes an implementation concept for the integration of the proposed recommender system into the advanced driver assistance system (ASAS). [ABSTRACT FROM AUTHOR]

This study presents an energy regeneration model and some theory required to construct a regeneration braking system. Due to the effects of carbon dioxide (CO2) emissions, there is increasing interest in the use of electric vehicles (EVs), electric bikes, electric bicycles, electric buses and electric aircraft globally. In order to promote the use of electric transportation systems, there is a need to underscore the impact of net zero emissions. The development of EVs requires regenerating braking system. This study presents the advantages of regenerative braking. This system is globally seen in applications such as electric cars, trams, and trains. In this study, the design specification, design methodology, testing configurations, Simulink model, and recommendations will be outlined. A unique element of this work is the practical experiment that was carried out using 1.5 Amps with no load and 2.15 Amps with a load. The discharge voltage was purely from the 22 W bulb load connected to the capacitor bank as we limited this study to the use of 1.5 Amps and it took 15 min for a full discharge cycle, after which no charge was left in the capacitor bank. The results showed that the discharge rate and charging rate for the regenerative braking system were effective but could be improved. The objective of this paper is to investigate how a supercapacitor works alongside a battery in regenerative braking applications. This study demonstrates that the superconductor used can deliver maximum power when required. Also, it can also withstand elevated peaks in charging or discharging current via the supercapacitor. Combining a battery with a supercapacitor reduces the abrupt load on the battery by shifting it to the capacitor. When these two combinations are used in tandem, the battery pack's endurance and lifespan are both boosted. [ABSTRACT FROM AUTHOR]

This paper addresses the optimal sizing of Hybrid Renewable Energy Systems (HRESs), encompassing wind, solar, and battery systems, with the aim of delivering reliable performance at a reasonable cost. The focus is on mitigating unscheduled outages on the national grid in Iraq. The proposed On–off-grid HRES method is implemented using MATLAB and relies on an iterative technique to achieve multi-objectives, balancing reliability and economic constraints. The optimal HRES configuration is determined by evaluating various scenarios related to energy flow management, electricity prices, and land cover effects. Consumer requirements regarding cost and reliability are factored into a 2D optimization process. A battery model is developed to capture the dynamic exchange of energy among different renewable sources, battery storage, and energy demands. A detailed case study across fifteen locations in Iraq, including water, desert, and urban areas, revealed that local wind speed significantly affects the feasibility and efficiency of the HRES. Locations with higher wind speeds, such as the Haditha lake region (payback period: 7.8 years), benefit more than urban areas (Haditha city: payback period: 12.4 years). This study also found that not utilizing the battery, particularly during periods of high electricity prices (e.g., 2015), significantly impacts the HRES performance. In the Haditha water area, for instance, this technique reduced the payback period from 20.1 to 7.8 years by reducing the frequency of charging and discharging cycles and subsequently mitigating the need for battery replacement. [ABSTRACT FROM AUTHOR]

From 2035 onward, the registration of new conventional internal combustion engine vehicles will be prohibited in the European Union. This shift is driven by steadily rising fuel prices and growing concerns over carbon dioxide emissions. Electric vehicles (EVs) are becoming increasingly popular across Europe, and many manufacturers now offer modified models, making pure internal combustion versions unavailable for certain types. Additionally, the comparatively lower operational costs of EVs for end users further bolster their appeal. In the European Union, new directives have been established to define innovative approaches to energy use in Member States, known as energy communities. This article provides a comprehensive overview of the architecture of energy communities, electric vehicles, and the V2X technologies currently on the market. It highlights the evolution of electric vehicle adoption in the EU, contextualizing it within broader energy trends and presenting future challenges and development opportunities related to energy communities. The paper details the diversification of electricity sources among Member States and the share of generated electricity that is utilized for transport. [ABSTRACT FROM AUTHOR]

