Experiment Study on the Ending Criteria of Charge and Discharge of Nickel-Hydride Battery

Charge and discharge characteristics of Ni/MH batteries are investigated with experiments. During battery’s working, the voltage, capacity, temperature and internal resistance were recorded, corresponding curves were depicted. Variations of the aforementioned four parameters are differently obvious. Ending criteria of charge and discharge of Ni/MH batteries are discussed on the basis of the curves. Voltage, capacity and temperature of a battery can be used as ending criteria during charge. When discharge takes place, voltage, capacity and internal resistance can be chosen as ending criteria. As a whole, capacity is more suitable for being used as ending criteria of charge and discharge than the other three parameters. At last, the capacity of a battery is recommended to be ending criteria of charge and discharge. The conclusions will provide references to different capacity Ni/MH batteries for electric vehicles.

Battery Management System with State ofCharge Indicator for Electric Vehicles

Aim To research and develop a battery management system(BMS)with the state of charge(SOC)indicator for electric vehicles (EVs).Methods On the basis of analyzing the electro-chemical characteristics of lead-acid. battery, the state of charge indicator for lead-acid battery was developed by means of an algorithm based on combination of ampere-hour, Peukert's equation and open-voltage method with the compensation of temperature,aging,self- discharging,etc..Results The BMS based on this method can attain an accurate surplus capa- city whose error is less than 5% in static experiments.It is proved by experiments that the BMS is reliable and can give the driver an accurate surplus capacity,precisely monitor the individual battery modules as the same time,even detect and warn the problems early,and so on. Conclusion A BMS can make the energy of the storage batteries used efficiently, develop the batteries cycle life,and increase the driving distance of EVs.

Application of Power Electronics and Control for Dual Battery Packs Management with Voltage Balancing and State of Charge Estimation

Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce operating costs. The battery storage system has to be monitored and managed to prevent serious problems such as battery overcharging, over-discharging, overheating, battery unbalancing, thermal runaway, and fire dangers. For voltage balancing between batteries in the pack throughout the charging period and the SOC estimate, a modified lossless switching mechanism is used in this research’s suggested battery management system. The OCV state of charge calculation, in the beginning, was used in conjunction with the coulomb counting approach to estimate the SOC. The results reveal that correlation factor K has an average value of 0.3 volts when VM ≥ 12 V and an average value of 0.825 when VM ≤ 12 V. The battery monitoring system revealed that voltage balancing was accomplished during the charging process in park one after 80 seconds with a SOC difference of 1.4% between Batteries 1 and 2. On the other hand, the system estimates the state of charge during the discharging process in two packs, with a maximum DOD of 10.8 V for all batteries. The project’s objectives were met since the BMS estimated SOC and achieved voltage balance.

A new state of charge determination method for battery management system

State of Charge (SOC) determination is an increasingly important issue in battery technology. In addition to the immediate display of the remaining battery capacity to the user, precise knowledge of SOC exerts additional control over the charging/discharging process which in turn reduces the risk of over-voltage and gassing, which degrade the chemical composition of the electrolyte and plates. This paper describes a new approach to SOC determination for the lead-acid battery management system by combining Ah-balance with an EMF estimation algorithm, which predicts the battery’s EMF value while it is under load. The EMF estimation algorithm is based on an equivalent-circuit representation of the battery, with the parameters determined from a pulse test performed on the battery and a curve-fitting algorithm by means of least-square regression. The whole battery cycle is classified into seven states where the SOC is estimated with the Ah-balance method and the proposed EMF based algorithm. Laboratory tests and results are described in detail in the paper.

Physics-based battery SOC estimation methods:Recent advances and future perspectives

The reliable prediction of state of charge(SOC)is one of the vital functions of advanced battery management system(BMS),which has great significance towards safe operation of electric vehicles.By far,the empirical model-based and data-driven-based SOC estimation methods of lithium-ion batteries have been comprehensively discussed and reviewed in various literatures.However,few reviews involving SOC estimation focused on electrochemical mechanism,which gives physical explanations to SOC and becomes most attractive candidate for advanced BMS.For this reason,this paper comprehensively surveys on physics-based SOC algorithms applied in advanced BMS.First,the research progresses of physical SOC estimation methods for lithium-ion batteries are thoroughly discussed and corresponding evaluation criteria are carefully elaborated.Second,future perspectives of the current researches on physics-based battery SOC estimation are presented.The insights stated in this paper are expected to catalyze the development and application of the physics-based advanced BMS algorithms.

