• Journal of the Korean Institute of Gas
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• v.24 no.6
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• pp.91-97
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• 2020

Lithium-ion batteries (LIBs) have a longer lifespan, higher energy density, and lower self-discharge rates than other batteries, therefore, they are preferred as an Energy Storage System (ESS). However, during years 2017-2019, 28 ESS fire accidents occurred in Korea, and accurate capacity estimation of LIB is essential to ensure safety and reliability during operations. In this study, data-driven modeling that predicts capacity changes according to the charging cycle of LIB was conducted, and developed models were compared their performance for the selection of the optimal machine learning model, which includes the Decision Tree, Ensemble Learning Method, Support Vector Regression, and Gaussian Process Regression (GPR). For model training, lithium battery test data provided by NASA was used, and GPR showed the best prediction performance. Based on this study, we will develop an enhanced LIB capacity prediction and remaining useful life estimation model through additional data training, and improve the performance of anomaly detection and monitoring during operations, enabling safe and stable ESS operations.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.355-357
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• 2004

In this paper, to calculate accurate remaining volume, it presents how to figure out nickel-cadmium battery algorithm. A nickel-cadmium battery has widely been used in industrial field and to military. Recent high demands on the battery caused 'How to calculate accurate remaining volume is very important task to be solved. In this paper, it says it is useful using the terminal voltage change of the resistance that can be connected with the battery and the differentiation of the terminal voltage to calculate remaining volume of nickel-cadmium battery. And these can be used for volume inference data so that it is fuzzy based system which can be helpful to inference the remaining volume by the resistance of terminal voltage change. Because of electrochemical complexity, the volume calculating system is inferencing undirectly by experimentally built DB where as current the existing volume models are suffering to be adapted.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.1
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• pp.48-55
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• 2022

This paper proposes a battery remaining useful life (RUL) prediction method using a deep learning-based EMD-CNN-LSTM hybrid method. The proposed method pre-processes capacity data by applying empirical mode decomposition (EMD) and predicts the remaining useful life using CNN-LSTM. CNN-LSTM is a hybrid method that combines convolution neural network (CNN), which analyzes spatial features, and long short term memory (LSTM), which is a deep learning technique that processes time series data analysis. The performance of the proposed remaining useful life prediction method is verified using the battery aging experiment data provided by the NASA Ames Prognostics Center of Excellence and shows higher accuracy than does the conventional method.

• Journal of Electrochemical Science and Technology
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• v.7 no.2
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• pp.161-169
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• 2016

Porous tungsten oxide thin films were prepared by electrodeposition and tested as anodes of lithium secondary batteries. The synthesized films were composed of nanoparticles of 60-140 nm size, with porosities of 30-40 %. Increasing the temperature turned out to be a more effective approach to introduce porosity in the structure than increasing the electrolyte viscosity. The assessment of the synthesized films as anodes of lithium secondary batteries revealed a much higher initial discharge capacity for the porous than the dense samples. The discharge capacity retention significantly increased with increasing porosity and was further enhanced by heat treatment. In particular, a thin film composed of particles of about 140 nm in size and with a porosity of 40 % exhibited an initial discharge capacity higher than 600 mAh/g and a remaining capacity above 300 mAh/g after 30 cycles. Following heat treatment, the remaining capacity of this sample after 30 cycles increased to about 500 mA h/g.

• Journal of the Korean Mathematical Society
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• v.42 no.3
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• pp.517-527
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• 2005

This paper considers a discrete-time queueing system with variable service capacity. Using the supplementary variable method and the generating function technique, we compute the joint probability distribution of queue length and remaining service time at an arbitrary slot boundary, and also compute the distribution of the queue length at a departure time.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2171-2172
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• 2011

Recently, while interests on supply of electric vehicles have increased there still are insufficient charging facilities. As a solution to this matter, using electric power grids that constantly retain about 30~50[%] residual power is being considered. Therefore proposed in this paper railway, is a method to establish a charging infrastructure to utilize railway DC power grids. In addition we designed a high-speed DC charging system, and simulated improvements of the charging structure's charging efficiency according to remaining capacity of batteries.

• The Journal of Information Systems
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• v.29 no.1
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• pp.75-91
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• 2020

Purpose Retrofit, defined to be addition of new technologies or features to the old system to increase efficiency or to abate GHG emissions, is considered as an important alternative for the old coal-fired power plant. The purpose of this study is to propose mathematical method to model multiple alternative retrofit in Generation Capacity Expansion Planning(GCEP) problem, and to get insight to the retrofit patterns from realistic case studies. Design/methodology/approach This study made a multi-alternative retrofit GECP model by adopting some new variables and equations to the existing GECP model. Added variables and equations are to ensure the retrofit feature that the life time of retrofitted plant is the remaining life time of the old power plant. We formulated such that multiple retrofit alternatives are simultaneously compared and the best retrofit alternative can be selected. And we found that old approach to model retrofit has a problem that old plant with long remaining life time is retrofitted earlier than the one with short remaining life time, fixed the problem by some constraints with some binary variables. Therefore, the proposed model is formulated into a mixed binary programming problem, and coded and run using the GAMS/cplex. Findings According to the empirical analysis result, we found that approach to model the multiple alternative retrofit proposed in this study is comparing simultaneously multiple retrofit alternatives and select the best retrofit satisfying the retrofit features related to the life time. And we found that retrofit order problem is cleared. In addition, the model is expected to be very useful in evaluating and developing the national policies concerning coal-fired power plant retrofit.

• The KIPS Transactions:PartC
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• v.15C no.4
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• pp.303-310
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• 2008

To increase the lifetime of ad-hoc networks, a ratio of energy consumption for each node should be kept constant by equally distributing network traffic loads into all of the nodes. In this paper, we propose a modified AODV routing protocol to determine a possible route by considering a remaining battery capacity of a node and the degree of its usage. In addition, to reduce the amount of energy consumption during the path rediscovery process due to the huge amount of the AODV control messages the limited number of possible routes are stored into a routing table of a source node. When some links of a route fail, another possible path can be looked up in the table before the route discovery process should be initiated. We have tested our proposed method with a conventional AODV and a MMBCR method which is one of the power-efficient energy routing protocols based on the three performance metrics, i.e., the total remaining battery capacity, network lifetime and the ratio of data packets received by the destination node to compare their performance.

• Journal of the Korean Institute of Gas
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• v.23 no.5
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• pp.1-7
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• 2019

Although the rupture pressure is evaluated from remaining strength when a flaw is defected to cylinder surface, but the rupture pressure can be not easy to estimate for the composite cylinders. In this study, the area capacity method is developed for the type-3 cylinders that is based on the result applied area capacity method of type-1 cylinders. And the reliability is validated by bursting test with artificial flaw at the cylinder surface. The predicted data of area capacity method and experimental results have very similar tendency. This method and results will be a very important records in field of rupture pressure estimations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.1
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• pp.90-97
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• 2016

Sunken vessels accidents have harmful impacts on the marine environment because of oils and chemicals in the vessels. The government has managed them and developed risk assessment which can evaluate potential risk quantitatively since 1999. But the grades of present risk assessment has changed greatly depending on quantity of remaining fuel oils, and the list of remaining fuel oils omitted in status report of sunken vessels. Therefore, the aim of the study is to estimate and develop model for quantity of remaining fuel oils and verify the remaining fuel estimation comparison with active vessels. To accomplish the purpose of the study, apply this verified estimation model to current risk assessment and recommend guideline for an accurate sunken vessels risk assessment.