• 한국지능시스템학회논문지
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• 제25권3호
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• pp.299-305
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• 2015

Global environmental concerns and the ever increasing need of energy, coupled with steady progress in renewable energy technologies, are opening up new opportunities for utilization of renewable energy resources. Distributed electricity generation is a suitable option for sustainable development thanks to the load management benefits and the opportunity to provide electricity to remote areas. Solar energy being easy to harness, non-polluting and never ending is one of the best renewable energy sources for electricity generation in present and future time. Due to the random and intermittent nature of solar source, PV plants require the adoption of an energy storage and management system to compensate fluctuations and to meet the energy demand during night hours. This paper presents an efficient, economic and technical model for the design of a MPPT based grid connected PV with battery storage and management system. This system satisfies the energy demand through the PV based battery energy storage system. The aim is to present PV-BES system design and management strategy to maximize the system performance and economic profitability. PV-BES (photovoltaic based battery energy storage) system is operated in different modes to verify the system feasibility. In case of excess energy (mode 1), Li-ion batteries are charged using CC-CV mechanism effectively controlled by fuzzy logic based PID control system whereas during the time of insufficient power from PV system (mode 2), batteries are used as backup to compensate the power shortage at load and likewise other modes for different scenarios. This operational mode change in PV-BES system is implemented by State flow chart technique based on SOC, DC bus voltages and solar Irradiance. Performance of the proposed PV-BES system is verified by some simulations study. Simulation results showed that proposed system can overcome the disturbance of external environmental changes, and controls the energy flow in efficient and economical way.

• 전기학회논문지
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• 제56권10호
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• pp.1763-1769
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• 2007

To improve the cycle-life and efficiency of an energy storage system for HEV, a dynamic control system consisted of a switch between a battery and an ultracapacitor module is proposed, which is appropriate for mild hybrid vehicle with 42V power net. The switch can be controlled based on the status of the battery and the ultracapacitor module, and a control algorithm that could largely decrease the number of high charging current peak is also implemented. Therefore the cycle life of the battery can be improved such that it is suitable for a mild hybrid vehicle with frequent engine start-stop and regenerative-braking. Also, by maximizing the use of the ultracapacitor, the system efficiency during high current charging and discharging operation is improved. Finally, this system has the effects that improves the efficiency of energy storage system and reduces the fuel consumption of a vehicle. To verify the validity of the proposed system, this paper presented cycles test results of different energy storage systems: a simple VRLA battery, hybrid energy Pack (HEP, a VRLA battery in Parallel with Ultracapacitor) and a HEP with a switch that controlled by energy management system (EMS). From the experimental result, it was proved the effectiveness of the algorithm.

• 한국자동차공학회논문집
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• 제23권2호
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• pp.153-160
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• 2015

Hybrid Electric Vehicles(HEVs) have seriously come into prevalence recently as car manufacturers and consumers have become more aware of the environmental and economic problems of conventional vehicles. For the alternative power-train and battery cooling systems in HEVs, an effective thermal management system is required, and many automakers are interested in using Brushless DC(BLDC) motors for cooling fans for the overall traction unit's performance and energy saving capability. This paper presents the development status of BLDC motors as major parts of the power-train, i.e. the engine cooling and battery cooling fans of HEVs. A design that uses BLDC motors for the power-train and each battery cooling fan, is successfully implemented through using electro-magnetic analysis, and prototype BLDC motors are examined. As experimental results, the BLDC motors achieved an efficiency of 85% as engine cooling fans and 72% as a battery thermal management fan motor. The electric cogging noise is significantly reduced by changing the skew of the slot pitch angle and optimizing the magnetic shape.

• 전기전자학회논문지
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• 제24권2호
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• pp.610-618
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• 2020

본 논문에서는 규칙기반 알고리즘을 이용한 수소연료전지/배터리 하이브리드 철도차량 모델링을 제시한다. 모터의 운전영역에 따른 토크 곡선을 계산하여 견인 시스템의 구동 전력을 결정하고 철도차량의 각 운전 모드에 적용하여 전기 시스템을 모델링 한다. 전기 시스템의 전력은 규칙기반 알고리즘을 이용한 에너지 관리시스템(Energy Management System, EMS)으로 결정한다. 배터리의 충전상태(State Of Charge, SOC)에 따라 운전 영역을 세분화하여 수소 소비량을 효율적으로 관리한다. 제안하는 철도차량 모델링의 타당성은 MATLAB/Simulink 시뮬레이션을 통해 검증한다.