Wireless sensors are used for smart building monitoring, biomedical applications, intelligent home appliances, urgent disaster management and precision agriculture production. These devices today operate with batteries that are very difficult to change. The major problem hindering the widespread deployment of wireless sensor networks is the need to constantly replace them because their batteries expires. We can see that it is possible to charge them using energy harvested from solar, vibration, thermal or ambient radio frequency sources. we can implement sustainable health surveillance systems, agriculture, mining, environmental protection and national infrastructure, which will improve the quality of life, save money and achieve ecological goals. We realized that it would be wise to specify a field of application for internet of things in order to be able to clarify the identification of the problem of energy consumption and its relation with renewable energies. In addition, one of the most interesting applications for the socio-economic fields in the world in recent years is Smart Farming. In this paper, we reviewed a state of the art on the use of renewable energy harvesting in precision agriculture. [ABSTRACT FROM AUTHOR]

Using multiple input power sources increases the reliability of electric vehicles compared to a single source. However, the inclusion of other sources exhibits complexity in the controller system, such as computing time, program difficulty, and switching speed to connect or disconnect the input power to load. To ensure optimal performance and avoid overloading issues, the EV system needs sophisticated control. This work introduces a machine-learning-based controller using an artificial neural network to solve these problems. This paper describes the detailed power management control methodology using multiple sources like solar PV, fuel cells, and batteries. Novel control with an instantaneous reference current scheme is used to manage the input power sources to satisfy the power demand of electric vehicles. The proposed work executes the power split-up operation with standard and actual drive cycles and maximum power point tracking for PV panels using MATLAB Simulink. Finally, power management with a machine learning technique is implemented in an experimental analysis with the LabVIEW software, and an FPGA controller is used to control a 48 V, 1 kW permanent-magnet synchronous machine. [ABSTRACT FROM AUTHOR]

In this work, an optimal control scheme based on the Maximum Power Point tracking for the Wind Energy Conversion System using Permanent Magnet Synchronous Generator (PMSG) is proposed and also modeled. The system studied in this paper consists of wind energy system powering a battery using a buck-boost converter as an interface. By modifying the buck-boost duty cycle, we vary the reflected voltage at PMSG, and accordingly its speed. It is controlled with Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) approach. The overall system is simulated with MATLAB/SIMULINK. [ABSTRACT FROM AUTHOR]

The widespread adoption of electric vehicles (EVs) has brought significant advancements in transportation technology, addressing the challenges of environmental sustainability and reducing dependence on fossil fuels. However, one of the critical aspects in the development of EVs is the efficient management of the battery system, particularly in terms of temperature control. The temperature of the battery cells plays a crucial role in determining their performance, lifespan, and overall safety. This paper presents a study on the application of fuzzy logic for electric vehicle battery temperature control. Fuzzy logic provides a flexible and robust framework for modeling and controlling complex systems with uncertain and imprecise information. By employing fuzzy logic-based algorithms, the temperature of the EV battery can be effectively regulated, ensuring optimal performance and longevity. To validate the effectiveness of the proposed approach, simulations and experiments are conducted using a representative EV battery system. The results demonstrate that the fuzzy logic-based temperature control system effectively maintains the battery temperature within the desired range, thereby improving battery performance, efficiency, longevity and reducing battery consumption by 10% compared to PID control. [ABSTRACT FROM AUTHOR]

Growing awareness of greenhouse gas emissions and exhaustion of fossil fuels leads to the adoption of electric vehicles (EVs). However, the major limitations with respect to EV technology are the driving range and charging time. Also, the proliferation of EVs overloads the power grid and paves the way of incorporating renewable energy sources and energy storage devices. The use of multiple sources necessitates the deployment of compact, low-cost, and high-power electronic converters. This paper proposes a novel configuration of a Multi-Source Non-Isolated Quasi-Resonant Converter (MSNQRC) to overcome the limitations in the charging infrastructure. Due to the presence of a quasi-resonant network, the proposed MSNQRC with a single switch can achieve high voltage gain even at low-duty cycles, provide continuous current and low voltage stress. In addition, this paper elaborates on the parametric design of the converter along with PV modeling based on load ratings and the reliability research of MSNQRC by analysing component failures. A prototype model of 300W is built to verify the efficacy of the designed converter model. The results thus obtained validate the designed model and prove that the proposed system can be used for off-board battery charging systems. [ABSTRACT FROM AUTHOR]

