Battery Charge Cycle Research Articles

Effect of Battery Level During Successive Charging Cycles on the Performance of Certified and Low-cost Uncertified Light-curing Units Available on E-commerce.

To evaluate the influence of battery level on power (mW), emission spectrum (mW/cm2/ nm), and light distribution on the active tip (mW/ cm2) of certified (FDA/ANVISA) and low-cost uncertified light-curing units (LCUs) purchased through e-commerce. Seven LCUs, three certified: VALO Grand (Ultradent); Radii Xpert (SDI); and LED.B (Woodpecker); and four uncertified: 1 Sec; BS 300; LED curing light; and VAFU (VRN, AZDENT), were used. The LCUs were evaluated by calculating the power (mW) after each sequential five exposure cycles of 20 seconds and the emission spectrum (mW/cm2/nm) in the initial and final cycles, using an integrating sphere during three battery charging cycles. Beam profiling was used to check the light distribution on the LCU tip after every 50 exposure cycles until the battery fully discharged. Data were analyzed by linear regression between power and the number of exposure times (R2). The certified LCUs VALO Grand (R2=0.005), LED.B (R2=0.02), and Radii Xpert (R2=0.09) and the uncertified LCU VAFU (R2=0.002) had no significant power reduction during the three battery charging cycles. The uncertified LCUs BS 300 (R2=0.87), 1 Sec (R2=0.60), and LED curing light (R2=0.83) showed significant power reduction, decreasing the emission spectrum (mW/cm2/nm) at the end of the battery charging cycle. The light distribution on the active tip across the level battery was modified significantly with successive exposure times. The certified LCUs (VALO Grand, Radii Xpert, and LED.B) and uncertified LCU (VAFU), maintained power, emission spectrum, and light distributions during the tested battery life cycles. Low-cost certified LCU LED.B exhibited inhomogeneous light concentrated at the center of the tip. Low-cost uncertified LCUs-BS 300, 1 Sec, and LED curing light-had significant power reductions during the battery cycles and increased inhomogeneous light distribution along the successive exposure times.

Advancing sustainable mobility: Dynamic predictive modeling of charging cycles in electric vehicles using machine learning techniques and predictive application development

The main goal in this research is to train various machine learning models to predict charging cycles in EV Electric Vehicles) battery systems. The considered models are gradient boosting, random forests, decision trees, and linear regression. Each of these was assessed based on its R-squared score, which is an important statistical measure in indicating the variance proportion yielded by the model. In contrast, the Random Forest model significantly improved, with an R-squared value of 0.83, thereby doing an excellent job in capturing nuances of the data. Only surpassed by the Gradient Boosting model at an astonishing R-squared score of 0.87, it is this excellent score that underlines its capability to predict the outcome quite accurately by modeling complex interrelations. In other words, gradient boosting outran the rest and provided the most robust results concerning drivers of students' performance. It also underlines how important choosing a good model is in educational analytics in order to increase the accuracy of the predictions. The use of these models in the proposed EV Battery Charging Cycle Predictor App results in accurate predictions to aid schedule maintenance and energy-related decisions. This research brings light to the future of advanced machine learning methods in enhancing the battery efficiencies of EVs and the development of electric mobility technologies. It is possible that the future work will imply the additional inclusion of real data and the integration of the application to general energy systems.