• 전기학회논문지
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• 제64권7호
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• pp.992-998
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• 2015

The ESS is composed of Battery Package, PCS(Power Conditioning System) Package, BCU(BESS Control Unit). In Jeju smart grid test-bed, we have developed a business model by ESS power system, renewable energy, transportation, such as customers, and have demonstrated above things. We have analyzed the EMS(Energy Management System) model of KPX where manages supply and demand of domestic electrical power system. We modified and launched EMS for microgrid but the cost was expensive and the system was large size. For releasing this system from industry as a whole, it is imperative to develop PMS(Power Management System) for microgrid. However, the cost of EMS for microgrid is expensive, some systems because it is a large development of the all of the first fruits in urgent PMS(Power Management System) for microgrid to be used in industry in general. Therefore, in this paper, we propose the ESS model considering the power systems characteristics and extensibility in korea. and also we propose the PMS to manage the ESS systems.

• 전력전자학회논문지
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• 제25권5호
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• pp.376-384
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• 2020

An energy storage system is composed of lithium-ion batteries in modern applications. Batteries are regarded as storage devices for renewable and residual energy. The failure of batteries can cause the performance reduction and explosion of battery systems. High maintenance cost is essential when dealing with the problem of battery safety. Therefore an accurate health diagnosis is required to ensure the high reliability of battery systems. A battery pack is a combination of single cells in series and parallel connections. A battery pack has to consider various factors to assess battery health. Battery health involves conventional factors and additional factors, such as cell-to-cell imbalance. For large applications, state-of-health (SOH) can be inaccurate because of the lack of factors that indicate the state of the battery pack. In this study, six characterization factors are proposed for improving the SOH estimation of battery packs. The six proposed characterization factors can be regarded as health indicators (HIs). The six HIs are applied to the principal component analysis (PCA) algorithm. To reflect information regarding capacity, voltage, and temperature, the PCA algorithm extracts new degradation factors by using the six HIs. The new degradation factors are applied to a multiple regression model. Results show the advancement and improvement of SOH estimation.

• 한국정보통신학회논문지
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• 제25권5호
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• pp.709-718
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• 2021

최근 선박의 환경오염에 대한 규제가 강화됨에 따라 하이브리드형 전력체계를 갖춘 전기 추진 선박과 같은 스마트 선박에 대한 관심이 높아지고 있다. 전기추진선박에서 사용되는 배터리는 차량 등에 사용되는 배터리보다 용량이 크므로, 가격이 높아지고 유지 보수 측면이 중요하게 여겨진다. 선박용 배터리는 일체형으로 제작되어 배터리관리 시스템에 의해 관리되며, 배터리의 유지·보수는 배터리의 교체를 통하여 이루어진다. 본 연구에서는 배터리의 용이한 관리를 위해서 예비-셀을 적용한 배터리 모듈과 제어 알고리즘을 설계 및 구현한다. 또한, 전기추진선박 전력 체계 제어에 필요한 데이터를 전력 제어 시스템에 송신 할 수 있도록 제어기를 설계한다. 해당 예비-셀을 적용한 배터리를 사용할 경우 선박 및 배터리 시스템의 안정성이 높아지며, 유지 및 보수 측면에서 이점을 가질 수 있다.

• 한국전자통신학회논문지
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• 제18권3호
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• pp.405-412
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• 2023

드론 및 ICT 융합 기술의 발전에 따라 기존 잠수사가 담당하고 있던 수중 현황 탐색, 수중 구조물 검사 등의 작업을 수중 드론으로 대체하고 낚시를 위한 수중 탐사 등의 레저용 수중 드론, 다리 교각 등 산업용 등의 수중 드론의 활용성이 증대되고 있다. 기존 모터 컨트롤러는 항공 드론에 적합하며 수중 드론 전용 BLDC 모터 컨트롤러의 개발을 통해 수중 드론의 완성도와 모터 컨트롤에 대한 신뢰도를 높일 수 있다. 수중 드론 전용 배터리 관리 시스템(BMS)의 개발을 통해 충전 상태 확인, 방전 상태 확인, 셀 밸런싱 조정, 고전압 보호 기능 구현으로 배터리 안정성을 확보하였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 전력전자학술대회 논문집
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• pp.309-310
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• 2016

Sealed flooded lead acid batteries are becoming popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation has always been an important factor in battery management systems. For the accurate SOC estimation, open circuit voltage (OCV) hysteresis should be modelled accurately. The hysteresis phenomenon of the sealed flooded lead acid battery is discussed in detail and its ultimate modeling is proposed based on the conventional parallelogram method. The SOC estimation is performed by using Unscented Kalman Filter (UKF) while the parameters of the battery are estimated using Auto Regressive with external input (ARX) method. The validity of the proposed method is verified by the experimental results. The SOC estimation error by the proposed method is less than 3 % all wing the 125hr test.

• Journal of Power Electronics
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• 제14권5호
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• pp.1038-1046
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• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.