• 전기학회논문지
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• 제60권10호
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• pp.1875-1880
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• 2011

This paper proposes a battery model applicable to Autonomie environment. Also, a various of experiment is implemented for validation. The proposed battery model modifies Randles equivalent circuit and battery parameters are extracted from pulsed current tests. The parameters are two-dimensional function of current and SOC(State of Charge). The battery model is developed in the Matlab/Simulink and is implemented for NiMH Panasonic HHR650D and compared with pulsed current discharge curves. The simulation results validate the accuracy of the proposed model and the model is also tested by adding it on Autonomie for HEV application. Constant current charge/discharge, pulsed current test that can be used to extract battery parameter are performed and test results are used to build up the proposed battery model for Autonomie.

• 제어로봇시스템학회논문지
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• 제14권9호
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• pp.904-908
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• 2008

Every autonomous system like a robot needs a power source known as a battery. And proper management of the battery is very important for proper operation. To know State of Charge(SOC) of a battery is the very core of proper battery management. In this paper, the SOC estimation problem is tackled based on the well known Extended Kalman Filter(EKF). Combined the existing battery model is used and then EKF is employed to estimate the SOC. SOC table is constructed by extensive experiment under various conditions and used as a true SOC. To verify the estimation result, extensive experiment is performed with various loads. The comparison result shows the battery estimation problem can be well solved with the technique proposed in this paper. The result of this paper can be used to develop related autonomous system.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2008년도 하계학술대회 논문집
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• pp.413-415
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• 2008

The charge equalizer design for a series connected battery string is very challenging because it needs to satisfy many requirements such as implementation possibility, equalization speed, equalization efficiency, controller complexity, size and cost issues, voltage and current stress, and so on. Numerous algorithms and circuits were developed to meet the above demands and some interesting results have been obtained through them. However, for a large number of cells, for example, eighty or more batteries, the previous approaches might cause problems. Such problems include long equalization time, high controller complexity, bulky size, high implementation cost, and high voltage and current stress. To overcome these circumstances, this paper proposes a charge equalizer design method based on a battery modularization technique. In this method, the number of cells that we consider in an equalizer design procedure can be effectively reduces; thus, designing a charge equalizer becomes much easier. Furthermore, by applying the previously verified charge equalizers to the intramodule and the outer-module, we can obtain easy design of a charge equalizer and good charge balancing performance. Several examples and experimental results are presented to demonstrate the usefulness of the charge equalizer design method.

• 대한임베디드공학회논문지
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• 제11권5호
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• pp.305-312
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• 2016

Modern embedded systems are typically operated by the rechargeable batteries in our daily life. Since charge of batteries is considered as an time consuming task, there have been extensive efforts to manage the charge time from the perspective of materials, circuits, and systems. Estimation of battery charge time is one of the essential information to design the charge circuitry. A compact macro model for the constant-current and constant-voltage charge protocol was recently introduced, which gives us a quick estimation of charge time with similar shape to the famous Peukert's law for discharge time estimation. The CC-CV charging protocol is widely used for Lithium-based batteries and Lead-acid batteries. In this paper, we characterize the lead-acid battery by measurement to extract the model coefficients, which was not covered by the previous studies. By our proposed model, the key coefficient Kcc results in 1.18-1.31, which is little bit higher than that of Lithium batteries. The accuracy of our model is within the range of ${\pm}10%$ error, which is compatible with the other studies such as Peukert's law.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1927-1934
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• 2018

In this paper, we studied the state of charge (SOC) estimation algorithm of a high-capacity lithium secondary battery for electric vehicles (EVs) considering temperature characteristics. Nonlinear characteristics of high-capacity lithium secondary batteries are represented by differential equations in the mathematical form and expressed by the state space equation through battery modeling to extract the characteristic parameters of the lithium secondary battery. Charging and discharging equipment were used to perform characteristic tests for the extraction of parameters of lithium secondary batteries at various temperatures. An extended Kalman filter (EKF) algorithm, a state observer, was used to estimate the state of the battery. The battery capacity and internal resistance of the high-capacity lithium secondary battery were investigated through battery modeling. The proposed modeling was applied to the battery pack for EVs to estimate the state of the battery. We confirmed the feasibility of the proposed study by comparing the estimated SOC values and the SOC values from the experiment. The proposed method using the EKF is expected to be highly applicable in estimating the state of the high-capacity rechargeable lithium battery pack for electric vehicles.

