• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.188.1-188.1
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• 2012

인공위성에 사용되는 배터리 기술은 1960년대 최초로 사용된 니켈 카드뮴(NiCd)을 시작으로 발전하기 시작해서 현재는 리튬-이온(Li-Ion)에 이르렀다. 리튬-이온 배터리는 높은 Energy Density(작은 크기와 무게), 낮은 자가 방전율을 가짐과 동시에 메모리 효과가 거의 없다는 장점이 있다. 하지만 리튬-이온 배터리 팩의 성능(Voltage, Capacity, Lifetime)은 사용된 Cell간 특성차이(State of Charge, Total Capacity Difference, Internal Impedance)에 의해 제한된다. 일반적으로 배터리는 원하는 전압과 용량을 확보하기 위해 직렬-병렬 혹은 병렬-직렬 구조를 가지는 팩 형태로 제작 된다. Cell간 특성차이가 존재하는 상태에서 배터리 팩을 사용할 경우 특정 Cell의 과충전 및 과방전이 발생하며 이로 인해 수명이 단축될 수 있고 심한 경우 폭발이 발생할 수 도 있다. 또한 Cell간 특성차이는 배터리팩의 사용가능 용량을 제한하는 효과를 가져 온다. 본 논문에서는 Battery 팩을 구성하는 Cell들에 특성 차이가 존재할 경우 발생할 수 있는 Battery 팩의 수명 단축 및 용량 감소 Mechanism에 대해서 고찰한다. 또한 Cell간 특성차이를 극복하기 위해 실제 위성 운용에 적용될 수 있는 배터리팩의 Balancing 방안과 함께 위성에 장착을 위해 보관중인 4p12s Battery의 Balancing 방안에 대해 고찰하고 Balancing 전후의 Cell간 특성(Voltage Dispersion) 차이 측정결과를 보인다. 이렇게 본 논문에서 소개한 리튬-이온 배터리의 전반적인 Balancing 방안은 추후 인공위성에 적용되는 리튬-이온 배터리의 운용 및 보관에 Guide Line을 제시할 것이라고 판단한다.

• Proceedings of the KIPE Conference
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• 2015.11a
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• pp.7-8
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• 2015

In this paper a cell-to-cell fast charge balancing circuit for the Lithium-Ion battery module is proposed. In the proposed topology the energy in a high voltage cell is transferred directly to a low voltage cell through the operation of the dc-dc converter. Furthermore, the charge balancing can be performed regardless of the battery operation whether it is being charged, discharged or relaxed. The monitoring circuit composed of a DSP and a battery monitoring IC is designed to monitor the cell voltage and detect the inferior cell thereby protecting the battery module from failure. In order to demonstrate the performance of the proposed topology, a prototype circuit was designed and applied to 12 Lithium-Ion battery module. It has been verified with the experiments that the charge equalization time of the proposed method was shorter compared with those of other methods.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.70-76
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• 2009

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.8
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• pp.577-584
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• 2007

A variable-flow-rate balancing valve has been developed and optimized to apply to a distributor in a hot-water heating system. Fluid dynamic performance of the system was evaluated by comparing the results with the previous pressure difference control valve (PDCV) system. In view of the variations of pressure drop and flow rate according to the sequential closing of the control valves, the present system which is named "smart system distributor", is very stable without a certain flow rate concentration. The level of pressure drop variation is also low as compared with the previous system with a PDCV. In view of the occurrence of cavitation, the present system is quite superior to the previous system because the instantaneous pressures at all sections are much higher than the vapor pressure. On the other hand, the previous system has a possibility of cavitation when one or more control valves are closed.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.135-141
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• 2018

Wireless sensor networks (WSN) are composed of a large number of sensor nodes. Battery-powered sensor nodes have limited coverage; therefore, it is more efficient to transmit data via multi-hop communication. The network lifetime is a crucial issue in WSNs and the multi-hop routing protocol should be designed to prolong the network lifetime. Prolonging the network lifetime can be achieved by minimizing the power consumed by the nodes, as well as by balancing the power consumption among the nodes. A power imbalance can reduce the network lifetime even if several nodes have sufficient (battery) power. In this paper, we propose a routing protocol that prolongs the network lifetime by balancing the power consumption among the nodes. To improve the balance of power consumption and improve the network lifetime, the proposed routing scheme adaptively controls the transmission range using a power control according to the residual power in the nodes. We developed a routing simulator to evaluate the performance of the proposed routing protocol. The simulation results show that the proposed routing scheme increases power balancing and improves the network lifetime.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.52-58
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• 2009

In this paper, we propose a probability method to determine minimum capacity of energy storage system(ESS) for Micro-grid Because of high capital cost of ESS, It's very important to determine optimal capacity of ESS and for stable operation of Micro grid(MG), we should determine minimum capacity of ESS. The proposed method has abilities to consider forced outage rate of generators and intermittent of non-dispatchable generators and minimum capacity make MG keep energy balancing by oneself.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3496-3514
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• 2015

One of the challenging tasks in Mobile Ad hoc Network is to discover precise optimal routing solution due to the infrastructure-less dynamic behavior of wireless mobile nodes. Ant Colony Optimization, a swarm Intelligence technique, inspired by the foraging behaviour of ants in colonies was used in the past research works to compute the optimal path. In this paper, we propose a Recurrent Ant Colony Optimization (RECACO) that executes the actual Ant Colony Optimization iteratively based on recurrent value in order to obtain an optimal path convergence. Each iteration involves three steps: Pheromone tracking, Pheromone renewal and Node selection based on the residual energy in the mobile nodes. The novelty of our approach is the inclusion of new pheromone updating strategy in both online step-by-step pheromone renewal mode and online delayed pheromone renewal mode with the use of newly proposed metric named ELD (Energy Load Delay) based on energy, Load balancing and end-to-end delay metrics to measure the performance. RECACO is implemented using network simulator NS2.34. The implementation results show that the proposed algorithm outperforms the existing algorithms like AODV, ACO, LBE-ARAMA in terms of Energy, Delay, Packet Delivery Ratio and Network life time.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.292-300
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• 2013

Nowadays, energy saving has become a hot topic and information and communication technology has become a major power consumer. In long term evolution advanced (LTE-A) networks, heterogeneous deployments of low-power nodes and conventional macrocells provide some new features, such as coverage extension, throughput enhancement, and load balancing. However, a large-scale deployment of low-power nodes brings substantial energy consumption and interference problems. In this paper, we propose a novel switching strategy (NS), which adaptively switches on or off some low-power nodes based on the instantaneous load of the system. It is compatible with the microcells' load balancing feature and can be easily implemented on the basis of existing LTE-A specifications. Moreover, we develop an analytical model for analyzing the performance of system energy consumption, block rate, throughput, and energy efficiency. The performance of NS is evaluated by comparison with existing strategies. Theoretical analysis and simulation results show that NS not only has a low block rate, but also achieves a high energy efficiency.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.1093-1094
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• 2005

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.587-591
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• 2003

This study develops a neural network for solving optimization problems. Hopfield network has been used for such problems, but it frequently gives abnormal solutions or non-optimal solutions. Moreover, it takes much time for solving a solution. To overcome such disadvantages, this study adopts a neural network whose output nodes change with a small value at every evolution, and the proposed neural network is applied to solve ALB (Assembly Line Balancing) problems . Given a precedence diagram and a required number of workstations, an ALB problem is solved while achieving even distribution of workload among workstations. Here, the workload variance is used as the index of workload deviation, and is reflected to an energy function. The simulation results show that the proposed neural network yields good results for solving ALB problems with high success rate and fast execution time.