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With technological advancement, the automobile industry is undergoing a design evolution. There has been an increase in the use of electrically actuated systems; electronics-based control systems, along with an increase in average power consumption. But such increased incorporation has been one of the main causes of roadside breakdowns. However, through the help of modelling and simulation manufacturers can evaluate vehicle operation; reduce their cost while achieving a competitive advantage in the automotive market. Here an automotive electrical system has been discussed. Its architecture consists of a battery, alternator, starter solenoid, and starter motor. Detailed modelling and simulation based on Simulink have been developed. Here charge level of automobile battery and its effect on the operational characteristics of an automobile has been considered and simulated in a MATLAB Simulink environment. First, a time-domain analysis has been made of the current response recorded from its maximum, minimum value, and slope characteristics. The response characteristics hence obtained are also analysed in the frequency domain through FFT analysis to obtain data characteristics in the frequency domain. A detailed analysis has been done at different levels of battery charge degradation to obtain a continuous data set for different states. The result shows significant changes both in time and frequency domain displaying discrimination in terms of DC and frequency components along with relative harmonics distortions enabling battery charge monitoring from starting transients. This method of response characteristics analysis helps in easier computation and in designing a system that can help with vehicle diagnosis and quality control.

A lithium-ion battery for mobile devices obtains a desired voltage by connecting a plurality of battery cells in series. However, the variation in the voltage of each battery cell shortens the lifetime of the battery. For this reason, a battery charge equalization circuit called a battery equalizer (BE) is commonly used. Among others, an inductor-less switched-capacitor (SC) BE is one of the most promising circuits, because it enables low cost, easy control, low EMI, and IC integration. However, to the best of our knowledge, there has been no research on the effects of element variation in inductor-less SCBEs. In this paper, the effect of circuit element variation is investigated regarding the inductor-less SCBE. Specifically, we use Monte-Carlo simulations to clarify the effects of circuit element variation in an inductor-less SCBE with a CMOS cross-coupled structure. Furthermore, the feasibility of the inductor-less SCBE is confirmed by experiments on a laboratory prototype circuit.

The safety of lithium-ion batteries is closely related to the charge transfer process inside the battery. With the rapid increase in battery usage, battery safety issues have become increasingly prominent. Due to technical limitations, the current battery thermal failure management system cannot realize risk early warning. Charge transfer resistance (Rct) is a macroscopic parameter characterizing the battery transport process, which can be detected by electrochemical impedance spectroscopy (EIS). Due to the high cost of EIS test equipment and high signal-to-noise ratio requirements, it is still not applicable to electric vehicles. In addition, Rctis affected by ambient temperature and battery aging, which brings challenges to online safety diagnosis. Here we propose a method to obtain the activation energy of a battery using direct current impedance spectroscopy (DCIS), which enables the stability diagnosis of the charge transport process. DCIS is a time-domain impedance spectroscopy technique. It uses the time constant characteristic of the internal resistor–capacitor network to detect battery parameters. Activation energy is the energy barrier for lithium-ions to cross the electrode/electrolyte interface and can indicate the stability of the charge transport process. Since activation energy is a microscopic parameter, it is not affected by temperature and aging, which is beneficial for battery safety diagnosis. The experimental results show that the charge transfer process of the sample cells with a state of health (SOH) greater than 80% is stable. When the SOH is less than 80%, the activation energy drops rapidly from 0.55 eV to 0.16 eV, indicating an increased risk of thermal runaway. Since DCIS supports online detection, it provides an option for safety diagnosis of electric vehicle batteries.