Inductive Power Transfer Based on Variable Compensation Capacitance to Achieve an EV Charging Profile With Constant Optimum Load

Wireless charging must be highly efficient throughout the entire battery charging profile to compete in the electric vehicle (EV) industry. Thus, optimum load matching is commonly used: it operates at the equivalent load that maximizes the efficiency, which depends on the coil’s alignment. In this article, the optimum load is made independent of the coils’ position by changing the system’s resonant frequency through switch-controlled capacitors (SCCs). This eliminates the need for load-side voltage control. The output current follows the battery voltage rise during the battery charging cycle to always match the optimum load, which can be achieved by regulating the input voltage via the power factor correction (PFC) converter. This method is called here constant optimum load (COL). Two SCC topologies have been implemented in a 3.7-kW hardware demonstrator. The one implementing the half-wave modulation achieves higher efficiency than the one employing full-wave modulation, with 96.30% at 3.2 kW and aligned coils. When misalignment occurs, the half-wave modulation technique results in higher efficiency than the conventional-fixed compensation, where the efficiency is lower by up to 0.68% at partial load. Based on these results, the proposed COL method is proven suitable for 3.7-kW EV-static wireless charging achieving one of the highest peak efficiencies listed in today’s literature for the same power class.

An Optimized Plane-Change Solution for Microsatellite Formation Flying

The cross-track baseline requirement in a satellite formation flying mission requires an orbital plane-change maneuver during the acquisition phase. While the optimization of orbital plane-change maneuver has been well studied, the constraints of the propulsion system, such as the power limitation, battery charging cycle, and finite thrust durations, are often neglected. In addition, the self-pressurized chemical propulsion system used in this satellite mission experiences a performance degradation effect over prolonged use in terms of specific impulse and thrust force. To overcome these constraints on the orbital plane-change maneuver process, this article proposes an optimized algorithm by minimizing Edelbaum’s equation using a selective constrained ensemble Kalman filter that includes propulsion’s performance variation and firing duration constraints. Monte Carlo simulations have been conducted to benchmark the proposed method against the theoretical impulsive thrusts in terms of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta V$ </tex-math></inline-formula> , and the commonly adopted natural precession-based plane-change method in terms of the total time taken. Results from the simulation have shown that the required <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta V$ </tex-math></inline-formula> of this proposed method is similar to the theoretical impulsive burn method. In addition, it requires a 75% shorter time than the natural precession method in achieving the desired plane change and is 36% more fuel efficient than the direct firing method. Furthermore, this study has verified that this algorithm can be directly integrated with the existing formation control algorithm.

(Invited) Electro-Chemo-Mechanics at Solid Electrolyte-Cathode Interfaces

Strain is present at interfaces of solid electrolytes with cathode and anode in solid state batteries due to interfacial reactions and due to volumetric expansion and contraction of the electrodes during battery charge and discharge cycles. In this talk, first, I will present our findings on how a solid electrolyte-cathode interface degrades chemically and electrochemically, and its implications on the interface mechanical degradation. In particular, we have studied the garnet type Li7La3Zr2O12 (LLZO) solid electrolyte with thin film LiNi0.6Mn0.2Co0.2O2 (NMC622) cathode as a model system to enable interface sensitivity. X-ray absorption spectroscopy, X-ray diffraction and Gibbs free energy analysis have enabled us to identify the chemical and electrochemical degradation pathways, and their implication on the mechanical instability at the interface. Second, is the reverse effect of such mechanical evolution, in particular the effect of elastic strain at the interface on Li-ion diffusion in the solid electrolyte. For this question, we have taken a model solid electrolyte, β-Li3PS4, and have performed Ab Initio Molecular Dynamics (AIMD) simulations to resolve the resulting changes in Li site stability and Li ion conductivity under different strain tensors. We have found that the strain tensors which compress the c-axis (+2% ab, –2% ac, –2% bc, –2% isotropic) increase the Li-ion diffusivity, and the strain tensors which stretch the c-axis (–2% ab, +2% ac, +2% bc, +2% isotropic) reduce it. The c-axis compression increases disorder in the lattice and promote jumps along all migration pathways. The results show that elastic strain can promote Li disorder and superionic conductivity, with an effect on Li-ion diffusion comparable to that of chemical doping, and is important to consider for accurate understanding and prediction of solid-state Li-ion battery interface properties.

