Constant Voltage Charging Research Articles

Simulation and Optimization of a Hybrid Photovoltaic/Li-Ion Battery System

The coupling of solar cells and Li-ion batteries is an efficient method of energy storage, but solar power suffers from the disadvantages of randomness, intermittency and fluctuation, which cause the low conversion efficiency from solar energy into electric energy. In this paper, a circuit model for the coupling system with PV cells and a charge controller for a Li-ion battery is presented in the MATLAB/Simulink environment. A new three-stage charging strategy is proposed to explore the changing performance of the Li-ion battery, comprising constant-current charging, maximum power point tracker (MPPT) charging and constant-voltage charging stages, among which the MPPT charging stage can achieve the fastest maximum power point (MPP) capture and, therefore, improve battery charging efficiency. Furthermore, the charge controller can improve the lifetime of the battery through the constant-current and constant-voltage charging scheme. The simulation results indicate that the three-stage charging strategy can achieve an improvement in the maximum power tracking efficiency of 99.9%, and the average charge controller efficiency can reach 96.25%, which is higher than that of commercial chargers. This work efficiently matches PV cells and Li-ion batteries to enhance solar energy storages, and provides a new optimization idea for hybrid PV/Li-ion systems.

Multi‐objective optimization of inductive power transfer system with reconfigurable topology for misalignment tolerance

AbstractAt present, most of the analyses or studies about inductive power transfer (IPT) with constant current (CC) output and constant voltage (CV) output are carried out without considering misalignment conditions or different gaps. An IPT system satisfying battery charging demand and anti‐misalignment requirements simultaneously is infrequent. This paper proposes a multi‐objective particle swarm optimization method of IPT reconfigurable topology to realize CC and CV modes at varying resistance conditions and wide coupling ranges. The output characteristics of an inductor–capacitor–capacitor (LCC)–LCC compensation circuit have been explored, and it is found that the secondary‐side compensated capacitors have a greater impact on the output power, which can be used to improve power regulation ability accompanied by coupling varying. Eight optimization compensated parameters of the reconfigurable topology are obtained from the Pareto front to achieve the required CC and CV charging outputs. By switching the compensated capacitors, the selected parameters can make the current and voltage fluctuation less than 9.3% and 7.9%, respectively, during the coupling charging range from 0.3 to 0.22. Moreover, primary zero voltage switching operation is achieved to enable high efficiency. The simulation and the experimental verification are carried out to verify the validity of the proposed method.

A heuristic-fuzzy improved virtual synchronous generator control strategy for charging station frequency regulation

To make use of charging station (CS) frequency regulation (FR) capability to get a better FR effect, a CS virtual synchronous generator (VSG) frequency control strategy based on the heuristic-fuzzy logic controller (FLC) is proposed in this paper. First, a CS VSG control architecture with heuristic-FLC is designed. Second, considering electric vehicle (EV) users' charging demands, a CS FR capability evaluation model based on the constant current-constant voltage (CC-CV) charging process and a V2G power response model based on frequency up/down-regulation participation factor are designed. Furthermore, a heuristic-FLC optimized by genetic algorithm (GA) is designed to improve the FR effect of the VSG control strategy. Simulation results show that the proposed strategy can make full use of the CS FR capability and get a better FR effect. In addition, the V2G power response model proposed in this paper can achieve the orderly responses of EVs in a CS under different scenarios.

Classification of aged batteries based on capacity and/or resistance through machine learning models with aging features as input: A comparative study

The growing popularity of electric vehicles generates a large amount of retired lithium-ion batteries (LIBs), which, if improperly managed, can cause irreversible harm to the ecosystem. In addition to materials recovery, the topic of repurposing retired LIBs is currently receiving increasing attention. This study proposes and assesses three classification criteria—capacity, resistance, and a composite of both—to enable more effective classification of retired batteries according to various consistency requirements and real-world application purposes. Instead of the battery capacity, which is often time-consuming to acquire, multiple aging features quickly obtained from the incremental capacity analysis curves, the electrochemical impedance spectroscopy curves, and the current curves during the constant-voltage charging process are employed to classify the retired batteries under different criteria. The accuracy of the classification is tested by utilizing the features extracted from these curves as the input to four supervised machine learning (ML) models, namely CatBoost, random forest, support vector machine, and deep neural networks. A detailed comparison is made across different classification criteria, aging features, and the adopted ML models. We demonstrate that the accuracy of classification depends on the selection of features for each criterion. There is an optimal aging feature that enables the classification to reach an accuracy rate of over 95%.