A patent has been issued to Ergotron Inc. for an accurate estimation of battery charge remaining in a mobile cart. The patent describes a system that uses sensors placed in and around the cart to monitor various factors such as temperature, barometric pressure, voltage, and current. The data collected from these sensors is transmitted to a database for analysis and can be used to improve products, reduce costs, and enhance the customer's experience. The patent also discusses the use of authentication methods to provide secure access to electronically secured compartments in the cart. [Extracted from the article]

The renewable energy sources (RES) became a fundamental necessity to the majority of electric systems and also the isolated systems like the water pumping and petroleum excavators systems. The RES typically required energy storage system because of variations in the power during the day. Because of increment popular of utilising batteries, the charging and discharging procedure of battery system should have been well managed through an adaptive controlled system. In this paper, a standalone power system utilising photovoltaic, wind energy and batteries are contributed in providing the required load. The charging balance of batteries is accomplished by utilising a new hybrid genetic algorithm (GA)-based proportional integral (PI) controller with adaptive neuro-fuzzy inference system (ANFIS). This new hybrid GA-based PI with ANFIS control method is compared with the GA-based PI controller and the conventional PI controller based on Ziegler Nichols (ZN) technique. Dynamic simulations exhibit the right performance of the hybrid GA-based PI with ANFIS control for the proposed power system under study and the better performance than the GA-based PI controller and ZN-based PI controller.

Rule-based near-optimal control strategy derived from global optimization results has the best real-time performance among current online optimal control strategies of the hybrid electric vehicle. However, the battery charge sustainability based on the rule-based near-optimal control strategy is not theoretically studied in current researches, which is important for robust control in complex driving conditions. In this paper, a deviation correction strategy based on linear quadratic regulator (LQR) is proposed for a power-split hybrid electric bus in order to sustain the battery’s state of charge (SOC). The LQR controller is designed according to an equivalent circuit model based on the state feedback control. Offline simulation is carried out to verify the proposed strategy under different driving cycles. Results show that, with the proposed strategy, the SOC can converge to a predefined value at the end of the optimization horizon.

The at least one non-transitory machine-readable medium of claim 13, further comprising instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: obtain a second set of sensor data from the sensor array included in the electronic device; and recalculate the battery runtime state using the second set of sensor data. The method of claim 8, further comprising: obtaining a second set of sensor data from the sensor array included in the electronic device; and recalculating the battery runtime state using the second set of sensor data. The system of claim 3, the memory further comprising instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: obtain a second set of sensor data from the sensor array included in the electronic device; and recalculate the battery runtime state using the second set of sensor data. [Extracted from the article]

•Explored the significance of the adaptive equivalence factor in the AECMS.•Conventional AECMS has poor control on highly dynamic driving maneuvers.•Adaptive neuro-fuzzy AECMS controller performs optimal battery sustaining operation.•Proposed AECMS delivered better energy management control on real-world drive cycle.•Proposed AECMS has 2.8% and 3.3% improved the fuel economy than rule-based and fuzzy-PI.

Ionically functionalized polymers as active binders in porous electrodes of Li-ion batteries have been studied recently to improve the rate capability of thick electrodes. Li+ion depletion and the accompanying rapid drop of electric potential act as limiting factors for thick cathodes in Li-ion batteries. We show that the incorporation of lithiated additives containing covalently bound anions, including both ionomers and nanoparticle salts, can enhance the nominal voltage and utilization of Li-ion cathodes. A mathematical model is proposed to describe the influence of the lithiated ionic additives in liquid electrolyte and is implemented. The simulation results elaborate the effect of varying ion-pair dissociability for the ionic additives. A steady state ion concentration gradient is achieved for low current density, but operation at high current density results in Li+depletion in the electrolyte phase. The use of dissociable ionic additives can overcome this limitation and reduce the potential polarization across the electrolyte. Higher concentration of ionomer ligands can improve performance for poorly dissociable ionic additives. The model validation shows that the potential drop can be lessened when ion-pair dissociation is considered while ion mobility remains unchanged. The modeling technique can be extended to a whole battery cell.