Thruway Sustainable Electric Vehicles Charging

A significant obstacle in execution is the restricted scope of EVs. Primarily EVs need an enormous battery ability to build the scope of the EV. One of the preparations is to charge the vehicles while moving referred to as "Dynamic Wireless Power Transfer (DWPT)". Charging the auto-mobile while shifting can decrease the battery energy capability restriction on the auto-mobile. To tackle the difficulty of the electrical vehicle (EV) charging sum vacillation added approximately using the form of charge in the course of moving charging, we propose an EV dynamic faraway charging control approach adjusting to speed alternate. The fundamental elements of dynamic charging are to send power by an electromagnetic field across a given space. As electric vehicles are a superior choice to control the continuous contamination, it is fundamental to make changes in the battery charging cycle to achieve more prominent dependability. Dynamic charging framework can be executed to charge the vehicle in any event, when it is moving. By utilizing inductive power or dynamic wireless charging, the power from source can be moved to the chargeable batteries through transformer windings, i.e., wireless transmission coils. For pre-arranged courses, such powerful charging stations can be set in the mood for charging batteries. This will not just expand the utilization of electric vehicles yet in addition make them productive and dependable for huge distances also. The paper extraordinarily presents an assessment on how the future EV improvement and remote charging techniques can be carried out. Dynamic remote charging of electric cars (EVs) is becoming a preferred method since it empowers energy change between the auto-mobile and the lattice while the car is shifting. Here we gift Mobile Energy Disseminators (MED), every other concept, which can paintings with EVs to increase their reach in a mean metropolitan situation.

Dendrite formation in rechargeable lithium-metal batteries: Phase-field modeling using open-source finite element library

We describe a phase-field model for the electrodeposition process that forms dendrites within metal-anode batteries. We derive the free energy functional model, arriving at a system of partial differential equations that describe the evolution of a phase field, the lithium-ion concentration, and an electric potential. We formulate, discretize, and solve the set of partial differential equations describing the coupled electrochemical interactions during a battery charge cycle using an open-source finite element library. The open-source library allows us to use parallel solvers and time-marching adaptivity. We describe two- and three-dimensional simulations; these simulations agree with experimentally-observed dendrite growth rates and morphologies reported in the literature.

Phase-field modeling of planar interface electrodeposition in lithium-metal batteries

This paper presents a detailed description of phase-field models of electrodeposition in lithium-anode batteries, along with underlying assumptions and parameters commonly employed. We simulate the coupled electrochemical interactions during a battery charge cycle using finite elements on open-source packages, allowing for parallel computation and time step adaptivity. We compare conventional free energy and grand canonical formulations. We obtain agreement between 1D phase-field simulations and the theoretical Faradic reaction kinetics. We study the mesh-induced errors through spatial convergence analysis. These simulations results set the groundwork for 2D and 3D simulations of dendritic metal electrodeposition in batteries.

Footprint Reduction of Sensor Control Modules for Remote Portable Laboratories.

Following the automation of monitoring systems for pollution levels in cities or protected nature reserves, there comes a need to increase the autonomy of robotic vectors deployed in the field. Thus, it is important to consider the weight that these robots must hold in order to be able to carry out a comprehensive analysis of the environment. A balance must be struck in the size, weight, and complexity of the mobile laboratories used for measurement and the autonomy of robots, especially given that current technology does not allow, in most cases, a completely autonomous battery charging cycle. Thus, in this paper, we consider a microcontroller-based architecture for a mobile laboratory control system that will be used for installation on both an aerial and an aquatic mobile vector. We found that such a system can be repurposed for several sensor types and configurations, thus being able to massively reduce the space allocated when compared to embedded widespread products.

