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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]

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]

As the use of electrochemical batteries, especially lithium–ion (Li-Ion) batteries, increases due to emerging applications and expanding markets, the accurate and fast estimation of their state of health (SOH) is becoming increasingly important. The accuracy of the SOH estimation is highly dependent on the correlation strength between the used indicator and SOH and the accuracy of the SOH indicator measurement. This paper presents a new differential indicator which has a strong and consistent correlation with the SOH of Li-Ion batteries, based on a new Electrochemical Impedance Spectrum (EIS) Phase–Magnitude relationship. It is shown in this paper that the EIS Phase–Magnitude relationship exhibits a phase-based differential impedance magnitude SOH indicator between a first-phase peak point and a last-phase valley point. Because of the differential nature of this SOH indicator and because the two impedance values are measured at a phase peak point and a valley phase point regardless of the phase absolute values, the effect of impedance measurement shift/offset (error) on SOH estimation is reduced. This supports the future development of more accurate and faster online and offline SOH estimation algorithms and systems that have a higher immunity to impedance measurement shift/offset (error). Furthermore, in this work, the EIS was measured for a lithium–ion battery that was down to a ~15% SOH, which was not only used to support the conclusions of this paper, but also helped in filling a gap in the literature for EIS data under deep/high degradation levels. [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]

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]

This paper presents a method to validate state of charge (SOC) estimations in batteries for their use in remotely manned aerial vehicles (UAVs). The SOC estimation must provide the mission control with a measure of the available range of the aircraft, which is critical for extended missions such as search and rescue operations. However, the uncertainty about the initial state and depth of discharge during the mission makes the estimation challenging. In order to assess the estimation provided to mission control, an a posteriori re-estimation is performed. This allows for the assessment of estimation methods. A reverse-time Kalman estimator is proposed for this task. Accurate SOC estimations are crucial for optimizing the utilization of multiple UAVs in a collaborative manner, ensuring the efficient use of energy resources and maximizing mission success rates. Experimental results for LiFePO4 batteries are provided, showing the capabilities of the proposal for the assessment of online SOC estimators. [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]

At present, the energy consumption and carbon emissions of maritime transportation have raised concerns about environmental issues. A potential way to reduce carbon emissions from vessels is the use of chemical-based carbon capture and storage (CCS) technology. However, this technology faces challenges such as high energy consumption, large space occupation, and high processing costs. Therefore, the development of a technology with low energy consumption and compact CO2 storage is crucial to promote the advancement of CCS technology. This paper introduces a magnesium CO2 battery system that converts CO2 into new energy, in the form of hydrogen, while storing CO2. By preparing highly efficient catalytic electrodes and testing the electrolyte and CO2 flow rate on the battery performance, the optimal process parameters were determined to be Pd/CeO2-oct for the electrodes, a 0.5 mol/L NaOH solution for the electrolyte, and a CO2 flow rate of 1 L/h. The battery system demonstrated high cycling stability and conversion efficiency at a current density of 8 mA·cm−2, with a stable cycling time of 600 min (20 cycles), a cathode hydrogen production of 10.135 mL, and a Faraday efficiency of 97.03%. [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]

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 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]

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 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]

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 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]

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]

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]

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]

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]

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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]

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]

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]