In this paper, we propose a solution to the complete vehicle energy management problem with battery charge acceptance limitations and battery aging limitations. The problem is solved using distributed optimization for a case study of a hybrid heavy-duty vehicle, equipped with a refrigerated semi-trailer for two different battery models. The first battery model takes charge acceptance into account by adding an additional energy state to the optimization problem. The second battery model includes battery aging for which a novel iterative algorithm is proposed. Simulation results show that charge acceptance limitations only have a minor effect on the solution to the energy management problem, while battery aging leads to a trade-off between battery capacity loss and fuel consumption reduction. In particular, a decrease in capacity loss by 260%, leads to a drop in fuel consumption reduction from 9.40% (without battery aging) to 8.61% (with battery aging), both when compared to a conventional vehicle. This is caused by the fact that aging limitations cause less energy to be stored in the high-voltage battery. Still, because energy can also be stored in the refrigerated semi-trailer, smart control of this refrigerated semi-trailer leads to an additional fuel reduction 0.53% in the case where battery aging is incorporated, while it was only 0.09% when battery aging was not considered. In other words, the drop in the fuel consumption reduction caused by battery aging constraints can be partly compensated by smart control of other energy buffers, which shows the true benefit of complete vehicle energy management.

AbstractThis study proposes a battery charge equalization circuit with a multi-winding transformer. A full-bridge converter with soft switching is applied at the primary side of a multi-winding transformer for reducing the switching loss and increasing the system efficiency. A voltage doubler type rectifier is used at the secondary side of multi-winding transformer to decrease the number of transformer windings and the conduction loss. The important advantages of the proposed circuit include the following: The charge current is limited by the transformer leakage inductance without any choke inductor, and charge equalization is realized by adjusting the transformer’s turn ratio. A measurement index, charge equalization performance (C.E.P.), is introduced for the performance measurement of the charge equalization method. In experiments, four LiFePO4battery modules are connected in series and discharged at different C-rates. The experimental results show that the discharging time of the series-connected battery modules can be greatly increased using the proposed battery charge equalization circuit.

When the heat losses sense is adopted for some solar system and power conversion components in residential building application, it is benefit to use those losses, that are consequently acts inversely on system efficiency, as a useful energy to modify the performance of that system instead of dissipated. In terms of efficiency of solar-battery charge controller, power dissipation is always associated with every power component and the losses would be either results from switching and conducting components or from the OFF state of the main switching component. This paper proposed a high efficiency solar-battery charge controller as an alternative to the main solar charge controller in most conventional residential solar system , the concept of the proposed controller circuit based on using the off state energy duration as well as that power losses coming from the main switching component and complexity of the conventional controller, and using this energy in a separate current path to energize an auxiliary battery or directly load used to cool or even to ventilate the system components causing in improving its performance. This will leads to electronic circuit with low losses as a compared with the conventional charge controller to be a part of the integrated and automated building solar system, the design has an algorithm based on some environment parameters like sun Irradiance and weather temperature, this algorithm seems to be inversely calculated because its start from the value of full charge battery voltage. A Simulink Matlab simulator is attempted in the simulation phase of this research as well as an experimental data has been collected to verify the circuit function and energy saving goal.

Solar-powered UAV is an alternative way to achieve high endurance and long range UAV flight. However, solar irradiance is not always available during the flight. Thus, secondary power source which is electrical batteries will improve the performance of solar-powered UAV when solar irradiance is not available. Therefore, bench test for LiPo battery is conducted in this paper for the design of solar-powered UAV power system. The impact of operating temperature at various charging and discharging rate on the duration to full charge and discharge and capacity level of a single LiPo battery were assessed. The solar module installed in solar-powered UAV developed by Aircraft Design Group, Cranfield University has to be designed to charge the battery pack at a nominal or maximum rate of 0.129 C and 0.155 C correspondingly. The solar module requires roughly 5.73 hours on nominal charging rate on 30 °C operating temperature to fully charge capacity level instead of 5.54 hours theoretical predicted. The battery pack will then discharge at cruise flight roughly about 0.071 C to a maximum of 1.685 C if required. If the battery pack is not charged, during cruise flight the battery capacity will deplete completely at about 6.51 hours for the same operating temperature, in contrast to the 6.48 hours based on the theoretical prediction. In addition, the usage of LiPo batteries for operation at high altitudes and/or extreme temperatures without an additional heating or cooling system for these battery packs is not favorable. Thus, it is best to charge at low charging rate and high operating temperature to store and utilize the most capacity from this battery.