Microstructures and Properties of Honeycomb Sulfur/carbon Black/MoS_(2) Composites

Microstructure and property of sulfur/carbon black composites prepared by ball milling were studied.Sulfur/carbon black composites were obtained by melting the mixture of sulfur and carbon black in 155℃and dispersing evenly in carbon black after hydrothermal reaction.Thus,its conductive properties were improved.Moreover,microstructure and property of honeycomb sulfur/carbon black/MoS_(2) prepared by hydrothermal method as a cathode material for lithium-sulfur batteries were studied.The initial discharge specific capacity of the material at 0.2 A/g current density is 838.495 mA·h/g,and the 55.14%after 100 weeks of cycling.It is indicated that MoS_(2) can not only combine with polysulfides through electrostatic action or the action of chemical bonds,but also honeycomb porous structure.MoS_(2) can fix polysulfides groups and prevent their shuttle.Therefore,the cycling performance of the battery is effectively improved.

Fractional Modeling and SOC Estimation of Lithium-ion Battery

This paper proposes a state of charge (SOC) estimator of Lithium-ion battery based on a fractional order impedance spectra model. Firstly, a battery fractional order impedance model is derived on the grounds of the characteristics of Warburg element and constant phase element (CPE) over a wide range of frequency domain. Secondly, a frequency fitting method and parameter identification algorithm based on output error are presented to identify parameters of the fractional order model of Lithium-ion battery. Finally, the fractional order Kalman filter approach is introduced to estimate the SOC of the lithium-ion battery based on the fractional order model. The simulation results show that the fractional-order model can ensure an acceptable accuracy of the SOC estimation, and the error of estimation reaches maximally up to 0.5% SOC. © 2014 Chinese Association of Automation.

Deep learning-based battery state of charge estimation:Enhancing estimation performance with unlabelled training samples

The estimation of state of charge(SOC)using deep neural networks(DNN)generally requires a considerable number of labelled samples for training,which refer to the current and voltage pieces with knowing their corresponding SOCs.However,the collection of labelled samples is costly and time-consuming.In contrast,the unlabelled training samples,which consist of the current and voltage data with unknown SOCs,are easy to obtain.In view of this,this paper proposes an improved DNN for SOC estimation by effectively using both a pool of unlabelled samples and a limited number of labelled samples.Besides the traditional supervised network,the proposed method uses an input reconstruction network to reformulate the time dependency features of the voltage and current.In this way,the developed network can extract useful information from the unlabelled samples.The proposed method is validated under different drive cycles and temperature conditions.The results reveal that the SOC estimation accuracy of the DNN trained with both labelled and unlabelled samples outperforms that of only using a limited number of labelled samples.In addition,when the dataset with reduced number of labelled samples to some extent is used to test the developed network,it is found that the proposed method performs well and is robust in producing the model outputs with the required accuracy when the unlabelled samples are involved in the model training.Furthermore,the proposed method is evaluated with different recurrent neural networks(RNNs)applied to the input reconstruction module.The results indicate that the proposed method is feasible for various RNN algorithms,and it could be flexibly applied to other conditions as required.

Empowering the Future: Exploring the Construction and Characteristics of Lithium-Ion Batteries

Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic table. The lithium atom has a strong tendency to release one electron and constitute a positive charge, as Li . Initially, lithium metal was employed as a negative electrode, which released electrons. However, it was observed that its structure changed after the repetition of charge-discharge cycles. To remedy this, the cathode mainly consisted of layer metal oxide and olive, e.g., cobalt oxide, LiFePO4, etc., along with some contents of lithium, while the anode was assembled by graphite and silicon, etc. Moreover, the electrolyte was prepared using the lithium salt in a suitable solvent to attain a greater concentration of lithium ions. Owing to the lithium ions’ role, the battery’s name was mentioned as a lithium-ion battery. Herein, the presented work describes the working and operational mechanism of the lithium-ion battery. Further, the lithium-ion batteries’ general view and future prospects have also been elaborated.