In order to promote low-carbon fuels such as hydrogen to decarbonize the maritime sector, it is crucial to promote clean fuels and zero-emission propulsion systems in demonstrative projects and to showcase innovative technologies such as fuel cells in vessels operating in local public transport that could increase general audience acceptability thanks to their showcase potential. In this study, a short sea journey ferry used in the port of Genova as a public transport vehicle is analyzed to evaluate a "zero emission propulsion" retrofitting process. In the paper, different types of solutions (batteries, proton exchange membrane fuel cell (PEMFC), solid oxide fuel cell (SOFC)) and fuels (hydrogen, ammonia, natural gas, and methanol) are investigated to identify the most feasible technology to be implemented onboard according to different aspects: ferry daily journey and scheduling, available volumes and spaces, propulsion power needs, energy storage/fuel tank capacity needed, economics, etc. The paper presents a multi-aspect analysis that resulted in the identification of the hydrogen-powered PEMFC as the best clean power system to guarantee, for this specific case study, a suitable retrofitting of the vessel that could guarantee a zero-emission journey. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are widely used in the electric vehicle industry due to their recyclability and long life. However, a failure of lithium-ion batteries can cause some catastrophic accidents, such as electric car battery explosion fires and so on. To prevent such harm from occurring, it is essential to monitor the remaining useful life of lithium-ion batteries and give early warning. In this paper, an adaptive noise reduction approach is proposed to predict the RUL (Remaining Useful Life) of lithium-ion batteries, which uses CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) combined with wavelet decomposition to achieve adaptive noise reduction decomposition, and then inputs the obtained IMF (Intrinsic Mode Function) components into LS–RVM (Least Square Relevance Vector Machine) for training, prediction, and reconstruction, so as to achieve high-precision prediction of RUL. Moreover, in order to verify the validity of the model, the model in this paper is compared with other common models. The results demonstrate that the RMSE, MAPE, and MAE of the proposed model are 0.008678, 0.005002, and 0.006894, and that it has higher accuracy than the other common prediction models. [ABSTRACT FROM AUTHOR]

In the pursuit of more efficient vehicles on the world's roads, the vehicle thermal management system has become a limiting factor when it comes to EV range and battery life. In extreme climates, if the thermal system cannot pull down or warm up the EV powertrain in a timely manner, the battery is at serious risk of capacity loss or accelerated degradation. As waste heat is inherently limited with EVs, the way in which we provide the heat for warm-up must be as efficient as possible to reduce the load on the battery. In this paper, a revolutionary waste heat recovery (WHR) thermal management system designed by Tesla, nicknamed the 'Octovalve', is described, modelled, and simulated. This paper contributes to collective knowledge by presenting an in-depth breakdown of the key operating modes and outlining the potential benefits. Modelled in the multidomain Simulink Simscape software, the octovalve's performance is directly compared to a typical EV WHR thermal management system. The system under analysis is shown to significantly reduce EV energy consumption and battery load during warm-up but at the cost of overall warm-up time. Unlike any other WHR system found in literature, this system has a heat pump with can perform air conditioning and heat pump tasks simultaneously, which is shown to have a remarkable impact on energy efficiency and battery life. [ABSTRACT FROM AUTHOR]

Due to the many attractions of solar energy, a lot of research is being done in research centers to improve the usefulness of photovoltaic systems (PVs). Despite the widespread use of PVs in different societies, one of the biggest challenges of these sources is to obtain the maximum possible output power. Up to now, several investigations are performed to achieve the maximum power point (MPP) in PV systems. In this paper, an incremental conductance (INC) in the combination of farmland fertility optimization (IFFO) based on the adaptive neuro-fuzzy inference system (ANFIS) is applied to implement the MPPT controller. The proposed MPPT method applies hybrid IFFO in different temperatures and radiation situations to attain optimal voltages. Then, the ANFIS and the INC algorithm try to find the MPP as the ANFIS cannot find the precise point alone. The main advantage of the ANFIS and INC is providing less number of samples for training. Simulations are performed to confirm the advantage of the technique over the conventional approach. Achieving the global optimum point, lower oscillations around MPP and fast tracking are approved using the simulations with the suggested IFFO-ANFIS-INC method. [ABSTRACT FROM AUTHOR]

This paper presents an electric vehicle (EV) switched reluctance motor (SRM) drive with incorporated operation capabilities integrated into the utility grid, the microgrid, and another EV. The motor drive DC-link voltage is established from the battery through an interleaved boost/buck converter with fault tolerance. The varied DC-link voltage can improve driving performance and reduce battery energy consumption over a wide speed range. Through a well-designed current control scheme, speed control scheme, and dynamic commutation tuning scheme, the established SRM drive possesses good performance in the motor driving mode. During deceleration, the regenerative braking energy can be effectively recovered to the battery. When the EV is in idle mode, the grid-to-vehicle (G2V) charging operation can be conducted through the bidirectional switch mode rectifier (SMR) and CLLC resonant converter. Satisfactory charging performance with good line drawn power quality and galvanic isolation is preserved. Conversely, the vehicle-to-grid (V2G) discharging operation can be performed. The EV can make movable energy storage device applications. Finally, the interconnected operations of the developed EV SRM drive to vehicle and microgrid are presented. Through vehicle-to-vehicle (V2V) operation, it can supply energy to the nearby EV when the battery is exhausted and needs roadside assistance. In addition, microgrid-to-vehicle (M2V) and vehicle-to-microgrid (V2M) operations can also be conductible. The EV battery can be charged from the microgrid. Conversely, it can also provide energy support to the microgrid. [ABSTRACT FROM AUTHOR]

