Voltage Lithium Ion Batteries Research Articles

Effect of explosion impact on the electrical performance and appearance of lithium-ion battery

In this work, the effect of the overpressure and incidence angle of shock waves on lithium-ion battery with various states of charge was studied, and the changes of electrical performance and appearance were measured accordingly. The result shows that the compression from shock wave can lead to the voltage going up and the internal resistance and capacity down; the elevated magnitude of the lithium-ion battery voltage goes up with the state of charge decreasing; the voltage increases and the internal resistance decreases with the overpressure increasing; the magnitude of battery capacity descent depends significantly on the severity of rupture disk cracking, and the capacity declines drastically corresponding to the complete failure of rupture disk; the cracked severity of rupture disk from oblique compression displays more than that from horizontal impact of shock wave; compared to 37Ah batteries, 50Ah batteries have higher safety valve damage thresholds and destruction thresholds, but are more prone to bulging. The conclusions will be of value to the establishment of safety standards for lithium-ion battery.

Understanding of Lithium-ion battery degradation using multisine-based nonlinear characterization method

The nonlinearity of lithium-ion battery voltage response has been recently gained high attention in battery characterization and health diagnosis. The multisine-based nonlinear characterization method has the potential for development as an expedient on-board technique for analyzing nonlinear responses. Despite this, it remains challenging to analyze the effect of aging degradation on LIB nonlinearity. In this study, the odd random-phase multisine method is performed on fresh and aged three-electrode experimental cells. This allowed for the separation of impedance-related linear approximation and odd or even order nonlinearity toward the full-cell voltage into their respective electrodes. The results demonstrate that, as the LIB degrades, the increase of impedance-related linear approximation estimated by the multisine-based method agrees well with the results of conventional EIS. The variation of nonlinearities is demonstrated in relation to the effect of degradation modes. The multisine-based method presents the advantage of simultaneously capturing impedance-related and nonlinearity information. This makes it become a fast diagnostic method that can be implemented in a BMS to quantify the causes of battery degradation, thereby supporting battery utilization optimization and future battery designs.

(Invited) Effect of Temperature on Lithium-Ion Battery Voltage Response and How to Model It in the Mechanistic Modeling Approach

The ongoing usage of lithium-ion cells and packs in both stationary and mobile applications necessitates comprehensive tools and models to diagnose and prognose cell performance onboard. One of the main tasks of a battery management system is to infer the state of charge (SOC) and state of health (SOH) of batteries. SOC estimation is usually done by relating a measured relaxation voltage to a stored SOC versus open circuit voltage (OCV) curve. The latter is dependent on the cell SOH and its degradation path. Therefore, both an accurate OCV and relaxation measurement are necessary for state estimation and it is essential to consider how they vary with temperature to ensure accuracy.This study aims at an exploration of the impact of temperature on relaxation and cell’s kinetics and how the voltage response at different temperatures can be simulated using the mechanistic modeling framework by tuning two parameters, the ohmic resistance increase and the rate degradation factor. The mechanistic modeling framework is using electrode half-cell data to synthesize the terminal voltage of battery cells based on the individual electrode potentials. Although proven valid in the quantification of degradation modes, path dependence of aging and cell-to-cell variations, the application of this modeling framework has been restricted so far mostly to voltage profiles recorded at room temperature and low rates. To be used in deployed battery management systems, this limitation should preferably be overcome to enable on-board diagnostics from medium to high rates and at any temperature.

First Cycle Cracking Behaviour Within Ni-Rich Cathodes During High-Voltage Charging

Increasing the operating voltage of lithium-ion batteries unlocks access to a higher charge capacity and therefore increases the driving range in electric vehicles, but doing so results in accelerated degradation via various mechanisms. A mechanism of particular interest is particle cracking in the positive electrode, resulting in losses in capacity, disconnection of active material, electrolyte side reactions, and gas formation. In this study, NMC811 (LiNi0.8Mn0.1Co0.1O2) half-cells are charged to increasing cut-off voltages, and ex situ X-ray diffraction and X-ray computed tomography are used to conduct post-mortem analysis of electrodes after their first charge in the delithiated state. In doing so, the lattice changes and extent of cracking that occur in early operation are uncovered. The reversibility of these effects is assessed through comparison to discharged cathodes undergoing a full cycle and have been relithiated. Comparisons to pristine lithiated electrodes show an increase in cracking for all electrodes as the voltage increases during delithiation, with the majority of cracks then closing upon lithiation.

