• Title/Summary/Keyword: lithium batteries

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A Study on the Rail Vehicle Applications and Increase the Capacity of Lithium Polymer Batteries (리튬폴리머 축전지의 철도차량 적용 및 용량증대에 관한 연구)

  • Cho, Kyu-Hwa;Kang, Seung-Wook
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.65 no.4
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    • pp.340-345
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    • 2016
  • Railway vehicle battery is supplying the power required for the initial start-up of the train, in the event of a fault in the vehicle, or catenary for supplying emergency power is one of the components are very important. Currently, the railway vehicles such as nickel-cadmium batteries are being used [1,2]. Ni-Cd batteries as a battery installed in the railway vehicles have a strong corrosion resistance is included, The charge-discharge performance is significantly degraded in cold weather, there is a danger of deterioration or explosion. Train accidents have been caused a lot of damage due to rapid deterioration and cracking of the battery and memory due to the effect of Ni-Cd batteries. In order to solve the problems, There is no risk of degradation, deterioration and leakage, cracking and exploding. maintenance is simple and applied measures proposed to apply Lithium Polymer battery of high performance. In addition, the lack of capacity problems identified by testing the different special systems is replaced by a 70Ah lithium-polymer battery is possible without changing the batteries of 50Ah caused by installing additional equipment in existing older trains were applied to the vehicle.

Numerical analysis on thermal runaway by cathode active materials in lithium-ion batteries (리튬이온전지 열폭주에 대해 양극활물질이 미치는 영향에 대한 수치해석적 연구)

  • Gang, Myung-Bo;Kim, Nam-Jin
    • Journal of the Korean Society for Geothermal and Hydrothermal Energy
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    • v.17 no.2
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    • pp.1-10
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    • 2021
  • Lithium-ion batteries with high energy density, long cycle life and other advantages, have been widely used to energy storage systems(ESS). But as ESS fires frequently occur, the safety concern has become the main obstacle that hinders the large-scale applications of lithium-ion batteries. Especially, thermal runaway is the key scientific problem in battery safety research. Therefore, in this study, we performed a numerical analysis on the thermal runaway phenomenon of NCM111, NCM523 and NCM622 batteries using a two-dimensional analysis model. The results show that the two-dimensional simulation results are generally matched with three-dimensional simulation. Also, In the case of NCM111 with a low Ni content in the temperature range used in this study, thermal runaway phenomenon does occurred very slowly, but as the Ni content is increased, the thermal runaway phenomenon occurs rapidly and the thermal stability tends to be decreased. And, in NCM523 and NCM622 batteries, chain reactions occur almost simultaneously, but in the case of NCM111 battery, it is found that after the SEI(Solid Electrolyte Interface) layer decomposition reaction, the cathode-electrolyte reaction is appeared sequentially. After that, the anodic decomposition reaction is increased and leads to the thermal runaway reaction.

Deep Learning Approaches to RUL Prediction of Lithium-ion Batteries (딥러닝을 이용한 리튬이온 배터리 잔여 유효수명 예측)

  • Jung, Sang-Jin;Hur, Jang-Wook
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.19 no.12
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    • pp.21-27
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    • 2020
  • Lithium-ion batteries are the heart of energy-storing devices and electric vehicles. Owing to their superior qualities, such as high capacity and energy efficiency, they have become quite popular, resulting in an increased demand for failure/damage prevention and useable life maximization. To prevent failure in Lithium-ion batteries, improve their reliability, and ensure productivity, prognosticative measures such as condition monitoring through sensors, condition assessment for failure detection, and remaining useful life prediction through data-driven prognostics and health management approaches have become important topics for research. In this study, the residual useful life of Lithium-ion batteries was predicted using two efficient artificial recurrent neural networks-ong short-term memory (LSTM) and gated recurrent unit (GRU). The proposed approaches were compared for prognostics accuracy and cost-efficiency. It was determined that LSTM showed slightly higher accuracy, whereas GRUs have a computational advantage.

Study on-Gas-generating Property Of Lithium Polymer Drone batteries (리튬 폴리머 드론 배터리 방전시 이상가스에 대한 연구)

  • Jong-Heon Lee;Jae-Won Kim;Hong-Joo Yoon;Won-Chan Seo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.1
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    • pp.195-204
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    • 2023
  • The drone's battery system uses lithium-ion or lithium-polymer batteries, and it is known that the cause of fire during the disposal process after using the drone is combustible gas from the battery being discarded. Most of the batteries in the disposal process generated oxygen, but a small amount of flammable gas was also generated, and a large amount of chlorine ions and sulfates were also detected in the equipment used for treatment. If a system that detects this early is configured, it will be possible to reduce the risk of accidents caused by discarded batteries.

