• 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.

• 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.

• 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.

• 한국전기화학회:학술대회논문집
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• 2001.11a
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• pp.75-93
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• 2001

• 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.

• 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.

• 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.

• 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.

• Transactions on Electrical and Electronic Materials
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• v.8 no.4
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• pp.157-160
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• 2007

Lithium-sulphur batteries were fabricated in a dry room, and their electrochemical properties were analyzed by scanning electron microscopy (SEM), cyclic voltammetry (CV), and charge-discharge tests. SEM results showed that sulphur and nanocarbon powders were mixed homogeneously, and sulphur powders were enwrapped by a large amount of carbon powders. The charge-discharge test results demonstrated that the lithium-sulphur battery displayed excellent reversibility and cycling performance, which supplied a discharge capacity of $788.1mAh\;g^{-1}$ at the first cycle and $796.4mAh\;g^{-1}$ after 71 cycles at room temperature, respectively.

• Journal of the Korea Safety Management & Science
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• v.22 no.2
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• pp.47-55
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• 2020

This study analyzed ignition probability about Lithium-polymer batteries of what variously were being produced wearable devices recently. The study analyzed ignition probability by PCM(Protection Circuit Module) operating state and overcharged, over-discharged, exposed to high temperatures of Lithium polymer batteries, analyzing wearable devices on the market. Then it classified experimental results to implement analysis comparison about weight, X-ray imaging, battery decomposition. With these experiments, the study analyzed combustion-possibility and fire patterns. These statistics will be used to measure and verify the cause of a fire when identify wearable devices using Lithium-polymer batteries.