Исследование характеристик литий-ионной аккумуляторной батареи

Purpose: To conduct research on obtaining data, that ties lithium-ion battery voltage to perturbing effects of current flow, to synthesize accumulator equivalent circuit, to obtain algorithm for calculating element parameters for accumulator equivalent circuit on experimental data basis with subsequent check of the model adequacy. Methods: Prognosing battery work that doesn’t correspond to real one at accumulator equivalent circuit synthesis. Equivalent-circuit models of cells plays a battery state though they do not possess all characteristics of physical model. Results: Algorithm for lithium-ion battery equivalent circuit synthesis has been considered, physical experiment on finding accumulator equivalent circuit parameters was conducted, mathematical model on the research results has been compiled and its adequacy has been confirmed. Practical significance: The pursued study made it possible to work out algorithm for calculating parameters to form the algorithm of lithium-ion battery functional diagnosis.

О выборе метода построения нечеткой модели прогнозирования состояния аккумулятора

Battery-powered electric vehicles are being currently considered to replace conventional non-environmental vehicles. Batteries could not be used without a control system, which development requires a mathematical model to predict the state of a separate battery. The Takagi --- Sugeno fuzzy system (fuzzy model) could become such a model. There are methods for automatic construction of fuzzy models according to the table of observations. However, unambiguous criteriafor selecting the appropriate method in each specific case are missing. The problem is considered of determining a method making it possible to obtain a fuzzy model that predicts the lithiumion battery voltage from the load current and the state of charge when discharging with direct current with the lowest meansquare error. The existing methods and their classes were reviewed, and five methods were selected for comparison. Prediction error by all the models obtained was unevenly distributed along the axis of the charge state, and it took the highest values in the range of 97--100 %. The lowest meansquare error was registered in the model built by the combined method using subtractive clustering, least squares method and adaptive network based on the adaptive neurofuzzy inference system. The error in such model was changing stepwise, which was associated with feature of the subtractive clustering algorithm, i.e., the formed clusters were of the same size

Precise prediction of open circuit voltage of lithium ion batteries in a short time period

Measuring the open circuit voltage (OCV) of a battery is quite time-consuming due to the relaxation process after the battery enters the open-circuit state. In this study, without the need of the complete voltage relaxation information, an available on-the-fly computing approach is proposed, by which the OCV at each state of charge (SOC) can be obtained from a simple first-order RC circuit model in a short period. The time constant of the RC model is evaluated by the ratio between the first and second derivatives of the experimental relaxation voltage at the earliest moment as soon as a specified voltage criterion on the real relaxation process is satisfied. With this criterion, the estimated OCV error is found to be extremely small. Experiments under three different temperatures and three types of battery state of health (SOH) are performed to verify the accuracy and robustness of the proposed approach. It is found that comparing to the traditional method of the OCV prediction at each SOC, the proposed approach can reduce the time of measuring the OCV to a few minutes (in most cases less than 6 min) with a reliable accuracy (in most cases less than 3 mV).

Precise Prediction of Open Circuit Voltage of Lithium Ion Batteries in a Short Time Period

Precise Prediction of Open Circuit Voltage of Lithium Ion Batteries in a Short Time Period

LiMn2O4 cathodes with F anion doping for superior performance of lithium-ion batteries.

Although considered as promising candidates for lithium-ion secondary batteries, spinel LiMn2O4 cathodes suffer from significant capacity decay owing to the Jahn-Teller effect, dissolution of Mn and lattice oxygen loss during the charge/discharge process, preventing their wider use. In this work, we realize that F-doping at small concentrations could improve the battery voltage and reduce the capacity decay using an atomistic model. For voltage, F-doping improves the voltage to about 4.4 eV under large delithiation. For capacity decay, it retards capacity decay owing to the reduced lattice oxygen loss. The larger Gibbs free energy of oxygen release after F-doping indicates harder lattice oxygen loss. In addition, although F-doping makes the average valence of Mn lower, the existence of Mn4+ during delithiation exerts a positive effect by reducing the Jahn-Teller effect. However, since the Mn3+ ions in the spinel structure could induce Jahn-Teller distortion, the effect of F-doping on Jahn-Teller distortion is determined by the competition between Mn4+ and Mn3+. The atomistic mechanism of F-doping in the performance of LiMn2O4 offers new insight in developing spinel lithium manganese oxide cathode materials with superior performance.

