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[en] A brief introduction of the development background, the concept, characteristic and advantages of lithium-ion battery was given. The typical fire accidents about lithium-ion battery in production process, the vehicle with new energy, portable electronic products were summarized. Some important factors for lithium-ion batteries’ safety were emphatically analyzed. Several constructive suggestions on improvement direction were given, meanwhile, we have a nice exception on the future of lithium-ion battery industry. (paper)
[en] With the wide application of lithium ion battery in the energy storage system, Much attention had been paid to the state of health (SOH) evaluation research. In this paper, the research advance of SOH evaluation methods for lithium-ion battery was reviewed. Several main SOH evaluation methods, including defining method, internal resistance method, AC impedance, voltage curve method, model method and some new methods, were discussed in detail. And finally the research direction of further progress in this area was proposed. (paper)
[en] Highlights: •SOC and capacity are dually estimated with online adapted battery model. •Model identification and state dual estimate are fully decoupled. •Multiple timescales are used to improve estimation accuracy and stability. •The proposed method is verified with lab-scale experiments. •The proposed method is applicable to different battery chemistries. -- Abstract: Reliable online estimation of state of charge (SOC) and capacity is critically important for the battery management system (BMS). This paper presents a multi-timescale method for dual estimation of SOC and capacity with an online identified battery model. The model parameter estimator and the dual estimator are fully decoupled and executed with different timescales to improve the model accuracy and stability. Specifically, the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them. Based on the online adapted battery model, the Kalman filter (KF)-based SOC estimator and RLS-based capacity estimator are formulated and integrated in the form of dual estimation. Experimental results suggest that the proposed method estimates the model parameters, SOC, and capacity in real time with fast convergence and high accuracy. Experiments on both lithium-ion battery and vanadium redox flow battery (VRB) verify the generality of the proposed method on multiple battery chemistries. The proposed method is also compared with other existing methods on the computational cost to reveal its superiority for practical application.
[en] Structural changes in a promising cathode material LiNi0.8Co0.1Mn0.1O2 for lithium-ion batteries were in situ studied by X-ray diffraction analysis in the course of electrochemical reactions. The Rietveld method and TOPAS 5 software package were used to examine changes in the unit cell parameters of LiNi0.8Co0.1Mn0.1O2 and the reasons for these changes. It was found that the unit cell volume increases by 2% relative to the discharged state (2.7 V) upon charging to 4.2 V.
[en] In this manuscript, porous Co3O4 nanorods are prepared through a two-step approach which is composed of hydrothermal process and heating treatment as high performance anode for lithium-ion battery. Benefiting from the porous structure and 1-dimensional features, the product becomes robust and exhibits high reversible capability, good cycling performance, and excellent rate performance. - Graphical abstract: 1D porous Co3O4 nanostructure as anode for lithium-ion battery with excellent electrochemical performance. - Highlights: • A two-step route has been applied to prepare 1D porous Co3O4 nanostructure. • Its porous feature facilitates the fast transport of electron and lithium ion. • Its porous structure endows it with capacities higher than its theoretical capacity. • 1D nanostructure can tolerate volume changes during lithation/delithiation cycles. • It exhibits high capacity, good cyclability and excellent rate performance
[en] In recent years lithium-ion batteries have been widely applied for portable electronic devices such as cellular phones and personal computers. Sulfones are dipolar aprotic solvents, which are used in lithium-ion batteries because of their high resistivity to electrode materials and ability to ensure high speed of electrode process. The aim of this work is the study of the local structures of LiCl in ethyl methyl sulfone (EMSO2) using quantum chemical calculations. All calculations have been carried out using the Gaussian 09 software package. Optimization of the molecular structure of isolated molecule of EMSO2 and that of the complex 1:1 LiCl:EMSO2 in their ground states in the gas phase was performed using restricted Hartree-Fock (RHF) method combined with 6-311++G(d,p) extended basis set including polarization and diffuse functions. The assignment of theoretical vibrational modes was performed by GaussView 5.0, which gives a visual representation of vibrational modes. The structural and spectral parameters of LiCl/ethyl methyl sulfone system were established. The calculations show the existence of two stable 1:1 LiCl:ethyl methyl sulfone structures and one transition state. The energy minima and transition state structure were verified by vibrational analysis. Energy minima were confirmed by the absence of imaginary vibration frequency. In the case of transition state one imaginary mode was observed. It was shown that intensity of the CH and SO stretching vibrations to the interaction between LiCl and sulfone strongly depends on the structure of the complex. The difference in spectral features is explained in the frame of vibrational Stark effect. The obtained results have been compared with those for LiCl/dimethyl sulfone and LiCl/diethyl sulfone system