Even though thick electrodes are essential to increasing the energy density of LIBs, high current rates cause them to lose power density due to high polarization and ion depletion in the pore spaces. Mixed active binders with lithiated bound charges can improve the battery capacity and voltage at high C-rates, even compared to similar high concentrated electrolyte. The lithiated binders also provide a more uniform spatial distribution of intercalation reaction current, electric potential, and open circuit potential. The LIB half cell is modeled at mesoscale by taking into account the diffusion-reaction physics of the bound charge mixed electrolyte in active carbon-binder-domain (CBD), that accounts the dissociation of anionic ligands. Electrolyte in separator and active CBD are coupled by Donnan theory at the interface, and the reaction interfaces are modeled by the standard Butler-Volmer equation. By means of a thermodynamically consistent model and its implementation in a FEM code, we investigate the impact of particle distribution, electrode thickness, and separator thickness for both standard binder and active binder mixed cathodes in terms of ion depletion, current density, and electric potential. This mathematical model can also be extended to the modeling of ion conducting polymer electrolytes, gel polymers, and other conductive materials for battery applications.

AbstractThe use of photovoltaic (PV) generation forecasts in economic load dispatching control, which includes the unit commitment of conventional power plants, is essential to ensure the economic performance and the reliability of power systems. In the previous study, we developed a day-ahead charge and discharge scheduling method of battery energy storage systems based on interval analysis using prediction intervals of a PV generation forecast; this interval forecast considers forecast errors and gives not only the forecasted output but also the possible range of the actual output with a certain confidence. In this study, we evaluate the proposed scheduling method by numerical simulations in terms of the power system supply and demand operation.

Frequency Scaling based energy efficient MBCCS is implemented in this paper. In this design, if battery's voltage or current is less than threshold then battery will continue charging. Whereas, if voltage or current is more than threshold then it will ring Overcharge Alarm. With Frequency Scaling, we reduce frequency from 1THz to 25GHz, where 125GHz, 625GHz are intermediate frequency value. There is 97.50%, 100%, 97.54%, 97.48%, 20%, 96.48 % reduction in clock power (CP), logic power (LP), signal power (SP), IOs power (IOP), leakage power and total power dissipation respectively when we scale down frequency from 1 THz to 25GHz.

This paper gives the description of the scheme of solar energy lighting system. In the stated scheme, constant voltage tracking technology is used to complete the solar battery charging. The intelligent charging technology is used to implement over-current protection, over-voltage protection, and over-temperature protection.

The article describes a method that enables the charging of batteries using a disclosed battery charger with two wires over some distance. The method, according to a research disclosure, is capable of accurately charging batteries at low currents. The charge current could be made low, which can reduce the cost of the charger and enables other power sources such as a universal serial bus port on a computer to perform the charging function.

Electric Vehicle (EV)/Hybrid Electric Vehicle (HEV) enabled by high-efficiency electric motor and controller, provide the means for a clean, efficient and environmental friendly transportation system. Portable rechargeable batteries are the essential basic component in EVs. In EV/HEV system a large number of cells should be connected in series to supply enough energy, while the voltage balancing problem between cells leads to poor performance. This paper attempts modular battery charge equalization based on state of charge (SOC) under MATLAB Simulink environment.

In this paper, the long-term storage of lithium batteries is studied, and a lithium battery charge management memory device with charging and intelligent management functions is derived. The store has two selectable modes of operation. It not only can safely charge the lithium battery, but also can intelligently detect the lithium battery power and maintain it for a long time. It solves the problem that after the lithium battery is stored for a long time, the performance of the battery is seriously reduced due to deep discharge, and the battery life is greatly shortened.

A development of a microcontroller-based charge controller for a 12V battery has been explained in this paper. The system is designed based on a novel algorithm to couple existing solar photovoltaic (PV) charging and main grid supply charging power source. One of the main purposes of the hybrid charge controller is to supply a continuous charging power source to the battery. Furthermore, the hybrid charge controller was developed to shorten the battery charging time taken. The algorithm is programmed in an Arduino Uno R3 microcontroller that monitors the battery voltage and generates appropriate commands for the charging power source selection. The solar energy is utilized whenever the solar irradiation is high. The main grid supply will be only consumed whenever the solar irradiation is low. This system ensures continuous charging power supply and faster charging of the battery.