Combination of Stochastic State Estimation with Online Identification of the Open-Circuit Voltage of Lithium-Ion Batteries

Typical equivalent circuit models for Lithium-ion batteries are represented in the form of the so-called Thévenin form. These models comprise a state of charge (SOC) controlled voltage source as well as lumped elements such as series resistances as well as at least one RC subnetwork to describe dynamic effects by the terminal current and voltage as input and output of the battery. In classical state estimation approaches, these characteristics are assumed to be identified beforehand, while aging of battery cells is related to a loss of the total capacity, changes in the charging/discharging efficiency, an increase of the Ohmic cell resistance, and/or changes of the time constants of the above-mentioned RC networks. Such variations can be estimated by means of additional parameters that are included in the system's state vector. However, the typically applied approaches do not allow for a direct identification of the nonlinear dependencies of the circuit elements on the SOC and other influence factors such as currents or the cell temperature. Therefore, this paper proposes a real-time capable, two-stage identification of these dependencies on the example of the open-circuit voltage by means of an Unscented Kalman Filter (UKF) approach. In the first stage, the state variables of the dynamic system model are estimated together with a lumped disturbance term (an additive correction of the open-circuit voltage). In the second stage, this disturbance term is used to correct the a-priori knowledge of the open-circuit voltage and to simultaneously express the identification quality in terms of covariances for the coefficients of its piecewise polynomial approximation in each temporal discretization step. The efficiency of the proposed methodology is demonstrated in simulations for an experimentally validated system model.

Stable Electrode/Electrolyte Interface for High-Voltage NCM 523 Cathode Constructed by Synergistic Positive and Passive Approaches.

Increasing the working voltage of lithium-ion batteries (LIBs) is an efficient way to increase energy density. However, high voltage triggers excessive electrolyte decomposition at the electrode-electrolyte interfaces, where the electrochemical performance such as cyclic stability and rate capability is seriously deteriorated. A new synergistic positive and passive approach is proposed in this work to construct a stable electrode-electrolyte interface at high voltage. As a positive approach, inorganic lithium sulfide salt (Li2S) is used as an electrolyte additive to build a stable cathode electrolyte interface (CEI) at the LiNi0.5Co0.2Mn0.3O2 (NCM523) cathode surface. In a passive way, acetonitrile (AN) is applied as a solvent additive to suppress oxidative decomposition of a carbonate electrolyte via preferential solvation with a lithium ion. Because of the synergistic interaction between the positive and passive approaches, the cyclic stabilities of NCM523/Li cells improved with a tiny amount of Li2S (0.01 mg mL-1) and AN (0.5 vol %). The capacity retention increased to 80.74% after 200 cycles compared to the cells with the blank electrolyte (67.98%) and AN-containing electrolyte (75.8%). What is more, the capacity retention of the NCM523/graphite full cell is increased from 65 to 81% with the addition of the same amount of Li2S and AN after 180 cycles. The mechanism is revealed on the basis of the theoretical calculations and various characterizations. The products derived from the preferential adsorption and oxidation of Li2S on the surface of NCM523 effectively increase the content of inorganic ingredients. However, the presence of AN prevents oxidation of the solvent. This study provides new principle guiding studies on a high-voltage lithium-ion battery with excellent electrochemical performance.

LiCoO2/Graphite Cells with Localized High Concentration Carbonate Electrolytes for Higher Energy Density

Widening the working voltage of lithium-ion batteries is considered as an effective strategy to improve their energy density. However, the decomposition of conventional aprotic electrolytes at high voltage greatly impedes the success until the presence of high concentration electrolytes (HCEs) and the resultant localized HCEs (LHCEs). The unique solvated structure of HCEs/LHCEs endows the involved solvent with enhanced endurance toward high voltage while the LHCEs can simultaneously possess the decent viscosity for sufficient wettability to porous electrodes and separator. Nowadays, most LHCEs use LiFSI/LiTFSI as the salts and β-hydrofluoroethers as the counter solvents due to their good compatibility, yet the LHCE formula of cheap LiPF6 and high antioxidant α-hydrofluoroethers is seldom investigated. Here, we report a unique formula with 3 mol L−1 LiPF6 in mixed carbonate solvents and a counter solvent α-substituted fluorine compound (1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropylether). Compared to a conventional electrolyte, this formula enables dramatic improvement in the cycling performance of LiCoO2//graphite cells from approximately 150 cycles to 1000 cycles within the range of 2.9 to 4.5 V at 0.5 C. This work provides a new choice and scope to design functional LHCEs for high voltage systems.