Estimating Parameters of Physics-Based Battery Models – What Machine Learning Can and Cannot Do

With the widespread use of Lithium-ion (Li-ion) batteries in multiple industries, the design space for the electrochemical cells has increased drastically. Li-ion batteries’ design parameters and material properties, such as porosity, electrode thickness, active material loading, and solid phase diffusivities, typically vary substantially due to different design goals and variation in the manufacturing process. Due to the difficulty in obtaining these and other battery cell parameters, many battery management systems used to control and monitor Li-ion batteries opt for the simplified resistor-capacitor circuit-based battery cell representation over using physics-based battery models. However, if these parameters become obtainable, scientists could implement advanced battery management systems using physics-based battery models to capture precisely how the battery performs and degrades in a wide variety of applications. Multiple methods, such as genetic algorithms, statistics, and machine learning, have been attempted for the parametrization and characterization of battery cells to enable accurate battery simulations using physics-based models [1, 2]. However, there are inherent limitations to the type and number of parameters that can be estimated using these methods if only the standard battery cell cycling data is utilized for this purpose. The present work elucidates and quantifies these limitations specifically in the case of machine learning based approach and provides deeper insights into these limitations that may help develop more robust cell characterization protocols. In the present work, model parameters are varied in a continuum-level physics-based model and simulations are performed for: (1) constant current-constant voltage (CC-CV) charging and constant current discharge at different C-rates, and (2) electrochemical impedance spectroscopy (EIS) in the relevant frequency range at multiple states of charge (SOCs). The Single Particle Model (SPM) is used for performing these simulations due to its relative simplicity and small number of parameters. At first, the charge and discharge data are input as training data in a long short-term memory neural network (LSTM NN), and EIS data is input as training data in a convolutional neural network (CNN). Once trained, the machine learning (ML) model uses charge, discharge, and EIS data withheld from the original training data set to predict SPM parameters. The estimated parameters are compared with the true parameters used for SPM charge, discharge, and EIS simulations, and the error in parameter estimation is quantified. A rigorous grid convergence analysis is performed to highlight the importance of ensuring that the spatial discretization error of the model does not influence the parameter estimation accuracy. For the first error quantification, all parameters are varied concurrently to obtain the parameter estimation error that arises from a large, undetermined parameter set. Parameters are then analyzed individually and in clusters related to diffusion, kinetics, and stoichiometric limitations. Further analysis is performed on parameters that could not be estimated with sufficient accuracy, including theoretical explanations for the incurred error and the effect of this error on the internal state predictions.

(Digital Presentation) Experimental Techniques for Parameterization of a Commercial 21700 Lithium-Ion Cell for Multiscale Battery Models

Lithium-ion batteries have gained huge attention in the past few decades. Since its commercialization, a steady improvement in cost, and performance over the last 25 years has surfaced many new applications such as EV, HEV, etc., and growing popularity for military and aerospace applications [1, 2]. However, developing a safer, longer life, high energy, power-dense, and cheaper Lithium-ion battery requires a concerted research effort from various disciplines. For a long time, research was focused on developing the chemistry, but in the recent past, the improvement in the battery performance has been realized by reengineering the manufacturing processes and model innovation that help to understand the battery performance during the charging-discharging process. Battery models employed to optimize and predict battery performance are useful tools to design and manage batteries to ensure safe and efficient utilization. To understand the underlying physical, chemical, and electrochemical properties and precisely capture the cell dynamics in EVs application, the model should be based on fundamental governing equations of diffusion and migration processes as well as the kinetics of species intercalation.The physicochemical model requires precisely evaluated model parameters for the materials under consideration. Accurately measured kinetics and transport parameters will hold the key to deriving reliable conclusions about the internal state of a Lithium-ion battery. Parameter’s quantification is a challenging and time-consuming process that requires a range of characterization and analytical methods as shown in Figure. The battery modelling community usually borrowed the parameters list from the literature, with their origins not essentially being traced [3]. In literature, parameterizations have been reported for both high-energy and high-power cells for a physicochemical model [4-7]. This work employed several characterization techniques to parametrize a commercial Lithium-ion cell model. Also, various analytical methods were employed to determine the geometrical, chemical, and electrode microstructure as suggested in Figure. To determine the thermodynamic, kinetics, and transport properties of the extracted electrode materials different electrochemical tests, e.g., galvanostatic intermittent titration technique (GITT), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), constant current constant voltage (CC-CV) charge and constant current (CC) discharge were employed. The parameter’s accuracy would be investigated by validating the mathematical modelling simulation results with the experimental charge-discharge curves at different currents of the commercial 21700 cell at room temperature.

