Papers by Keyword: Lithium-Ion Battery

Abstract: Structural and electronic properties of a new fluorine-free cathode material of polyanionichydroxysulfates, LiFeSO₄OH with caminite structure are studied using first principles density functional theory. From the calculated result, it reveals that antiferromagnetic configuration is more stable compared to ferromagnetic and non-magnetic configuration. Meanwhile, the density of state calculation divulges that this material exhibited large d-d type of band gap and would behave as a Mott-Hubbard insulator. Thus, this behaviour can lead to poor electronic conductivity.

Abstract: In order to online estimate the state of charge (SOC) of lithium-ion battery pack in this paper. This article establishes a dual Kalman filter (DEKF) algorithms for it. We establish a battery model of state space expression based on Thevenin battery model and Kalman filter algorithms. We use least square method and DEKF algorithms to identify the parameters of battery model in order to improve the accuracy of battery model. It can make battery model reflect true state of internal battery well. It introduces the principle which is dual Kalman filter algorithm online estimate the state of charge. Finally, it verifies DEKF algorithm has better convergence and robustness which can effectively resolve the problems of initial estimates error and cumulative error issue.

Abstract: Based on the genetic algorithm (GA), a novel type of parameters identification method on battery model was proposed. The battery model parameters were optimized by genetic optimization algorithm and the other parameters were identified through the hybrid pulse power characterization (HPPC) test. Accuracy and efficiency of the battery model were validated with the dynamic stress test (DST). Simulation and experiment results shows that the proposed model of the lithium-ion battery with identified parameters was accurate enough to meet the requirements of the state of charge (SoC) estimation and battery management system.

Abstract: We use Thevenin battery model and Kalman filter algorithm to online estimate lithium-ion battery pack state of charge (SOC) in this paper. In order to improve the accuracy of the model we use least square method and Dual Kalman filter (DEKF) algorithms to identify the parameters of model. The battery model can reflect the true state of internal battery well. The principle of Kalman filter algorithm is introduced. The relevant battery testing laboratory is designed. The algorithm has better accuracy when online estimate SOC and adapt to the environment well from experimental results. Finally, the convergence and robustness of DEKF algorithm are verified. It solves the problems that initial estimates are not accuracy and cumulative error.

Abstract: The state of charge (SOC) is an important index for power battery system. To obtain its accurate value,a comprehensive equivalent circuit model that parameters change depend on SOC was estiblished in this paper by using the lithium-ion battery hybrid pulse power characteristic data. Then the Extended Kalman filter (EKF) method is applied to estimate the SOC under the working condition. Numerical simulations are conducted to verify the effectiveness of the model and the EKF method. The results show that the EKF method based on the dynamic model can satisfy the accuray requirements.

Abstract: Considering the self-structure of lithium-ion battery and features of lithium-ion battery casing machine, the detailed design and analysis were carried on the components of lithium-ion battery casing machine. The motion simulation and finite element analysis were conducted by ADAMS and MARC software. The results show that the structure is practicable and the design is reasonable.

Abstract: For powering various micro/nanodevices and systems, it is necessary to develop a thin film micro-battery with high capacity and outstanding cycle performance. By using radio frequency (RF) magnetrons sputtering, tin oxide thin films used for thin film micro-batteries negative electrode were deposited on silicon substrates. Besides, doping metal impurity Cu was used to improve the performance of the films. The results showed that with the increasing of Cu-doping content, the phase of thin oxide thin films tended from crystalline to amorphous, the capacity of SnO_x films increased, and the cycle performance improved. Lastly, LiCoO₂/LiPON/SnO_x and LiCoO₂/LiPON/Cu_ySnO_x all-solid-states thin film lithium-ion batteries were prepared with MEMS techniques, and the tests gave the conclusions that with the copper doping in the negative electrode, the capacity of thin film lithium-ion batteries increased, and the batteries showed better circulation property.

Abstract: Pr doped SnO₂ particles as negative electrode material of lithium-ion battery are synthesized by the coprecipitation method with SnCl₄·5H₂O and Pr₂O₃ as raw materials. The structure of the SnO₂ particles and Pr doped SnO₂ particles are investigated respectively by XRD analysis. Doping is achieved well by coprecipitation method and is recognized as replacement doping or caulking doping. Electrochemical properties of the SnO₂ particles and Pr doped SnO₂ particles are tested by charge-discharge and cycle voltammogram experimentation, respectively. The initial specific discharge capacity of Pr doped SnO₂ the negative electrode materials is 676.3mAh/g. After 20 cycles, the capacity retention ratio is 90.5%. The reversible capacity of Pr doped SnO₂ negative electrode material higher than the reversible capacity of SnO₂ negative electrode material. Pr doped SnO₂ particles has good lithiumion intercalation/deintercalation performance.

Abstract: In order to evaluate the lithium-ion battery charging during electric vehicles regenerative braking, by testing on different initial SOC, charging current and temperature, the charging curves of lithium-ion battery are drawn under different conditions, and various parameters are derived. Based on a single factor in the impact of change on energy recovery, analyzed the influencing factors of coupling mechanism. Get approximation functions between energy recovery and multi-factor using multiple regression analysis method, and built energy recovery models. According to some experimentation with measured value and the calculated value, indicated the set of polynomials energy recovery model efficiency.

Abstract: Ti_xSn_1-xO₃ solid solution nanoparticles have been successfully prepared via a hydrothermal process. The morphology and structure of TiO₂, SnO₂ and Ti_xSn_1-xO₃ solid solution nanoparticles were investigated by scanning electron microscopy, transmission electron microscope and X-ray diffraction measurements. The electrochemical performance of TiO₂, SnO₂ and Ti_xSn_1-xO₃ solid solution nanoparticles as anode material for lithium-ion batteries were systematically investigated by a variety of electrochemical testing techniques. The Ti_xSn_1-xO₃ solid solution nanoparticles showed not only higher specific capacity of 401.3 mA h·g¹ after 50 cycles but also better cycle performance, superior than the pure SnO₂ electrode, which can be ascribed to the stable cyclability of TiO₂ and the high reversible capacity of nanosized SnO₂.