Energy storage systems are essential in modern energy infrastructure, addressing efficiency, power quality, and reliability challenges in DC/AC power systems. Recognized for their indispensable role in ensuring grid stability and seamless integration with renewable energy sources. These storage systems prove crucial for aircraft, shipboard systems, and electric vehicles, addressing peak load demands economically while enhancing overall system reliability and efficiency. Recent advancements and research have focused on high-power storage technologies, including supercapacitors, superconducting magnetic energy storage, and flywheels, characterized by high-power density and rapid response, ideally suited for applications requiring rapid charging and discharging. Hybrid energy storage systems and multiple energy storage devices represent enhanced flexibility and resilience, making them increasingly attractive for diverse applications, including critical loads. This paper provides a comprehensive overview of recent technological advancements in high-power storage devices, including lithium-ion batteries, recognized for their high energy density. In addition, a summary of hybrid energy storage system applications in microgrids and scenarios involving critical and pulse loads is provided. The research further discusses power, energy, cost, life, and performance technologies. [ABSTRACT FROM AUTHOR]

Second-life applications for lithium-ion batteries offer the industry opportunities to defer recycling costs, enhance economic value, and reduce environmental impacts. An accurate prognosis of the remaining useful life (RUL) is essential for ensuring effective second-life operation. Diagnosis is a necessary step for the establishment of a reliable prognosis, based on the aging modes involved in a cell. This paper introduces a method for characterizing specific aging phenomenon in Graphite/Lithium Iron Phosphate (G/LFP) cells. This method aims to identify aging related to the loss of active material at the negative electrode (LAMNE). The identification and tracking of the state of health (SoH) are based on Incremental Capacity Analysis (ICA) and Differential Voltage Analysis (DVA) peak-tracking techniques. The remaining capacity of the electrode is thus evaluated based on these diagnostic results, using a model derived from half-cell electrode characterization. The method is used on a G/LFP cell in the format 18650, with a nominal capacity of 1.1 Ah, aged from its pristine state to 40% of state of health. [ABSTRACT FROM AUTHOR]

Electrically powered rail transport is constantly increasing in order to meet the high demand for people and cargo transportation, whether with high-speed trains, subways, suburban trains, or electric tramways. In these types of applications, power electronics solutions such as integrated and efficient converters with multiple functionalities are highly desirable. Among these converters, one family stands out for its ability to generating multiple output terminals with reduced number of switches, namely, the nine-switch converter. Therefore, this paper proposes a multiport converter solution based on the nine-switch converter topology that integrates multiple functionalities with a reduced switch count. The converter, responsible for the power drive of the electric tramway, is exclusively powered by a battery. Moreover, it presents a strategically connected passive filter that provides a low-impedance path for high-frequency currents, avoiding leakage of the current circulation in the induction motor. Its phase-shift pulse-width modulation is capable of reducing the high-frequency components of the current delivered by the battery. The energy storage system is designed to optimize the system capacity based on the known real load profile of a public tramway, with a maximum power of 532.1 kW. The control system is designed and applied considering the battery as the energy source. Simulations were performed in the Matlab/Simulink environment to validate the proposed system, along with experiments using a reduced-scale prototype controlled by the dSPACE platform. The results present the converter's proper operation with integration of the source and AC load, presenting improved features compared with conventional solutions in terms of reduced leakage of the current circulation from the AC load and reduced battery current ripple. [ABSTRACT FROM AUTHOR]