An improved wireless power transmission system for micro unmanned aerial vehicles

AbstractDue to its limited load capacity, the piggybacking of wireless charging systems for micro unmanned aerial vehicles has become a challenging task in the design of micro unmanned aerial vehicles. Therefore, this paper proposes an improved lightweight design method for micro unmanned aerial vehicles to carry a wireless charging system. The improved system uses an inductor–capacitor–capacitor‐parallel (LCC‐P) topology compensation network instead of a bilateral inductor–capacitor–capacitor (LCC) topology compensation network to achieve constant current charging (CC) and constant voltage charging (CV). Then the adaptive frequency conversion control is used to realize the automatic conversion from CC charging to CV charging during the charging process. Compared with the traditional wireless charging system based on a direct current‐direct current converter (DC‐DC converter) to achieve CC charging and CV charging, this improved system reduces the total weight of the receiving end of the wireless charging system based on ensuring the charging efficiency, which meets the demand of wireless charging systems carried by micro drone aircraft. The test results of the constructed physical system coincide with the simulation design results, and the total weight of the receiving end is only 8 g, which verifies the correctness and effectiveness of the improved design scheme.

Research on topology technology of integrated battery energy storage system with reconfigurable battery and converter

In traditional battery energy storage systems (BESS), batteries are usually connected in a simple series or parallel form, and separate converters and balancing modules are typically used for energy exchange between the battery and external sources, as well as for balancing energy between batteries. This paper proposes an integrated battery energy storage system (IBESS) with reconfigurable batteries and DC/DC converters, resulting in a more compact structure. The IBESS can reconfigure the connection of energy storage batteries based on the battery's status and external demand. The DC/DC converters can operate in different modes such as boost, buck, or buck-boost converters. The IBESS has five working modes: discharging mode, balancing mode, battery discharging and balancing mode, constant current and constant voltage (CCCV) charging mode and backup mode. To verify the feasibility of the proposed energy storage system, a model with four battery modules was built using MATLAB/SIMULINK, and the operation of all working modes was demonstrated. The simulation results verified the system's performance and reliability, demonstrating its flexibility and efficiency in different operating modes.

A novel correlation-based approach for combined estimation of state of charge and state of health of lithium-ion batteries

State of charge(SOC) and state of health(SOH) estimation are two critical aspects for the secure operation and echelon utilisation of lithium-ion batteries. Considering the two states are interrelated, combined estimation methods are desired in practice. However, previous machine learning-based or traditional filter-based techniques have high computational requirements or suffer from convergence issues. To this end, the combined SOC and SOH estimation method of lithium-ion batteries using the novel correlation between SOC and SOH is proposed in this study. Specifically, a correlation between the capacity ratio for constant-current charging process and constant-voltage charging process and capacity loss is established. Extended Kalman filter is adopted to track SOC values at the end of constant current charging process instead of relying on the entire charging process during online application and SOH estimation can be accomplished in only one step based on the established correlation. The results show that the proposed combined SOC and SOH estimation method enables precise SOC estimation during both charging and discharging processes and achieves reliable estimation results during battery degradation. Additionally, the proposed method offers a swift means of estimating SOH with guaranteed estimation accuracy.