Study on Charge and Discharge Phenomenon of Lithium Ion Battery under High Electric Field

It aims to clarify the influence of high electric field on lithium ion battery and to contribute to the establishment of appropriate use of it. In this study, a lithium ion battery is installed in the vicinity of a spherical electrode (diameter 100 mm) kept at a direct current ±10 kV and the presence or absence of a voltage change of the lithium ion battery. (1) A gap (20 mm) is provided between a needle electrode (tip radius of curvature 51 μm) attached to the positive electrode of a lithium ion battery and a spherical electrode, and the negative electrode is grounded. When applying +10 kV, the voltage rose by about 15 mV in 300 s, and the lithium ion battery was charged. When −10 kV was applied, the voltage dropped by about 10 mV in 300 s, and it was discharged. (2) A gap (10 mm) is provided between the needle electrode attached to the positive electrode of the lithium ion battery, and the spherical electrode, and the needle electrode attached to the negative electrode, and the grounded spherical electrode (diameter 100 mm). In this case, the lithium ion battery voltage has changed. Therefore, Lithium ion battery was found to be affected by high electric fields. It is presumed that the voltage of the battery changes because corona discharge causes charge transfer in the gap and a chemical reaction of the lithium ion battery occurs.

Fractional calculus based modeling of open circuit voltage of lithium-ion batteries for electric vehicles

Abstract Open circuit voltage (OCV) and state of charge (SOC) are key characteristic parameters of power batteries for electric vehicles. The OCV-SOC model is an integral of the design of the effective model and SOC estimation of the battery. However, there is a strong nonlinear relationship between OCV and SOC of lithium-ion batteries (LIBs). A novel OCV-SOC model of LIBs based on fractional calculus was proposed for the first time in this paper. The root mean squared error and the coefficient of determination were compared with the benchmarking models under a relatively fair condition. The sensitivity of the accuracy of the OCV-SOC models to temperature, numbers of data points, and SOC regions, were verified by the experimental results respectively, which showed that the proposed OCV-SOC model has good performance under different conditions, satisfying the accuracy requirements for modeling and state estimation of the battery in battery management systems.

Hybrid Control of PV-FC Electric Vehicle using Lyapunov based Theory

Lyapunov based control is used to test whether a dynamical system is asymptotically stable or not. The control strategy is based on linearization of system. A Lyapunov function is constructed to obtain a stabilizing feedback controller. This paper deals with Lyapunov based control of multiple input single output system for hybrid electric vehicles (HEVs). Generally, an electric vehicle has an energy management system (EMS), an inverter, a DC-DC converter and a traction motor for the operation of its wheels. The control action is applied on the DC-DC converter, which works side-by-side with the EMS of the electric vehicle. The input sources considered in this study are: photo-voltaic (PV) panel, fuel cell and high voltage lithium-ion (Li-ion) battery. PV cell and fuel cell are considered as the primary sources of energy and the battery is considered as the secondary source. The converter used is a DC-DC boost converter which is connected with all the three sources. The idea follows the basic HEV principle in which multiple sources are incorporated to satisfy the power demands of the vehicle, using a DC-DC converter and an inverter, to operate its traction motor. The target is to achieve necessary tracking of all input source currents and output voltage, and fulfill the power demand of the HEV under severe load transients. The operations of the DC-DC converter are divided into three stages, each representing a different combination of the input sources. The analysis and proof of the stability of the HEV system is done using the Lyapunov stability theory.The results are discussed in the conclusion.