The deployment of energy storage systems can play a role in peak and frequency regulation, solve the issue of limited flexibility in cleaner power systems in China, and ensure the stability and safety of the power grid. This paper presents a comprehensive environmental impact analysis of a lithium iron phosphate (LFP) battery system for the storage and delivery of 1 kW-hour of electricity. Quantities of copper, graphite, aluminum, lithium iron phosphate, and electricity consumption are set as uncertainty and sensitivity parameters with a variation of [90%, 110%]. The results show that global warming potential is 9.08E+01 kg CO2 eq. and fossil resource use is 1.21E+03 MJ, with uncertainty ranges of [8.54E+01, 9.23E+01] and [1.15E+03, 1.23E+03], respectively. Electricity consumption during the manufacture and installation process is the greatest contributor to climate change (CO2 eq. emissions), accounting for 39.71% and largely owing to non-renewable sources, followed by cathode materials at 27.85% and anode materials at 18.36%. The disposal and recycling process offers emission reductions but requires an additional 1.17% use of fossil resources. Sobol T indices for the quantity of electricity are the highest for acidification, climate change, fossil resource use, and ionizing radiation. By considering the pathway of China's electricity mix from 2020 to 2050 under the Paris Agreement's 2° target, the potential for environmental emission reduction in the system is evaluated. The results show that the greener electricity mix could lead to a 24.59% reduction in acidification impact, a 35.74% reduction in climate change impact, a 33.24% reduction in fossil resource use, and a 44.13% reduction in ionizing radiation impact. This study offers a comprehensive view of the environmental impact reductions associated with the lithium iron phosphate battery and its industry. [ABSTRACT FROM AUTHOR]

This paper presents the development of an airport bipolar DC microgrid and its interconnected operations with the utility grid, electric vehicle (EV), and more electric aircraft (MEA). The microgrid DC-bus voltage is established by the main sources, photovoltaic (PV) and fuel cell (FC), via unidirectional three-level (3L) boost converters. The proposed one-cycle control (OCC)-based current control scheme and quantitative and robust voltage control scheme are proposed to yield satisfactory responses. Moreover, the PV maximum power point tracking (MPPT) with FC energy-supporting approach is developed to have improved renewable energy extraction characteristics. The equipped hybrid energy storage system (HESS) consists of an energy-type battery and a power-type flywheel; each device is interfaced to the common DC bus via its own 3L bidirectional interface converter. The energy-coordinated operation is achieved by the proposed droop control. A dump load leg is added to avoid overvoltage due to an energy surplus. The grid-connected energy complementary operation is conducted using a neutral point clamped (NPC) 3L three-phase inverter. In addition to the energy support from grid-to-microgrid (G2M), the reverse mcrogrid-to-grid (M2G) operation is also conductible. Moreover, microgrid-to-vehicle (M2V) and vehicle-to-microgrid (V2M) bidirectional operations can also be applicable. The droop control is also applied to perform these interconnected operations. For the grounded aircraft, bidirectional microgrid-to-aircraft (M2A)/aircraft-to-microgrid (A2M) operations can be performed. The aircraft ground power unit (GPU) function can be preserved by the developed microgrid. The MEA on-board facilities can be powered by the microgrid, including the 115 V/400 Hz AC bus, the 270 V DC bus, the switched-reluctance motor (SRM) drive, etc. [ABSTRACT FROM AUTHOR]

Batteries are one of the most crucial energy storage devices today, and battery-energy management technology has an extremely significant impact on the performance and lifespan of batteries. The traditional design approach for battery-energy management platforms often neglects considerations for charging and discharging scenarios. Additionally, functional modules are designed independently, leading to incompatibility issues between hardware and control units, thereby limiting the system's performance. To address these challenges and enhance system coordination, this paper proposes a systematic design and implementation method for a battery-energy comprehensive management platform applied in charging and swapping scenarios. The method consists of four parts: hardware design, a dynamic load charging-balance control strategy, a composite micro-source hierarchical coordination control strategy, and a system emergency-response and protection strategy. The proposed method has been successfully applied to a design and has been used to build a battery-energy comprehensive management platform. Finally, through experiments, it has been demonstrated that this system can achieve energy scheduling, battery-energy balance, mode switching, and fault protection in a stable and reliable manner. [ABSTRACT FROM AUTHOR]