Ionic Liquid Crystal Electrolytes based on Ether Functionalized Ionic Liquid for Lithium Batteries (리튬전지용 에테르가 기능화된 이온성 액체 기반 이온성 액정 전해질의 전기화학적 특성)

  • Kim, Il Jin;Kim, Ki Su;Lee, Jin Hong
    • Applied Chemistry for Engineering
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    • v.31 no.3
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    • pp.305-309
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    • 2020
  • In this study, a series of ionic liquids based electrolytes for lithium batteries were prepared by mixing the anion functionalized ionic liquid, [DMIm][MPEGP] (1,3-dimethylimidazolium (2-methoxy(2-ethoxy(2-ethoxy)))-ethylphosphite), with the lithium salt, LiTf2N (lithium bis(trifluoromethanesulfonyl)imide), and the concentration of lithium salt was varied between 0 and 3.0 molar ratio. We observed the ionic mixtures became opaque and spontaneously aggregated to form a thermotropic ionic liquid crystal. Extensive spectroscopic examinations of the ionic liquid crystals were carried out to investigate their self-organized structures and the ion transport behavior depending on the concentration of lithium salt. An increase in the ionic conductivity was observed for the ionic liquid crystals related to the ability to form ion diffusion pathways along the ordered structures, resulting in improved electrochemical performances of lithium batteries.

Electrochemical properties of all solid state Li/LiPON/Sn-substituted LiMn2O4 thin film batteries

  • Kong, Woo-Yeon;Yim, Hae-Na;Yoon, Seok-Jin;Nahm, Sahn;Choi, Ji-Won
    • Proceedings of the Korean Vacuum Society Conference
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    • 2011.02a
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    • pp.409-409
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    • 2011
  • All solid-state thin film lithium batteries have many applications in miniaturized devices because of lightweight, long-life, low self-discharge and high energy density. The research of cathode materials for thin film lithium batteries that provide high energy density at fast discharge rates is important to meet the demands for high-power applications. Among cathode materials, lithium manganese oxide materials as spinel-based compounds have been reported to possess specific advantages of high electrochemical potential, high abundant, low cost, and low toxicity. However, the lithium manganese oxide has problem of capacity fade which caused by dissolution of Mn ions during intercalation reaction and phase instability. For this problem, many studies on effect of various transition metals have been reported. In the preliminary study, the Sn-substituted LiMn2O4 thin films prepared by pulsed laser deposition have shown the improvement in discharge capacity and cycleability. In this study, the thin films of LiMn2O4 and LiSn0.0125Mn1.975O4 prepared by RF magnetron sputtering were studied with effect of deposition parameters on the phase, surface morphology and electrochemical property. And, all solid-state thin film batteries comprised of a lithium anode, lithium phosphorus oxy-nitride (LiPON) solid electrolyte and LiMn2O4-based cathode were fabricated, and the electrochemical property was investigated.

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New Solid Polymer Electrolyte for Lithium Secondary Batteries

  • Park, Jung-Ki;Lee, Yong-Min;Lee, Jun-Young;Ryou, Myeong-Hyeon
    • Proceedings of the Polymer Society of Korea Conference
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    • 2006.10a
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    • pp.67-68
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    • 2006
  • Solid polymer electrolyte is very important in the applications to high energy density lithium batteries of high safety. In this work, solid polymer electrolytes based on PE non-woven matrix, hybrid salt, and anion receptor were successfully prepared. They could provide high ion conduction phase with maintaining mechanical strength. They also showed high electrochemical stability and lithium ion transference number. This new type of solid polymer electrolyte is expected to be a good candidate for rechargeable solid state lithium secondary batteries.

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Development of High-Performance Smart Battery for Notebook PCs with Lithium Ion Battery (리튬이온전지를 이용한 노트북 PC용 고성능 Smart Battery의 개발)

  • 김현수;문성인;윤문수;고병희;김동훈
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.16 no.11
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    • pp.1047-1054
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    • 2003
  • Smart battery pack (SBP) for notebook PCs was developed using a cylindrical-type lithium ion battery. Batteries were connected with three serial and two parallel, the nominal capacity and the maximum load of SBP was 4,000mAh and 4.0A, respectively. The SBP was composed of a protection IC, by which safety of lithium ion batteries is maintained against overcharge, overdischarge and overcurrent, and a smart IC, which calculates the remaining capacity and the remaining run time. In matching test on notebook PC using Battery Mark 4.0, real and smart data of END voltage coincided nearly and LB and LLB signal worked norma]]y. And there were errors of less than 1% between the real and the smart data on the residual capacity in the charge and discharge test.

On-board Capacity Estimation of Lithium-ion Batteries Based on Charge Phase

  • Zhou, Yapeng;Huang, Miaohua
    • Journal of Electrical Engineering and Technology
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    • v.13 no.2
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    • pp.733-741
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    • 2018
  • Capacity estimation is indispensable to ensure the safety and reliability of lithium-ion batteries in electric vehicles (EVs). Therefore it's quite necessary to develop an effective on-board capacity estimation technique. Based on experiment, it's found constant current charge time (CCCT) and the capacity have a strong linear correlation when the capacity is more than 80% of its rated value, during which the battery is considered healthy. Thus this paper employs CCCT as the health indicator for on-board capacity estimation by means of relevance vector machine (RVM). As the ambient temperature (AT) dramatically influences the capacity fading, it is added to RVM input to improve the estimation accuracy. The estimations are compared with that via back-propagation neural network (BPNN). The experiments demonstrate that CCCT with AT is highly qualified for on-board capacity estimation of lithium-ion batteries via RVM as the results are more precise and reliable than that calculated by BPNN.