[en] Highlights: •The model is linked to known physicochemical degradation processes and material properties. •Aging dynamics of various battery formulations can be understood by the proposed model. •Large number of experiments will be reduced to accelerate the battery design process. •This approach can describe batteries under various operating conditions. •The proposed model is simple and easily implemented. -- Abstract: A five-state nonhomogeneous Markov chain model, which is an effective and promising way to accelerate the Li-ion battery design process by investigating the capacity fading dynamics of different formulations during the battery design phase, is reported. The parameters of this model are linked to known physicochemical degradation dynamics and material properties. Herein, the states and behaviors of the active materials in Li-ion batteries are modelled. To verify the efficiency of the proposed model, a dataset from approximately 3 years of cycling capacity fading experiments of various formulations using several different materials provided by Contemporary Amperex Technology Limited (CATL), as well as a NASA dataset, are employed. The capabilities of the proposed model for different amounts (50%, 70%, and 90%) of available experimental capacity data are tested and analyzed to assist with the final design determination for manufacturers. The average relative errors of life cycling prediction acquired from these tests are less than 2.4%, 0.8%, and 0.3%, even when only 50%, 70%, and 90% of the data, respectively, is available for different anode materials, electrolyte materials, and individual batteries. Furthermore, the variance is 0.518% when only 50% of the data are available; i.e., one can save at least 50% of the total experimental time and cost with an accuracy greater than 97% in the design phase, which demonstrates an effective and promising way to accelerate the Li-ion battery design process. The qualitative and quantitative analyses conducted in this study suggest that the proposed model provides an accurate, robust, and simple way to accelerate the Li-ion battery design process for battery manufacturers, thereby enabling rapid market capture.
[en] Accelerated degradation tests can be used as the basis for predicting the performance or state of health of products and materials at use conditions over time. Measurements acquired at accelerated levels of stress are used to develop models that relate to the degradation of one or more performance measures. Frequently, products/materials of interest are subjected to variable stress levels during their lifetimes. However, testing is usually performed only at a few fixed stress levels. In such cases, cumulative degradation models are developed and assessed by using data acquired under those fixed stress conditions. The degradation rate at any stress condition within the range of the model can be estimated by the derivative of the cumulative model at that stress condition. It follows that, to predict cumulative degradation over variable use conditions, one might integrate the fluctuating degradation rate over time. Existing approaches for doing this consider degradation rates that depend only on the current stress level. Here, we propose to allow the degradation rate to also depend on the current state of health as indicated by the associated performance measure(s). The resulting modeling approach is capable of portraying a broader range of degradation behavior than existing approaches. The assertion of memoryless degradation by using this or any other approach should be assessed experimentally with data acquired under variable stress in order to increase confidence that the integrated rate model is accurate. In this article, we demonstrate the additional capability of the proposed approach by developing empirical memoryless rate-based degradation models to predict resistance increase and capacity decrease in lithium-ion cells that are being evaluated for use in electric vehicles. Here, we then assess the plausibility of these models.
[en] Highlights: • The modified adiabatic method is used to measure the heat generation under overcharge. • Side reactions contribute 80% heat to thermal runaway in the cases with cycling rate below 1.0 C. • The inflection and maximum voltages increase linearly with the increasing current rates. • The decomposed products of cathode materials are soluble with that of SiO_x. • Lithium plating on anode is due to changes of distance between the cathode and anode. - Abstract: Cells in battery packs are easily overcharged when battery management system (BMS) is out of order, causing thermal runaway. However, the traditional calorimetry could not estimate dynamic overcharging heat release. In this study, commercial LiCoO_2 + Li(Ni_0_._5Co_0_._2Mn_0_._3)O_2/C + SiO_x cells are employed to investigate the dynamic thermal behaviors during overcharge under adiabatic condition by combining a multi-channel battery cycler with an accelerating rate calorimeter. The results indicate that overcharging with galvanostatic - potentiostatic - galvanostatic regime is more dangerous than that with galvanostatic way. Side reactions contribute 80% heat to thermal runaway in cases below 1.0 C charging rate. To prevent the thermal runaway, the effective methods should be taken within 2 min to cool down the batteries as soon as the cells pass inflection point voltage. Hereinto, the inflection and maximum voltages increase linearly with the increasing current rates. By scanning electron microscope and energy dispersive spectrometer, the decomposed products of cathode materials are suspected to be soluble with SiOx. The overcharge induced decomposition reaction of Li(Ni_0_._5Co_0_._2Mn_0_._3)O_2 is also proposed. These results can provide support for the safety designs of lithium ion batteries and BMS.