Beyond solar and wind energy, wave energy is gaining great interest due to its very high theoretical potential, although its stochastic nature causes intermittent and fluctuating power production. Energy storage system (ESS) integration to wave energy converter (WEC) plants represents a promising solution to mitigate this issue. To overcome the technological limits of the single storage devices, the hybridization of complementary ESSs represents an effective solution, extending the operating range over different timeframes. This paper analyzes the benefits of Li-ion battery–supercapacitor hybrid ESS integration into a grid-connected WEC, aiming at smoothing the produced power oscillations. The hybridization concept involves coupling a power-intensive technology, such as a supercapacitor devoted to managing fluctuations at higher frequency, with a battery technology exploited to manage power variations over longer timeframes to mitigate degradation issues. In this study, a multi-objective data-driven power management strategy, based on the simultaneous perturbation stochastic approximation (SPSA) algorithm, is implemented to minimize power fluctuations in terms of power ramp (representing the power variation between two consecutive values with a 1 s time step), both at the Point of Common Coupling (PCC) and the Li-ion battery terminals, thanks to the supercapacitor peak-shaving function. The SPSA management strategy, together with a suitable sizing procedure, allows a reduction of more than 70% in the power oscillations at the PCC with respect to those at the WEC terminals, while decreasing battery stress by more than 25% if compared to a non-hybrid ESS consisting of a Li-ion battery. This shows how supercapacitor features can extend battery lifespan when integrated in a hybrid ESS. [ABSTRACT FROM AUTHOR]

This paper proposes a methodological way to compensate for the imbalance between energy generation and consumption using a battery block from electric vehicles as an energy reservoir through the well-known vehicle-to-grid system (V2G). This method is based on a simulation process developed by the authors that takes into consideration the daily fluctuations in energy consumption as well as the power level generated by an energy source, either conventional, renewable, or hybrid. This study shows that for very large electric vehicle fleets, the system is rendered non-viable, since the remaining energy in the battery block that allows the electric vehicle to be usable during the daytime avoids having to compensate for the energy grid imbalance, only allowing it to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. This method allows for predicting the optimum size of an electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance, and size of the electric vehicle fleet. [ABSTRACT FROM AUTHOR]

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This paper proposes an Energy Management System (EMS) of an off-grid residential microgrid comprised of a solar photovoltaic array, wind turbine, and a battery-based energy storage system for a residential building in a remote area. The aim is to design a less complex energy management system that addresses energy resources dispatch challenge in a hybrid residential microgrid. It equitably dispatches resources and manages the generated energy to meet the residential load. The management control system algorithm is implemented using the state machine and simulated in MATLAB/Simulink environment for validation. Three scenarios are simulated, they emulate various contingencies scenarios that might rise due to the intermittency nature of the renewable resources. Simulation results show that the proposed energy management system achieves its design objectives. It maintains the power supply and demand balance, through an appropriate scheduling of resources even during contingency due to the intermittence nature of the renewable resources. [ABSTRACT FROM AUTHOR]

The paper presents a Dual Active Bridge (DAB) converter operating as an interface between the LiFePo4 battery and the fuel cell/hydrogen generator. The hydrogen tank can increase the stored energy of the battery system. Among the main requirements for a converter is the need to transfer power of up to 10 kW and operate with widely changing voltages on both sides of the converter. The design of the power electronic part and passive components of the converter is deeply discussed. Next, the influence of the wide voltage range on the operation of the converter is depicted, including its impact on power losses and current values. Different topological modifications for power loss reduction are presented and experimentally verified. Finally, a simple modification of the control system, giving the possibility of increasing efficiency, is briefly presented. [ABSTRACT FROM AUTHOR]