Recent Progress in Layered Manganese and Vanadium Oxide Cathodes for Zn‐Ion Batteries

Aqueous zinc‐ion batteries (AZIBs) are promising candidates for grid‐scale energy‐storage systems, which are essential for maintaining and distributing energy generated from various sources. In contrast to current commercial lithium‐ion batteries (LIBs), AZIBs offer advantages such as, but not limited to, high safety, low cost, and fast kinetics. Zn intercalation material serves as the key element for the suitability of Zn‐ion batteries (ZIBs) for grid and stationary applications. Different materials are tested as cathode materials for ZIBs, including manganese oxides and vanadium oxides. MnO2‐ and V2O5‐based cathodes, in particular, seem compatible with ZIBs, with the potential to perform better than existing batteries in the market. Due to the fast and facile (de)intercalation‐type storage mechanism of Zn2+ ions, layered electrode materials generally have a more stable structure during battery charge and discharge cycles. Materials with large interlayer spacing are expected to exhibit good electrochemical performance, thereby favoring hydrated and cation‐intercalated materials in the development of AZIBs cathodes. Herein, an overview is provided on the synthesis, morphology, and electrochemical performance of various MnO2‐ and V2O5‐based cathode materials in AZIB, as well as the challenges that must be overcome to reach the commercialization of AZIBs.

Power conditioning unit with independent extreme power control for two sections of small spacecraft solar arrays

the article analyzes the main approaches applied in the development process of power conditioning unit (PCU) model to ensure the efficient power use of non-orientable solar arrays for small satellites operated in low Earth orbits with altitudes ranging from 300 to 1500 km. Particular attention is paid to the description of PCU structure choice, as well as the way to achieve the technical specification goals, such as efficiency factor and specific power. A conclusion is made that the optimal structure to ensure PCU efficiency and reliability is the one with a series regulator and section-by-section solar array power extreme control. It is noted that this structure will make it possible to receive power from solar array sections regardless of the difference in temperature and illumination between them. Based on the quantity and duration analysis of the solar battery charge and discharge cycles, the charge and discharge modes of the batteries are defined as basic ones, so the efficiency factor in these modes is maximized. The results of the study described in the article can be used by enterprises specialized in developing small satellites and power conditioning units as a stepping stone for developing a PCU flight model to ensure the efficient power use of non-orientable solar arrays for small satellites.

A Buck-Boost Transformerless DC–DC Converter Based on IGBT Modules for Fast Charge of Electric Vehicles

A transformer-less Buck-Boost direct current–direct current (DC–DC) converter in use for the fast charge of electric vehicles, based on powerful high-voltage isolated gate bipolar transistor (IGBT) modules is analyzed, designed and experimentally verified. The main advantages of this topology are: simple structure on the converter’s power stage; a wide range of the output voltage, capable of supporting contemporary vehicles’ on-board battery packs; efficiency; and power density accepted to be high enough for such a class of hard-switched converters. A precise estimation of the loss, dissipated in the converter’s basic modes of operation Buck, Boost, and Buck-Boost is presented. The analysis shows an approach of loss minimization, based on switching frequency reduction during the Buck-Boost operation mode. Such a technique guarantees stable thermal characteristics during the entire operation, i.e., battery charge cycle. As the Buck-Boost mode takes place when Buck and Boost modes cannot support the output voltage, operating as a combination of them, it can be considered as critically dependent on the characteristics of the semiconductors. With this, the necessary duty cycle and voltage range, determined with respect to the input-output voltages and power losses, require an additional study to be conducted. Additionally, the tolerance of the applied switching frequencies for the most versatile silicon-based powerful IGBT modules is analyzed and experimentally verified. Finally, several important characteristics, such as transients during switch-on and switch-off, IGBTs’ voltage tails, critical duty cycles, etc., are depicted experimentally with oscillograms, obtained by an experimental model.