State of Health Estimation of LiFePO_(4) Batteries for Battery Management Systems

When considering the mechanism of the batteries,the capacity reduction at storage(when not in use)and cycling(during use)and increase of internal resistance is because of degradation in the chemical composition inside the batteries.To optimize battery usage,a battery management system(BMS)is used to estimate possible aging effects while different load profiles are requested from the grid.This is specifically seen in a case when the vehicle is connected to the net(online through BMS).During this process,the BMS chooses the optimized load profiles based on the least aging effects on the battery pack.The major focus of this paper is to design an algorithm/model for lithium iron phosphate(LiFePO4)batteries.The model of the batteries is based on the accelerated aging test data(data from the beginning of life till the end of life).The objective is to develop an algorithm based on the actual battery trend during the whole life of the battery.By the analysis of the test data,the complete trend of the battery aging and the factors on which the aging is depending on is identified,the aging model can then be recalibrated to avoid any differences in the production process during cell manufacturing.The validation of the model was carried out at the end by utilizing different driving profiles at different C-rates and different ambient temperatures.A Linear and non-linear model-based approach is used based on statistical data.The parameterization was carried out by dividing the data into small chunks and estimating the parameters for the individual chunks.Self-adaptive characteristic map using a lookup table was also used.The nonlinear model was chosen as the best candidate among all other approaches for longer validation of 8-month data with real driving data set.

Reduced Switching-Frequency State of Charge Balancing Strategy for Battery Integrated Modular Multilevel Converter

A modular multilevel converter(MMC)integrated with split battery cells(BIMMCs)is proposed for the battery management system(BMS)and motor drive system.In order to reduce the switching losses,the state of charge(SOC)balancing strategy with a reduced switching-frequency(RSF)is proposed in this paper.The proposed RSF algorithm not only reduces the switching losses,but also features good balancing performance both in the unbalanced and balanced initial states.The results are verified by extensive simulations in MATLAB/Simulink surroundings.

Research on the Nickel Metal Hydride Battery Quick Charger

In order to design a new type of quick charger for NiMH battery, the new method of pulse charge discharge was adopted after studying the charge process and analyzing the NiMH battery charge characteristics. The charge and discharge experiments were carried out to check feasibility and superiority of the new method. The results indicated that with the discharge pulse added the charger can charge quickly, the battery voltage and temperature can be properly controlled to prevent the battery being destroyed, and the capacity of the NiMH battery is greater than that of the battery without the discharge pulse added.

A Nonlinear Observer Approach of SOC Estimation Based on Hysteresis Model for Lithium-ion Battery

In this paper, a state of charge U+0028 SOC U+0029 estimation approach for lithium-ion battery based on equivalent circuit model and the input-to-state stability U+0028 ISS U+0029 theory has been proposed. According to the electrochemical performance of lithiumion battery, the equivalent circuit model with two RC networks is established, which includes hysteresis characteristic in inner electrochemical response process. The nonlinear relation between open circuit voltage U+0028 OCV U+0029 and SOC is obtained from a rapid test. Exponential fitting method is used to identify the parameters of the model. A novel state observer based on ISS theory is designed for lithium-ion battery SOC estimation. The designed observer is tested on AMESim and Simulink co-simulation. The simulation results show that the proposed method has a high SOC estimation accuracy with an error of about 2 percent. © 2017 Chinese Association of Automation.

An Optimal Management System of a Wind Energy Supplier

In this paper, we propose a real time approach to optimize the supplied energy of a wind station. This station is used for electric energy storage in battery bank, water pumping, lighting and heating systems. The characterization of the wind generator allows us to estimate the available electrical wind energy of the platform. A data sheet of the required energy for each load (battery charging, wind pumping system, lighting system and heating system) is drawn up. Basing on the issued data sheet we develop and implement a management system for optimal energy distribution. To improve the proposed management system, we introduce a real time data acquisition (DAQ-S) and data processing (DP-S) subsystems. The DAQ-S measures all the required electrical parameters needed by the proposed DP-S to perform an optimal algorithm activating our smart decision system to allow a rational and effective use of the electrical wind power.