A Light-Load Efficiency Improvement Technique for an Inductive Power Transfer System through a Reconfigurable Circuit

Constant voltage (CV) charging and efficiency improvement are the most basic and main targets to be achieved in inductive power transfer (IPT) systems. However, efficiency may be jeopardized as battery charging progresses, especially under a light-load condition, which accounts for most of the charging time. Traditional maximum-efficiency tracking (MET) control provides an effective solution to the above issues. However, MET control not only brings the difficulties of complicated control and increased cost/volume, but also increases the additional power losses because of the introduction of additional converters or hard-switching in dual-shift phase control. To address the above difficulty, a light-load efficiency improvement (LLEI) technique is presented in this study. Under a heavy-load condition, both the inverter and rectifier operate in conventional full-bridge mode with satisfactory efficiency. Under a light-load condition, both the rectifier and inverter are reconfigured as a voltage-doubler rectifier and half-bridge inverter, respectively, to achieve two targets: one is to keep the charging voltage roughly unchanged, and the other is to force the equivalent load resistance (ELR) approach to the optimal point to improve system power transfer efficiency. A demonstrative experimental prototype with a charging voltage of 60 V is constructed and tested to validate the LLEI method proposed in this study. The experimental results show that the proposal can ensure stable CV charging and significantly improve the system efficiency under a light-load condition over the whole charging process.

Experiment-Based Determination of Optimal Parameters in Constant Temperature–Constant Voltage Charging Technique for Lithium-Ion Batteries Using Taguchi Method

Charging methods significantly affect the performance and lifespan of lithium-ion batteries. Investigating charging techniques is crucial for optimizing the charging time, charging efficiency, and cycle life of the battery cells. This study introduces a real-time charging monitoring platform based on LabVIEW, enabling observation of battery parameters such as voltage, current, and temperature. The proposed system allows the precise control of charging parameters via a user-friendly interface. Utilizing a programmable DC power supply, it delivers specific charging waveforms, while data acquisition instruments record temperature changes. Key performance metrics, including charging time, efficiency, and temperature rise, are analyzed. Moreover, this paper conducts in-depth research on the constant temperature–constant voltage (CT-CV) charging technique and applies the Taguchi method to identify key parameter configurations that achieve the objectives of the shortest charging time, highest charging efficiency, and lowest average temperature rise. A comprehensive evaluation compares the optimized CT-CV method with conventional constant current–constant voltage (CC-CV) charging. The results demonstrate a 10.7% reduction in charging time compared to the 1C CC-CV method, indicating the efficacy of CT-CV in shortening charging duration while managing temperature rise.

Hybrid Topology with Reconfigurable Rectifier for Enable CC and CV Output Characteristics in Wireless Power Transfer Systems

To achieve simple and reliable conversion from constant current (CC) charging mode to constant voltage (CV) charging mode in wireless power transfer systems, this paper proposes a hybrid topology equipped with a reconfigurable rectifier. An AC switch is adapted to simultaneously realize the change from half-bridge rectification to full-bridge rectification and achieve the shift from a topology with capacitors in the series compensated primary and secondary sides to a topology with capacitors in the series compensated primary side and the inductor-capacitor-inductor (LCL) compensated secondary side. Notably, communication between the transmitter and receiver sides is not necessary in the proposed method. Furthermore, the zero phase angle characteristic is successfully maintained in both charging modes. The experimental results obtained using the 48 V/0.7 A experimental prototype, which was built to validate the relevant theoretical analysis, show that output current/voltage can be achieved in CC/CV charging mode independent of load resistance. Notably, the maximum power transfer efficiency of the system during the charging process reached 95.33%.