Optimal sizing of grid-connected photovoltaic battery systems for residential houses in Australia

This paper presents optimal sizing algorithms of grid-connected photovoltaic-battery system for residential houses. The objective is to minimize the total annual cost of electricity. The proposed methodology is based on a genetic algorithm involving a time series simulation of the entire system and is validated using data collected through one year. Genetic algorithm jointly optimises the sizes of the photovoltaic and the battery systems by adjusting the battery charge and discharge cycles according to the availability of solar resource and a time-of-use tariff structure for electricity. Houses without pre-existing solar systems are considered. The results show that jointly optimizing the sizing of battery and photovoltaic systems can significantly reduce electricity imports and the cost of electricity for the household. However, the optimal capacity of such photovoltaic battery varies strongly with the electricity consumption profile of the household, and is also affected by electricity and battery prices. Besides individual PV generation and battery storage for each house, this paper also investigates group battery optimizations for communities with different consumption levels or with different energy demand diversity to see their effects on optimal sizing and peak demands for aggregated PV-battery system.

Battery Charging Profile-Based Parameter Design of a 6.78-MHz Class $E^2$ Wireless Charging System

Wireless power transfer (WPT) working at several megahertz (MHz), 6.78 or 13.56 MHz, is widely considered to be a promising candidate for charging electronic devices. The so-called Class $E^2$ converters combining the soft-switching-based Class $E$ power amplifier (PA) and Class $E$ rectifier are known to be suitable for high-frequency applications with improved efficiency. However, the charging of batteries usually need to follow a specific profile, in which battery voltage and charging current vary over time. The input reactance of the Class $E$ rectifier also becomes obvious at megahertz. This nonneglectable and varying reactance significantly lowers system efficiency and complicates parameter design. In this paper, a systematic design approach is developed that minimizes the energy loss of a 6.78-MHz Class $E^2$ wireless charging system during the entire battery charging cycle. A $LC$ matching network is added to improve the loading conditions of the Class $E$ PA and coupling coils, and provides new degrees of freedom in the parameter design. Average power loss is defined based on analytically derived system efficiency and a discretized battery charging profile. It serves as an objective function that is minimized through the proposed battery charging profile-based parameter design. In final experiments, the proposed design achieves a 24.5% reduction of the average power loss when comparing with that through the conventional design.

A method of computer modelling the lithium-ion batteries aging process based on the experimental characteristics

The paper presents a method of modelling the processes of aging lithium-ion batteries, its implementation as a computer application and results for battery state estimation. Authors use previously developed behavioural battery model, which was built using battery operating characteristics obtained from the experiment. This model was implemented in the form of a computer program using a database to store battery characteristics. Batteries aging process is a new extended functionality of the model. Algorithm of computer simulation uses a real measurements of battery capacity as a function of the battery charge and discharge cycles number. Simulation allows to take into account the incomplete cycles of charge or discharge battery, which are characteristic for transport powered by electricity. The developed model was used to simulate the battery state estimation for different load profiles, obtained by measuring the movement of the selected means of transport.

Open-circuit voltage-based state of charge estimation of lithium-ion power battery by combining controlled auto-regressive and moving average modeling with feedforward-feedback compensation method

Being one of the important parameters describing the state of power battery, state of charge (SOC) is essential for the electric vehicle battery management system (BMS). SOC estimation method, which combines the constructed controlled auto-regressive and moving average (CARMA) model with the feedforward-feedback compensation method used for revising SOC by the deviation of terminal voltage, is presented in this paper. Fully taken into account the measurement errors of voltage and current, the CARMA model is employed to estimate the battery open-circuit voltage (OCV). With the good consistency of the OCV-SOC curve under the process of battery charge and discharge cycles within a certain temperature range, OCV is adopted to estimate SOC. BP neural network rather than the high order polynomial approximation is used to capture the strong nonlinear relationship between OCV and SOC with the high precision. It is a big challenge for OCV-based SOC estimation that the flat area of OCV-SOC curve for lithium-ion power battery enlarges the measurement errors of OCV. By analyzing the flat characteristic of ΔSOC-OCV curve, the feedforward-feedback compensation for SOC is used for improving the accuracy of OCV-based SOC estimation. Experiment results confirm the effectiveness of the proposed approach that has evidently advantages over other estimation methods.