Rapid Prediction of the Open-Circuit-Voltage of Lithium Ion Batteries Based on an Effective Voltage Relaxation Model

The open circuit voltage of lithium ion batteries in equilibrium state, as a vital thermodynamic characteristic parameter, is extensively studied for battery state estimation and management. However, the time-consuming relaxation process, usually for several hours or more, seriously hinders the widespread application of open circuit voltage. In this paper, a novel voltage relaxation model is proposed to predict the final open circuit voltage when the lithium ion batteries are in equilibrium state with a small amount of sample data in the first few minutes, based on the concentration polarization theory. The Nernst equation is introduced to describe the evolution of relaxation voltage. The accuracy and effectiveness of the model are verified using experimental data on lithium ion batteries with different kinds of electrodes (LiCoO2/mesocarbon-microbead and LiFePO4/graphite) under different working conditions. The validation results show that the presented model can fit the experimental results very well and the predicted values are quite accurate by taking only 5 min or less. The satisfying results suggest that the introduction of concentration polarization theory might provide researchers an alternative model form to establish voltage relaxation models.

A prediction method for discharge voltage of lithium-ion batteries under unknown dynamic loads

Discharge voltage is an important indicator to alarm end-of-discharge of lithium-ion batteries. Therefore, prediction of the discharge voltage when the battery is in use is helpful in preventing issues caused by running out of power. For many real applications, the battery is working under unknown and dynamic loads, which makes the prediction difficult. In this paper, we propose a novel method to predict the discharge voltage under unknown future loads. This method firstly establishes the relationship between the discharge voltage and the loads, then predicts future loads based on a framework consisted of wavelet analysis and polynomial neutral network with group method of data handling. Finally, the discharge voltage is predicted using the battery model with particle filter-based updating procedure and the predicted future loads. The effectiveness of this method is demonstrated by a real flight dataset coming from experiments conducted on a plant protection UAV. The results show that our method can achieve good prediction accuracy and outperforms some other benchmark methods.

An approach to predicpt discharge voltage of lithium-ion batteries under dynamic loading conditions

Terminal voltage is an important indicator to alarm end-of-discharge of lithium-ion batteries. Therefore, predicting the terminal voltage is helpful in preventing issues that caused by running out of power. However, the loading condition of battery is usually dynamic in real practice which greatly increases the difficulty of prediction. In this paper, we propose a novel approach to predict the terminal voltage under dynamic loading condition. This approach transforms the problem of predicting the terminal voltage into the problem of predicting the state-of-charge (SOC) of battery, using equivalent circuit model and a polynomial function. In the prediction of SOC, an accurate value of capacity is required, but it is not practical to be measured in each discharge process. Therefore, we develop an adaptive capacity method based on feature extraction in charging profile and k-nearest neighbor algorithm to timely update batterys SOC after each charge process. The whole prediction approach is tested on an open dataset, and comparison experiments demonstrate that it outperforms traditional approaches.

Destruction mechanism of the internal structure in Lithium-ion batteries used in aviation industry

In the article, the reasons for destruction of the internal structure in Lithium-ion batteries used in aviation industry have been explained. They manifest themselves in the battery's overheating, and in extreme cases they result in explosion. The report presents the results of experiments, which consisted in subjecting the tested Lithium-ion battery to vibration over a specified period of time and observing the changes of temperature inside it with the use of a thermal infrared camera. Another focal point of the study was the influence of vibrations on voltage change in relation to variable current load, and the influence of ambient temperature change on the Lithium-ion battery's voltage change. It has also been demonstrated that vibrations can damage the control electronics of the Lithium-ion battery. Moreover, the mechanism by which potentially dangerous thermal hot spots are formed in a Lithium-ion battery has been presented, as well as an uncertainty analysis of all measurement results.

Fluorinated Carbonate As an Additive for High-Voltage Performance Lithium Ion Battery

Increase of the operation voltage of lithium ion batteries (LIB) is one important approach to enhance the energy density. Generally, conventional organic electrolytes based on the carbonate solvents show oxidation at about 4.5 V. This can lead to severe capacity decay during the charge-discharge cycling. Thus it is significant to suppress decomposition of electrolyte and stabilize the cathode. Here we investigated fluorinated carbonate solvent as an additive for high-voltage performance of LiNi0.5Co0.2Mn0.3O2 cathode LiB. The effects of additive content and electrochemical performances of the LIB were studied.