Design and Control Strategy of an Integrated Floating Photovoltaic Energy Storage System

Floating photovoltaic (FPV) power generation technology has gained widespread attention due to its advantages, which include the lack of the need to occupy land resources, low risk of power limitations, high power generation efficiency, reduced water evaporation, and the conservation of water resources. However, FPV systems also face challenges, such as a significant impact from aquatic environments on the system’s stability and safety and high operational and maintenance costs, leading to large fluctuations in the grid-connected power output. Therefore, it is necessary to integrate energy storage devices with FPV systems to form an integrated floating photovoltaic energy storage system that facilitates the secure supply of power. This study investigates the theoretical and practical issues of integrated floating photovoltaic energy storage systems. A novel integrated floating photovoltaic energy storage system was designed with a photovoltaic power generation capacity of 14 kW and an energy storage capacity of 18.8 kW/100 kWh. The control methods for photovoltaic cells and energy storage batteries were analyzed. The coordinated control of photovoltaic cells was achieved through MPPT control and improved droop control, while the coordinated control of energy storage batteries involved a droop charge–discharge mode, a constant-voltage charging mode, and a standby mode. The simulations were realized in MATLAB/Simulink and the results validated the effectiveness of the coordinated control strategy proposed in this study. The strategy achieved operational stability and efficiency of the integrated photovoltaic energy storage system.

Suppression of Initial Charging Torque for Electric Drive-Reconfigured On-Board Charger

This paper presents a new electric drive-reconfigured on-board charger and initial electromagnetic torque suppression method. This proposed reconfigured on-board charger does not need many components added to the original electric drive system: only a connector is needed, which is easy to add. Specifically, the inverter for propulsion is reconfigured as a buck chopper and a conduction path to match the reconfigured windings. Two of the machine phase windings serve as inductors, while the third phase winding is reutilized as a common-mode inductor. In addition, the initial charging torque is generated at the outset of the charging process, which may cause an instant shock or even rotational movement. In order to prevent vehicle movement, the reason for the charging torque and suppression method were analyzed. Further, predictive control of the model based on mutual inductance analysis was adopted, where the charging torque was directly used as a control object in the cost function. Finally, experimental performances were applied to verify the proposed reconfigured on-board charger under constant current and constant voltage charging.

Design and development of an LC compensated WPT system with multiple constant voltage outputs function

SummaryWith the increasing demand for the constant voltage (CV) charging of multiple loads, this article proposes an LC compensated wireless power transfer (WPT) system with multiple load‐independent CV outputs function. Each transmission channel consists of a compensation capacitor and a compensation inductor forming a resonant loop. By configuring different combinations of compensation inductor and capacitor for each transmission channel, different CV outputs can be achieved without affecting the output voltages of other transmission channels. In addition, the proposed system can achieve near zero phase angle (ZPA) and zero‐voltage switching (ZVS) operations, thereby improving system efficiency. Firstly, a detailed theoretical derivation of the proposed system with multiple load‐independent CV outputs and ZPA operation is performed, and the detailed parameter design process is provided. Secondly, the implementation method of ZVS operation is introduced and verified through simulation. Finally, an experimental prototype of two transmission channels is taken as an example to verify the correctness and rationality of the proposed system.

Self-Switching Wireless Power Transfer System Design with Constant Current/Constant Voltage Output Features Based on LCC-LCL/S Topology

To meet the demand for constant current and constant voltage charging of batteries and to increase the system output power, the LCC-LCL/S-type self-switching wireless power transfer system is proposed. The system does not require communication between the primary and secondary circuits, and its output mode is controlled by simply changing the status of two switches on the secondary side. Notably, the system satisfies the zero phase angle characteristic before and after mode switching. The parameter design method is proposed based on the circuit topology and the maximum safe current constraint. To make the output voltage fluctuation as small as possible, the optimum load switching point for the system has been designed, and its optimality has been validated by simulation. Furthermore, the switching control strategy is proposed, considering the effects of the system no-load and load short-circuit in real situations. Finally, an experimental platform was built to achieve the high efficiency output of the system with the maximum output voltage of 46.21 V, the maximum output power of 180 W, and the maximum efficiency of 93.4%, which verified the applicability of the proposed method.