The article discusses the discovery of mineral reserves in Afghanistan and Bolivia such as lithium, gold and iron which can profit their export and mining industry. Prices of lithium have surged with the increased in demand of lithium batteries used for laptop computers and electric cars. While security in Afghanistan is threatened by the presence of the Taliban rebels, Bolivia is seen as the best option for investors. Bolivia's President Evo Morales, however, is also determined to develop the potential of lithium.

The article describes the structure of a charge-discharge unit which allows to perform electrical, resource and thermal testing of several lithium-ion batteries simultaneously. The principle of operation of a one battery research channel (BRC) is shown. This study evaluated the stabilization error and rate of change of charge/discharge currents, the switching time from the charge mode to the discharge mode and vice versa for a single BRC and parallel BRCs. The possibility of increasing the maximum battery testing current due to the parallel connection of multiple BRCs without using a current alignment device between channels was discussed.

Deals with the rape and extortion charges against Afro-American rapper Mystikal. Details on the charges; Sentence given to the rapper for extortion; Views of the rapper on the charges.

The article presents a method of controlling a hybrid powertrain to provide coast torque while achieving zero high voltage battery charge power. Powertrain braking must be performed when the high voltage battery cannot accept more charge. It reveals that there is an optimal torque split between the machines in a hybrid architecture with two or more machines to achieve any given axle torque.

The article focuses on an optimized energy buffer of lithium-ion battery for marine application. It examines the discharge and recharge efficiency issue, as well as the difference of coulombic efficiency and energy efficiency. It discusses how lithium-ion batteries can be prevented from damage by monitoring the discharging and recharging. INSET: Boeing and Other Fires.

The circuitry modelling of the standalone photovoltaic (PV) maximum power point tracking (MPPT) lithium-ion battery charge controller is presented in this study using the MATLAB/Simulink environment. For the charge controller implementation, a DC-DC converter called a buck topology is used. The Perturb and Observe (P&O) MPPT algorithm monitors the solar panel’s peak power. The lithium-ion battery is charged in three stages by the battery charge controller. The model’s performance is analysed in terms of MPPT tracking performance, battery charging performance, and overall charge controller efficiency performance. With an MPPT efficiency of up to 99.9%, the performance result demonstrates that the MPPT is capable of tracking to the PV panel maximum point at any variation in solar irradiation. For small and medium standalone PV systems, this verified model aids in improved sizing of PV panels and battery energy storage. Techno-economic analysis refers to the assessment of the economic viability and profitability of using this type of lighting compared to other forms of lighting. The maintenance costs and efficiency of these systems can be improved even more by adding a programmable logic controller (PLC).

Battery electric vehicles have been developing rapidly in recent years due to their advantages of energy saving and emission reduction. However, the development of battery electric vehicles is still in its infancy due to the relatively immature charging technology and the lack of infrastructure development. In many researches, there have been many solutions to adopt remote monitoring systems in battery electric vehicles to monitor and collect them in real time for statistical analysis and fault diagnosis. However, the current monitoring systems are carried out statistically and it is difficult to extract much valuable information from the data. In this paper, after analyzing the construction mode of battery electric vehicle charging facilities, the battery electric vehicle charging facility system platform using embedded system was analyzed. Several functions were simulated to meet the problems encountered by users in using it, studying the battery electric vehicle charging facility layout optimization model based on data mining algorithm. Focusing on the coverage problem in the siting problem, the State-of-Charge (SOC) of the battery charge state was analyzed. Taking residential areas as an example and 4 weeks as a cycle, it was found that during the first to fourth weeks, the negative power at 1:00, 20:00 and 24:00 was higher. At the same type of time point, different charging thresholds had a significant impact on the charging load demand of users. The larger the charging threshold of battery electric vehicles appeared, the earlier the peak moment and the higher the peak load. The battery state of the battery electric vehicle in the work area is 60 % at 1:00, and it reaches a relatively full state of 90 % at 8:00. In different regions, the allocation of charging thresholds for battery electric vehicles was different, and the Markov theory was derived from the analysis of the coverage problem to enable fast and effective siting of charging piles while satisfying charging convenience and high utilization of charging facilities to complement the research on the optimization model of battery electric vehicle charging facility layout.

