• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.4
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• pp.324-331
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• 2007

This paper studies new estimation method for state of charge (SOC) of the hybrid electric vehicle lithium battery using sliding mode observer. A simple R-C Lithium battery modeling technique is established and the errors caused by simple modeling was compensated by the sliding mode observer. The structure of the sliding mode observer is simple, but it shows robust control property against modeling errors and uncertainties. The performance of the system has been verified by the UUDS test. The test results of the proposed observer system shows robust tracking performance under real driving environments.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.271-272
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• 2012

전류 적산법(Coulomb counting, ampere counting)을 이용한 배터리 SOC(State-of-Charge) 추정 방법은 상용화된 IC를 사용할 수 있기에 구현이 간단하고 SOC 정의를 통해 배터리 사용 가능한 시간을 쉽게 예측할 수도 있다. 하지만 초기 SOC 오류와 누적되는 전류 정보의 오차로 인해 추정이 실패하는 단점이 존재하기 때문에 이를 해결해주는 알고리즘이 필요하다. 본 논문에서는 전류 적산법 기반의 배터리 SOC 추정 회로에 확장 칼만 필터(EKF, Extended Kalman Filter)를 접목하여 전류 적산법을 이용하였을 때 나타날 수 있는 오차 누적을 줄이는 알고리즘을 제안한다. 또한 실험을 통해 제안된 배터리 SOC 추정 회로의 성능을 확인해본다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.15-23
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• 2017

This paper reports a SOC(State-of-Charge) estimation method using the extended Kalman filter(EKF) algorithm, which can allow real-time implementation and reduce the error of the model and be robust against noise, to accurately estimate and evaluate the charging/discharging state of the EV(Electric Vehicle) battery. The battery was modeled as the first order Thevenin model for the EKF algorithm and the parameters were derived through experiments. This paper proposes the changed method, which can have the SOC to 0% ~ 100% regardless of the aging of the battery by replacing the rated capacity specified in the battery with the maximum chargeable capacity. In addition, This paper proposes the EKF algorithm to estimate the non-linearity interval of the battery and simulation result based on Ah-counting shows that the proposed algorithm reduces the estimation error to less than 5% in all intervals of the SOC.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.182-186
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• 2007

This paper studied performance characteristics of hybrid automotive to replace existing fossil fuel vehicles. Specially, about power split type HEV that is T-HEV's drive system when a vehicle drives at steady speed, monitored both output of each engine, motor and generator and battery SOC (state of charge) and analyzed performance characteristic of power transmission system and electricity power parts. This study shows those that acquired and analyzed information from signals between HCU and each controller of actual T- vehicle. From this study, it is confirmed that each conditions of EV and HEV drive can be a improvement with respect to the fuel efficiency of vehicles.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1072-1079
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• 2014

This paper introduces a coordinated droop control for the stand-alone DC micro-grid, which is composed of photo-voltaic generator, wind power generator, engine generator, and battery storage with SOC (state of charge) management system. The operation of stand-alone DC micro-grid with the coordinated droop control was analyzed with computer simulation. Based on simulation results, a hardware simulator was built and tested to analyze the performance of proposed system. The developed simulation model and hardware simulator can be utilized to design the actual stand-alone DC micro-grid and to analyze its performance. The coordinated droop control can improve the reliability and efficiency of the stand-alone DC micro-grid.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.87-88
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• 2010

주위온도, 사용연한 및 운전점 등에 의해서 동작특성이 변화되는 배터리의 SOC(State of Charge)를 정확하게 추정하는 것은 매우 어려운 과제이다. SOC를 추정하기 위해서는 배터리의 복잡한 비선형적인 특성을 고려한 등가 모델의 개발이 필요하다. 본 논문은 SOC 추정을 위해 최근까지 수행되었던 연구를 검토하고, SOC 추정을 위해 개발된 배터리 모델 및 추정기법을 비교 분석하고, PSIM 시뮬레이션 연구 결과를 제시한다.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.244-245
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• 2012

본 논문에서는 이산 웨이블릿 변환(DWT;discrete wavelet transform)의 다해상도 분석(MRA;multi-resolution analysis)을 통해 분해된 배터리의 저주파 전압 성분(approximation;$A_n$) 기반 SOC(State-of-charge) 추정방법을 소개한다. 급격한 전압 변화의 특성을 나타내는 고주파 전압 성분(detail;$D_n$)이 제거되고 저주파 전압 성분만이 SOC 추정을 위해 사용된다. 이 경우 기존 확장 칼만필터(EKF;extended Kalman filter)에서 SOC 추정에러를 개선하기 위해 사용되었던 노이즈 모델의 생략이 가능하여 알고리즘의 복잡성이 개선된다. 개선된 확장 칼만필터 기반 SOC 추정 결과를 통해 제안된 방법을 검증하였다.

• Journal of IKEEE
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• v.22 no.2
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• pp.455-459
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• 2018

In this paper, proposed a multi-channel charging control strategy for electric vehicle. This control strategy can adjust the charging power according to the calculated state-of-charge (SOC). Electric vehicle (EV) charging system using Particle Swarm Optimization (PSO) algorithm is proposed. A stochastic optimization algorithm technique such as PSO in the time-of-use (TOU) price used for the energy cost minimization. Simulation results show that the energy cost can be reduced using proposed method.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.29-38
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• 2017

This paper presents a study on the state-of-charge (SOC) reference based active cell balancing in real-time. The optimal references of SOC are determined by using the proposed active cell balancing system with the bidirectional DC/DC converters via the dual active bridge (DAB) type. Then, the energies between cells can be balanced by the power flow control of DAB based bidirectional DC/DC converters. That is, it provides the effective management of battery by transferring energy from the strong cell to the weak one until the cell voltages are equalized to the same level and therefore improving the additional charging capacity of battery. In particular, the cell aging of battery and power loss caused from energy transfer are considered. The performances of proposed active cell balancing system are evaluated by an electromagnetic transient program (EMTP) simulation. Then, the experimental prototype is implemented in hardware to verify the usefulness of proposed system.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.99-107
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• 2017

This paper proposes a battery model coefficient correction method for improving the accuracy of existing lithium battery equivalent models. BMS(battery management system) has been researched and developed to minimize shortening of battery life by keeping SOC(state of charge) and state of charge of lithium battery used in various industrial fields such as EV. However, the cell balancing operation based on the battery cell voltage can not follow the SOC change due to the internal resistance and the capacitor. Various battery equivalent models have been studied for estimation of battery SOC according to the internal resistance of the battery and capacitors. However, it is difficult to apply the same to all the batteries, and it tis difficult to estimate the battery state in the transient state. The existing battery electrical equivalent model study simulates charging and discharging dynamic characteristics of one kind of battery with error rate of 5~10% and it is not suitable to apply to actual battery having different electric characteristics. Therefore, this paper proposes a battery model coefficient correction algorithm that is suitable for real battery operating environments with different models and capacities, and can simulate dynamic characteristics with an error rate of less than 5%. To verify proposed battery model coefficient calibration method, a lithium battery of 3.7V rated voltage, 280 mAh, 1600 mAh capacity used, and a two stage RC tank model was used as an electrical equivalent model of a lithium battery. The battery charge/discharge test and model verification were performed using four C-rate of 0.25C, 0.5C, 0.75C, and 1C. The proposed battery model coefficient correction algorithm was applied to two battery models, The error rate of the discharge characteristics and the transient state characteristics is 2.13% at the maximum.