Design and testing of a high-performance solar LED streetlight

This paper presents the development and validation of a high-performance solarpowered charging streetlight. Our controller incorporates various charging modes, including MPPT charging, constant current charging, and constant voltage charging, and the controller can automatically change the charging mode based on the battery level. The streetlight can achieve brightness adjustment through PWM adjustment. The controller turns off the streetlights once the battery voltage reaches the over-discharge protection voltage. However, turning off the streetlights inevitably results in a voltage rebound above the over-discharge protection voltage. Consequently, the streetlights enter a cycling pattern of illumination and extinguishment. We have addressed this issue by incorporating a voltage rise threshold in the controller program, effectively preventing the streetlights from cycling between illumination and extinguishment. The MCU (Micro Controller Unit) can output multiple sets of PWM waves, where each set can control the on/off state of an LED light group. Combining multiple LED groups enables the driving and control of high-power LED street lights. We designed and constructed two solar-powered LED lighting systems to demonstrate the practicality of our approach. Extensive long-term outdoor field tests validate the robust performance of our control system.

A Multimode Power Processor With Wired and Wireless Battery Charging for Electric Vehicle

The propulsion unit is the prime power module in an Electric Vehicle (EV) that keeps it moving. This module includes a propulsion motor and a power electronic interface that converts DC to three phase AC for driving the motor. In addition to this, separate power electronic modules are used for on-board wired charging and wireless charging. This paper proposes a multimode power processor for EV capable of serving the purpose of three different power modules required for propulsion, wired charging and wireless charging. This optimizes the weight, volume, and cost of the EV as separate power modules are avoided for three different modes. This paper also proposes a new scheme for the transmitting side power electronic module that taps power from the single-phase utility grid and generates high frequency AC using a resonant inverter for wireless power transfer. In both the wired and wireless charging method, the proposed technique draws power from the single-phase wall outlet, charges the EV battery pack with constant current-constant voltage (CC-CV) charging logic and performs power factor correction operation at the input AC grid side. A laboratory scale prototype is developed for experimentally validating the proposed concept with a 24 V, 30 Ah battery set and a 24 V, 400 W BLDC motor.

Control of Li-ion transport through a combination of conductive coating and charging protocol for a stable and extremely fast charging cathode

This study demonstrates the importance of controlling Li-ion transport through a combination of conductive coating and charging protocol to achieve a stable and extremely fast charging cathode. In this research, the LiFePO4 (LFP) material coated with carbon (C) and Li1.3Al0.3Ti1.7(PO4)3 (LATP) solid electrolyte exhibits superior performance to the conventional carbon-coated LFP (LFP@C), especially at high current rates, demonstrating the possibility of developing an extremely fast charging cathode for practical applications. Our systematic experimental results reveal that the LATP coating effectively regulates the surface reactions, prolongs the voltage plateaus, and contributes additional capacity to the olivine LFP cathode material. To take advantage of the coating, a charging protocol consisting of multi-step constant current (MCC) charging combined with constant voltage (CV) charging has been proposed. During MCC charging, the current gradually increases to initiate Li-ion transport on the particle surface before accelerating charging in a short time. Under the proposed charging protocol, the LFP@C_LATP can stably deliver an average charge capacity of 161.7 mAh g−1 within 10 min for 100 cycles. This research also demonstrates the advantage of incorporating a Li-ion conductor into the electrode for the development of an extremely fast charging electrode.

Ratiometric Fluorescence Optical Fiber Enabling Operando Temperature Monitoring in Pouch-Type Battery.

Thermal characteristics are essential for improving the performance and monitoring the status of Li-ion batteries (LIBs). However, it is a challenge to design efficient and facile sensing materials for the detection of the in situ temperature of a working LIB. Herein, a ratiometric fluorescence optical fiber is developed and real-time temperature monitoring is performed with a measurement accuracy of 0.12°C, and the feasibility based on this polymer optical fiber composed of NaLaTi2O6:Yb/Er phosphors is verified in a pouch-type battery. During the charging and discharging cycles, the in situ temperature is instantaneously conveyed, revealing the internal situation of LIBs. This article further dwells on the thermal characteristics in constant current (CC)/constant voltage charging and CC discharging processes at different C-rates and the battery failure when operated at low temperatures (0°C). This work demonstrates an innovative strategy for operando solitary temperature monitoring conducted by ratiometric fluorescence optical fiber.