Experimental studies were conducted to investigate the effect of varying torque loads on the temperature distribution on the surface of lithium-ion batteries (72 volts–20 Ah) in real commercial two-wheeler electric vehicles as part of our previous research. An electric vehicle engine was installed in a dyno testing laboratory and used as the main load for the battery. Ambient temperature and relative humidity were controlled using an air conditioning system. The test results are presented as surface temperature distributions on each side of the battery at various torque loads. The highest temperature on the battery's surface was found to be approximately 40 °C at a torque load of 100%. Unfortunately, the heat generated by the battery during testing could not be measured for further research. This paper presents a numerical study of battery heat generation at 100% torque load using Ansys Fluent 2020 R1©. This tool is employed to calculate the heat flux from the battery surface to the ambient air. The CFD tool was initially validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the current predictions and experimental data were observed for laminar flow regimes. Convective heat transfer between the battery surface and ambient air was simulated. The results indicate that the commonly used heat transfer correlation for vertical plates accurately predicts the heat transfer rate on the battery surface, and it was found that the heat generation rate is 1199 W/m3. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are utilized everywhere from electronic equipment, smartphones and laptops to electric vehicles; however, certain disadvantages are inherited including high-cost and low-temperature range, caused by high currents. In this paper, a compact and low-cost battery management system is presented which can measure the voltage and current for both the battery and power supply. Two NTC thermistors, 10k and 100K Ohm each, are exploited for collecting battery temperature in two different spots of the socket for direct comparison and validation while an additional sensor measures external temperature and humidity. A charging socket is provided for charging the cell through an external source with dynamic voltage output to test the battery response. Finally, an Arduino-compatible device is implemented in order to protect the battery from overcharging. This system collects parameters at a 10 s time rate and calculates precious parameters of the battery-like State of Charge (SoC), State of Health (SoH) and State of Power (SoP). Keeping the operation within a safe zone of 20–80% SoC maximizes longevity and ensures that it can provide even the maximum power to cover the load required; hence, these three parameters are considered collaborative. Afterwards, the collected data are sent over Wi-Fi on the internet application server for real-time monitoring, in an efficient, portable and low-cost setup. [ABSTRACT FROM AUTHOR]

The utilization of fuel cells (FC) in automotive technology has experienced significant growth in recent years. Fuel cell hybrid electric vehicles (FCHEVs) are powered by a combination of fuel cells, batteries, and/or ultracapacitors (UCs). By integrating power converters with these power sources, the FCHEV system can overcome the limitations of using them separately. The performance of an FCHEV is influenced by the efficiency of the power electronics converter controller, as well as the technical efficiency of the power sources. FCHEVs need intricate energy management systems (EMSs) to function effectively. Poor EMS can lead to low efficiency and accelerated fuel cell and battery degradation. The literature discusses various types of EMSs such as equivalent consumption minimization strategy, classical PI controller, fuzzy logic controller, and mutative fuzzy logic controller (MFLC). It also discusses a systematic categorization of FCHEV topologies and delves into the unique characteristics of these topologies. Furthermore, it provides an in-depth comparative study of EMSs applied in FCHEVs, encompassing rule-based, optimization-based, and advanced learning-based approaches. However, comparing different EMSs can be challenging due to the varying vehicle and system parameters, which might lead to false claims being made regarding system performance. This review aims to categorize and discuss the various topologies of FCHEVs, highlighting their pros and cons, and comparing several EMSs based on performance metrics such as state of charge (SOC) and FC deterioration. This paper seeks a deeper comprehension of the recent advancements in EMSs for FCHEVs. It offers insights that can facilitate a more comprehensive grasp of the current state of research in this field, aiding researchers in staying up to date with the latest developments. [ABSTRACT FROM AUTHOR]

This paper proposes a multiport energy management system (EMS) and its rule-based expert control strategy for a 150 kW range-extended towing vessel (RETV). The system integrates a diesel generator system, a permanent magnet synchronous motor, a lithium battery, and supercapacitors. To verify its feasibility and effectiveness, the proposed multiport EMS was modelled and tested through MATLAB/Simulink. Simulation results demonstrate that the designed multiport EMS works efficiently under the five typical operating conditions of the 150 kW RETV. In addition, two case studies were conducted and compared to investigate the impact of the battery's initial state of charge (SoC) on the system's energy efficiency. It was found that an overall 85% energy efficiency can be achieved for the RETV when the initial SoC is either 75% or 15%. The battery consistently operates within the optimal SoC range of 20% to 80%, and the supercapacitors effectively meet the instantaneous high-power demand. [ABSTRACT FROM AUTHOR]