• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.839-847
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• 2016

Energy recovery battery testing systems (ERBTS) have been widely used in battery manufactures. All the ERBTS are connected in parallel which forms a special and complicated micro-grid system, which has the shortcomings of low energy recovery efficiency, complex grid-connected control algorithms issues for islanded detection, and complicated power circuit topology issues. To solve those shortcomings, a DC micro-grid system is proposed, the released testing energy has the priority to be reutilized between various testing system within the local grid, Compared to conventional scheme, the proposed system has the merits of a simplified power circuit topology, no needs for synchronous control, and much higher testing efficiency. The testing energy can be cycle-used inside the local micro-grid. The additional energy can be recovered to AC-grid. Numerous experimental comparison results between conventional and proposed scheme are provided to demonstrate the validity and effectiveness of the proposed technique.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.179-185
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• 2014

Average temperature and temperature uniformity in a battery cell are the important criteria of the thermal management of the battery pack for hybrid electric vehicles and electric vehicles (HEVs and EVs) because high power with large size cell is used for the battery pack. Thus, liquid cooling system is generally applied for the HEV/EV battery pack. The liquid cooling system is made of multiple cooling plates with coolant flow paths. The cooling plates are inserted between the battery cells to reject the heat from batteries to coolant. In this study, the cooling plate with U-shaped coolant flow paths is considered to evaluate the effects of coolant flow condition on the cooling performance of the system. The counter flow and parallel flow set up is compared and the effect of flow rate is evaluated using CFD tool (FLUENT). The number of counter-flows and flow rate are changed and the effect on the cooling performance including average temperature, differential temperature, and standard deviation of temperature are investigated. The results show that the parallel flow has better cooling performance compared with counter flow and it is also found that the coolant flow rate should be chosen with the consideration of trade-off between the cooling performance and pressure drop.

• Journal of Power Electronics
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• v.12 no.6
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• pp.954-959
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• 2012

A hybrid switch that uses a microelectromechanical system (MEMS) switch as a gate driver of a MOSFET is applied to an energy harvesting system. The power management circuit adopting the hybrid switch provides ultralow leakage, self-referencing, and high current handling capability. Measurements show that solar energy harvester circuit utilizing the MEMS-MOSFET hybrid switch accumulates energy and charges a battery or drive a resistive load without any constant power supply and reference voltage. The leakage current during energy accumulation is less than 10 pA. The power management circuit adopting the proposed hybrid switch is believed to be an ideal solution to self-powered wireless sensor nodes in smart grid systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.141-146
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• 2014

This paper suggests a way of generating one-day load curves for performance improvement of peak shaving in a power system. This Peak Shaving algorithm is a long-term scheduling algorithm of PMS (Power Management System) for BESS (Battery Energy Storage System). The main purpose of a PMS is to manage the input and output power from battery modules placed in a power system. Generally, when a Peak Shaving algorithm is used, a difference occurs between predict load curves and real load curves. This paper suggests a way of minimizing the difference by making predict load curves that consider weekly normalization and seasonal load characteristics for smooth energy charging and discharging.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.108-116
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• 2015

A missile defense system is composed of radars detecting incoming missiles aiming at defense assets, command control units making the decisions on weapon target assignment, and artillery batteries firing of defensive weapons to the incoming missiles. Although, the technology behind the development of radars and weapons is very important, effective assignment of the weapons against missile threats is much more crucial. When incoming missile targets toward valuable assets in the defense area are detected, the asset-based weapon target assignment model addresses the issue of weapon assignment to these missiles so as to maximize the total value of surviving assets threatened by them. In this paper, we present a model for an asset-based weapon assignment problem with shoot-look-shoot engagement policy and fixed set-up time between each anti-missile launch from each defense unit. Then, we show detailed linear approximation process for nonlinear portions of the model and propose final linear approximation model. After that, the proposed model is applied to several ballistic missile defense scenarios. In each defense scenario, the number of incoming missiles, the speed and the position of each missile, the number of defense artillery battery, the number of anti-missile in each artillery battery, single shot kill probability of each weapon to each target, value of assets, the air defense coverage are given. After running lpSolveAPI package of R language with the given data in each scenario in a personal computer, we summarize its weapon target assignment results specified with launch order time for each artillery battery. We also show computer processing time to get the result for each scenario.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.766-772
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• 2009

Generally, wind industry has been oriented to large power systems which require large windy areas and often need to overcome environment restrictions. However, small-scale wind turbines are closer to the consumers and have a large market potential, and much more efforts are required to become economically attractive. In this paper, a prototype of a small-scale urban wind generation system for battery charging application is described and a neural network based MPPT(Maximum Power Point Tracking) algorithm which can be effectively applied to urban wind turbine system is proposed. Through Matlab based simulation studies and actual implementation of the proposed algorithm, the feasibility of the proposed scheme is verified.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.11
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• pp.419-426
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• 2014

The recent trend of performance increase in the smart mobile devices demands more power consumption and lower batter life time. Among three battery models of mathematical model, electrochemical model and electric model, the Thevenin's equivalent circuit with non-linear function model of SOC in the electrical model is widely used. However, the OCV results have only limited accuracy because of the characteristic shift caused by temperature and age and atypical impedance property that cannot expressed by electrical components. In this paper, the new battery model that improves the accuracy of the existing models is proposed. In the proposed simulator the mathematical model for SOC characteristic is improved and the adjustment for the temperature, the age of battery and atypical electrical characteristics. In the experimental results of predicting of the battery in the static and dynamic state, the proposed simulator shows improved MSE comparing to the results of the existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.159-164
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• 2008

The efficiently power management Is an important requirement traditionally in the mobile communication system which uses battery as their power source. Especially, it has been emphasized in the most recent devices, which has to provide high performance and various functions with an extended operating time. In this article, the adaptive Power management technique for the core processor unit in embedded systems used widely for the mobile system thanks to its advantage on power consumption and physical site, is proposed.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.53-62
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• 2011

Although the demand of Variable Message Sign(VMS) has become pervasive in fulfilling the ITS policy, there are still several unsolved problematic issues. The most critical ones of them are inequality and inefficiency of providing traffic information. This paper proposes the Infra-free Variable Message Sign in order to provide useful informations such as road condition, weather, and traffic of the area, where constructing the infrastructure of communication and power supply is relatively very hard. First of all, the characteristics of infra-free Variable Message Sign are studied and analyzed in deep because of differences between normal Variable Message Sign and Infra-free Variable Message Sign in the configuration and the operating method due to the nature of the Infra-free Variable Message Sign. Futhermore, for effective power management of operating Infra-free Variable Message Sign with limited power acquired through stand-alone PV system, new battery connection structure and dynamically variable power managements for the differently shown messages on Variable Message Sign are proposed. The proposed structure in this paper can be applied to not only power management for Infra-free Variable Message Sign but also power management for the various applications using parallel connection battery system.