With a single-switched DC-DC converter, a hybrid approach is proposed for a fast-charging (FC) dc to dc converter with the controller for an electric vehicle charging station (EVCS) that combines solar photovoltaic (PV), fuel cells (FC), and a battery energy storage system (BESS). The proposed hybrid technique integrates a radial-basis-function-neural-network (RBFNN) and a student-psychology-optimization-algorithm (SPOA); commonly known as the RBFNN-SPOA technique. The PV-FC hybrid electric vehicle systems, like controllers, electric vehicle, and the vehicle’s power source, are displayed. The proposed converter architectures have less voltage waveform changes, a low voltage stress on semiconductor power sources, and a high-voltage ratio of conversion. The proposed method is to use FC successfully at battery charge states and varied radiation levels. The FC in the controller of SPOA may change the inputs and outputs depending on the battery state of charge (SoC) and PV irradiation. Similarly, the needed input-torque for the motor is forecasted by the recalling recurrent neural network controller using several manually produced torque signals. The performance of the proposed technique is evaluated in MATLAB and is compared to ant colony optimization (ACO), crow optimization algorithm (COA), and fuzzy logic controller (FLC) approaches. According to the results, the efficiency of the proposed technique is 99.17%.

Battery Swap technology represents a promising solution to overcome the main obstacles to a widespread adoption of electric vehicles (EVs) in urban environment, like the limited range of EVs and the long battery charging time. Furthermore, with respect to traditional charging stations, it offers higher flexibility in dynamically managing the EV electricity demand to prevent the risk of power grid overload. Nevertheless, proper scheduling of the battery charge process is crucial to offer effective e-mobility services, trading off cost, Quality of Service (QoS) and feasibility constraints. We consider a renewable powered multi-socket Battery Swapping Station (BSS) and design two algorithms based on Approximate Dynamic Programming (ADP) and Reinforcement Learning (RL) to dynamically adapt the battery charging scheduling to the stochastic nature of the system. Both approaches result effective in remarkably increasing the capability to satisfy the customer demand for EV battery charging, at a lower cost with respect to benchmark approaches, with RL outperforming ADP under any budget constraint. In particular, under RL the probability of not satisfying the EV demand is decreased by up to more than 40% with respect to benchmark approaches, and cost can be significantly reduced by almost 20%, jointly with a greener system operation. Furthermore, our results show that a fine tuning of hyper-parameters is fundamental to properly trade off cost and QoS constraints according to varying business needs. Finally, we analyse how the proposed strategies may affect the battery health due to their impact on battery degradation, hence influencing the BSS management cost.

The increase in greenhouse gas emissions (GHG) from the transportation sector, along with the ongoing depletion of fossil fuels, emphasizes the necessity for increased focus on energy storage systems (ESSs) and renewable energy sources (RESs) in seaports and on short-distance vessels such as ferries. This paper investigates the development of next-generation smart ports, wherein the integration of Internet of Things (IoT) and sensors transforms ports into intelligent hubs. This transformation aims to optimize operations for all stakeholders, that leverage emerging technologies to enhance efficiency and connectivity. Notably, many smaller seaports lack shore-power facilities, shore-based power installations that supply electric power to ships from the grid. Consequently, ships often rely on continuous operation of auxiliary diesel engines and generators while at berth to meet auxiliary loads. To address these challenges and overcome economic and logistical constraints, this paper proposes a seaport microgrid (SMG) with a DC distribution that would be created by integrating multiple ships with decentralized control mechanisms supplemented by an onshore charging infrastructure. This helps to achieve a sustainable path by introducing ship-based SMGs involving the integration of shipboard microgrids with onshore charging. The proposed approach relies on adaptive droop control, decentralized power-sharing based on battery charge and reducing traditional communication dependencies. The case study supported by the simulation results shown in the paper emphasizes the potential of this strategy in the evolution of maritime infrastructure.