Interval quadratic programming for day-ahead dispatch of uncertain predicted demand

In this paper, we propose an interval quadratic programming method for the day-ahead scheduling of power generation and battery charge cycles, where the prediction uncertainty of power consumption and photovoltaic power generation is described as a parameter vector lying in an interval box. The interval quadratic programming is formulated as the problem of finding the tightest box, i.e., interval hull, that encloses the image of a function of the minimizer in parametric quadratic programming. To solve this problem in a computationally efficient manner, we take a novel approach based on a monotonicity analysis of the minimizer in the parametric quadratic programming. In particular, giving a tractable parameterization of the minimizer on the basis of the Karush–Kuhn–Tucker condition, we show that the monotonicity analysis with respect to the parameter vector can be relaxed to the sign pattern analysis of an oblique projection matrix. The monotonicity of the minimizer is found to be essential in the day-ahead dispatch problem, where uncertain predicted demand, described by a parameter vector, is dispatched to power generation and battery charge cycles while the economic cost is minimized. Finally, we verify the efficiency of the proposed method numerically, using experimental and predicted data for power consumption and photovoltaic power generation.

Spatiotemporally Multiresolutional Optimization Toward Supply-Demand-Storage Balancing Under PV Prediction Uncertainty

Large-scale penetration of photovoltaic (PV) power generators and storage batteries is expected in recently constructed power systems. For the realization of smart energy management, we need to make an appropriate day-ahead schedule of power generation and battery charge cycles based on the prediction of demand and PV power generation, which inevitably involves nontrivial prediction errors. With this background, a novel framework is proposed to maintain the balance among the total amounts of power generation, demand, and battery charging power with explicit consideration of the prediction uncertainty, assuming that consumer storage batteries are not directly controllable by a supplier. The proposed framework consists of the following three steps: 1) the day-ahead scheduling of the total amount of generation power and battery charging power; 2) the day-ahead scheduling of utility energy consumption requests to individual consumers, which aim to regulate battery charging cycles on the consumer side; and 3) the incentive-based management of the entire power system on the day of interest. In this paper, we especially focus on the day-ahead scheduling problems in steps 1) and 2), and show that they can be analyzed in a manner originating from spatiotemporal aggregation. Finally, we demonstrate the validity of the proposed framework through numerical verification of the power system management.

Application of Super Capacitor in HEV Regenerative Braking System

In order to ensure superiority of fuel and improve start and stop performance of hybrid electric vehicle, battery is used in the system. Limited by vehicle's size, traditional hybrid electric vehicles can only carry a limited number of batteries, results in a relatively short running distance in one battery charge cycle. To improve energy using efficiency and increase vehicle safety, composite power based on lithium ion battery and super capacitor was proposed. Super capacitor parameter was designed according to hybrid electric vehicle regenerative braking model based on matlab simulation. Experiment also was realized based on composite power, results show that both motor and power can work well, and super capacitor can absorb the regenerative braking energy of hybrid electric vehicle greatly.

A Variable Frequency Pulse Fast Charging Technique for Li-Ion Batteries Based on Fuzzy Control

To further shorten the charging time, enhancing charging efficiency and extending battery charge cycle life, this paper presents a variable frequency pulse fast charging methods based on fuzzy control depolarization. This method uses perturbation and observation method tracking resonant frequency real-timely and then finds the maximum current corresponding to the resonant frequency to charge the battery while using fuzzy control technology to detect and eliminate polarization effects arising from the charge process to accelerate the charging speed and realize frequency-varied fast charging. Experiments showed that using the fuzzy control frequency-varied pulse charging technique improves the charging time, charging efficiency, and rising temperature of the Li-ion battery by about 6.9%, 2.4%, 17.3%, respectively, as compared with the currently used fast charging method of intermittent alternating current.