While hybrid ship drive systems may offer a large potential, a thorough analysis is needed as it is strongly dependent on the operational profile. The fixing of costs during the early design stage, leads to the necessity of a precise evaluation of the systems efficiency within this phase. Conducting statistic-based calculations can be inadequate due to the time-dependent behavior of the battery. Moreover, idealized temporal data is often utilized for the design of battery supported ships. Therefore, this paper discusses the consequential inaccuracies using statistical or smoothed data. But also examines the potential of an advanced in-house developed statistical approach. For the examination, an internal developed method for dimensioning hybrid ship power systems is used. The paper shows that conducting statistical calculations lead to incorrect modeling of battery behavior, while smoothed power time-series can result in an overestimation of the battery lifetime (up to 21% less charge cycles). [ABSTRACT FROM AUTHOR]

Digital Twin (DT) has been considered one of the most promising technologies promoting the development of the industry and has successfully achieved significant applications in many fields including national defense, intelligent manufacturing, smart cities, and so on. In addition, DT is gradually used in the research of automobiles which are necessary means of transportation in people's life. A systematic review of the definitions of DT and its applications in automotive-related fields reported in the literature is presented in this paper, with the overall goal to summarize almost all the related research achievements and stimulate innovative thinking. The digital twin, its structure, and its evolution are systematically reviewed. And all reviewed automotive applications of DT are divided into three categories: automotive industry, transportation, and batteries which is the research hotspot in the automotive field. Besides, these methods and ideas will be emphasized in this paper. Particularly, future development directions of digital twins in the automotive field are highlighted. [ABSTRACT FROM AUTHOR]

The wide application of clean energy has promoted the development of microgrids. For direct current (DC) microgrids, power fluctuations are inevitable, because photovoltaics, wind power and other clean energy sources are very unstable, which will bring great trouble to DC microgrids. Hybrid energy storage systems (HESS) are an effective solution to suppress power fluctuations. For a HESS composed of battery and supercapacitor (SC), a low-pass filter is usually used to allocate energy and power requirements to each energy storage unit, but the filter constant of the filter cannot be dynamically adjusted to adapt to different situations. The low-pass filter compensation coefficient used in this paper will change with the state of charge and discharge and dynamically change and allocate different power requirements to the battery and SC according to the actual operating conditions of the HESS. The objective function of DC bus power fluctuation is established, and the optimized particle swarm algorithm (PSO) is used to obtain the output power coefficient of each energy storage unit. The output coefficient of the HESS control strategy has the characteristics of fast convergence speed and high computational efficiency in the optimization process, and it will not fall into the local optimal solution. Through the design experiment, the SC can withstand more high-frequency components, fully utilize the advantages of SC with fast response to power fluctuations, improve the performance of HESS and have great engineering application value. [ABSTRACT FROM AUTHOR]

The development of microgrids is progressing due to intelligent load demands, clean energy, batteries and electric vehicles. The presence of such systems in microgrids causes power balance inconsistency, leading to increased power losses and deviation in voltage. In this paper, a mixed-integer non-linear programming model is proposed for modelling island microgrid energy management considering smart loads, clean energy resources, electric vehicles and batteries. Similarly, a flexible distributed AC transmission system device is proposed to prevent voltage deviation and reduce power losses. A scenario-based multi-objective function has been proposed to decrease energy losses and voltage deviations and energy outages of clean energy resources, reduce emissions from fossil-fired distributed generation and finally decrease load outages to reduce the vulnerability of the islanded microgrid. Regarding the proposed mixed-integer non-linear model and the high number of variables and constraints, a modified evolutionary algorithm based on particle swarm optimization has been proposed to solve the proposed model, which can be more efficient than other algorithms to achieve global optimal solutions. The model presented is implemented on a 33-node island microgrid and the results illustrate that the proposed algorithm and model are effective in reducing energy losses and voltage deviation, as well as reducing the vulnerability of the microgrid. The simulation results demonstrate that the proposed approach can lead to significant improvements in the performance of the microgrid. Specifically, the approach can result in a 27% reduction in losses, a 6% reduction in pollution and a 31% improvement in voltage. Additionally, the approach allows maximum utilization of renewable energy sources, making it a promising solution for sustainable energy management. [ABSTRACT FROM AUTHOR]