An iterative computation method for interpreting and extending an analytical battery model

Battery models are of great importance to develop portable computing systems,for whether the design of low power hardware architecture or the design of battery-aware scheduling policies.In this paper,we present a physically justified iterative computing method to illustrate the discharge,recovery and charge process of Li/Li-ion batteries.The discharge and recovery processes correspond well to an existing accurate analytical battery model:R-V-W's analytical model,and thus interpret this model algorithmically.Our method can also extend R-V-W's model easily to accommodate the charge process.The work will help the system designers to grasp the characteristics of R-V-W's battery model and also,enable to predict the battery behavior in the charge process in a uniform way as the discharge process and the recovery process.Experiments are performed to show the ac-curacy of the extended model by comparing the predicted charge times with those derived from the DUALFOIL simulations.Various profiles with different combinations of battery modes were tested.The experimental results show that the extended battery model preserves high accuracy in predicting the charge behavior.

Research on Fuzzy PID Charging Control of Battery Pack

Battery groups are widely used in production and life. Optimal charging can not only shorten the charge time, but also improve the performance and life of the battery pack. A constant current or constant voltage charging method is commonly used. This type of method cannot adjust the charge capacity in time according to the change of charging capacity of storage battery, and the charge performance is not high. This paper designs a fuzzy PID controller. In the case of variable load and interference, the battery group can still be charged by the optimal charging current. Through the simulation results, the fuzzy PID controller works well and verifies the feasibility of the charging controller.

Control System Design of CSI Applied in the Battery Pack Testing System

This paper designed the loop-locked SVPWM control system of current source inverter (CSI) in the battery pack charging/discharging system. The battery pack is sensitive to the charging/discharging current ripple and orders the current posess fast transform speed. Because the battery pack has tiny inner resistance, back electromotive force and it acted as a comparative load. This made the system hard to design. The control system aimed at the specialty of the battery pack load and put forward a loop-locked control method based on dq coordinate conversion in SVPWM converters. It increases the transform efficiency by SVPWM and gets high power factor and high dynamic response quality by dq coordinate conversion.

A novel Zn-PANI dry rechargeable battery

Conducting polyaniline (PANI) powder was well mixed with graphite and acetylene black to obtain the optimum conductivity and porosity. The mixed powder was compressed into a pellet for cathode. Zinc powder was mixed with some metal powder, and compressed into a pellet used as the anode. The electrolyte comprised ZnCl2, NH4Cl, Triton-X100 and PVA at pH 3. The battery has an open-circuit voltage of 1.44 V. The battery underwent charge-discharge cycle with a constant current density of 3 mA·cm-2, within the voltage range of 0.40-1.68 V. It is found that the capacity of the battery is related to the charge-discharge cycles, the maximum capacity is 67.9 mAh·g-1, and Coulombic efficiency is between 95% and 100%. The battery stability was also investigated after 78 d of standing without use. It is found that the battery experiences a self-discharge of less than 0.29% per day.

A facile preparation of 3D flower-shaped Ni/Al-LDHs covered by β-Ni(OH)2 nanoplates as superior material for high power application

In the present study,we propose a novel electrode material ofβ-nickel hydroxide covering nickel/aluminum layered double hydroxides via a facile complexation–precipitation method.The as-obtained materials with 3-dimensional nanostructures are further utilized as highly capable electrode material in nickel–metal hydride batteries.The electrochemical test results demonstrated theβ-nickel hydroxide covering nickel/aluminum-layered double hydroxides with 28%ofβ-nickel hydroxide provided a superior specific capacity value of 452 m A·h·g-1 in a current density of 5 A·g-1 using 6 M KOH as electrolyte as compared with other materials.In addition,the optimized sample displays an outstanding cyclic stability along with a huge specific capacity value of320 m Ah·g-1,and very small decay rate of 3.3%at 50 A·g-1 after 3000 cycles of charge/discharge test.These indicate that the newly designed material with nanostructures not only provides an efficient contact interface between electrolyte and active species and facilitates the transport of electrons and ions,but also protects the 3-dimensional nickel/aluminum layered double hydroxides,achieving a high specific capacity,fast redox reaction and excellent long-term cyclic stability.Therefore,theβ-nickel hydroxide covering nickel/aluminum layered double hydroxides with superior electrochemical performance is predictable to be a gifted electrode material in nickel–metal hydride batteries.