• 한국정보기술학회논문지
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• 제18권5호
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• pp.55-64
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• 2020

태양광 시스템의 안정성과 신뢰성 향상을 위해서는 배터리의 잔존량 (State of Charge, SOC)을 정확하게 추정하여야 한다. 본 연구에서는 gradient descent, Levenberg-Marquardt 및 scaled conjugate gradient 학습방법을 사용한 인공 신경회로망 (Artificial Neural Networks, ANN)과 적응형 뉴로-퍼지 추론 시스템 (Adaptive Neuro-Fuzzy Inference System, ANFIS)을 사용한 SOC 추정방법을 제안한다. 입력으로는 충전 시작 전압 및 적류적산법을 통해 구한 충전 전류를 사용하여 추정된 SOC를 출력한다. 4개의 모델 (ANN-GD, ANN-LM, ANN-SCG, 및 ANFIS)을 사용하여 SOC 추정 방법을 구현하였고 실험을 통해 MATLAB을 사용하여 4개의 모델의 성능을 비교 분석하였다. 실험 결과로부터 ANFIS 모델을 사용한 배터리의 SOC 추정이 가장 정확도가 높았으며 빠른 속도로 수렴함을 확인하였다.

• Journal of Electrochemical Science and Technology
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• 제15권3호
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• pp.414-420
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• 2024

Lithium-ion batteries are widely used in many applications due to their high energy density, high efficiency, and excellent cycle ability. Once an unknown Li-ion battery is reusable, it is important to measure its lifetime and state of health. The most favorable measurement method is the cycle test, which is accurate but time- and capacity-consuming. In this study, instead of a cycle test, we present an empirical model based on the C-rate test to understand the state of health of the battery in a short time. As a result, we show that the partially accelerated charge/discharge condition of the Li-ion battery is highly effective for the degradation of battery capacity, even when half of the charge/discharge conditions are the same. This observation provides a measurable method for predicting battery reuse and future capacity degradation.

• 한국태양에너지학회 논문집
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• 제34권4호
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• pp.123-129
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• 2014

Photovoltaic and fuel cell systems can be used as power source in mobile robots. At this time the photovoltaic system generally generate power in daytime. The starting time of fuel cell is slower than the lithium battery. To compensate for these disadvantages, a battery charge-discharge system is used. Especially the bi-directional converter is used mainly in the charge-discharge method. The controller in a buck converter controls the input voltage of the converter to meet the maximum power point tracking(MPPT) performance. First of all, the simulations of hybrid system for battery charge-discharge system in each step simulated using solar and fuel cell modeling as input source in PSIM. Experiment of the buck and bi-directional converter system is conducted through using photovoltaic/fuel cel simulator(pCube) instead of solar and fuel cell. This hybrid system for battery charge discharge using photovoltaic/fuel cell generates emergency power for the communication system in mobile robot.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1999년도 춘계학술대회 논문집
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• pp.362-365
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• 1999

The electrochemical properties of flyash obtained from combustion of fuel in fossil power plants and their performance as anode material of secondary battery have been investigated Various flysh pellets molded at various molding pressure have been used as anode lithium secondary battery. The best Performance was achieved when flyash pellet molded at pressure of 400kgf/$\textrm{cm}^2$ is utilized, that is, charge capacity of 300kgf/$\textrm{cm}^2$ and Coulombic efficiency of larger than 95% have been achieved. In addition, this battery exhibited good cycling performance. Considering these results, we predicted that utilization of the flyash as anode material and polyaniline conducting polymer as cathode material in a secondary will show capacity of 300mAh/g and Coulombic efficiency of higher than 95%.

• Journal of Power Electronics
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• 제18권1호
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• pp.129-136
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• 2018

An accurate state-of-charge (SOC) estimation ensures the reliable and efficient operation of a lithium-ion battery management system. On the basis of a combined electrochemical model, this study adopts the forgetting factor least squares algorithm to identify battery parameters and eliminate the influence of test conditions. Then, it implements online SOC estimation with high accuracy and low run time by utilizing the low computational complexity of the unscented Kalman filter (UKF) and the rapid convergence of a particle filter (PF). The PF algorithm is adopted to decrease convergence time when the initial error is large; otherwise, the UKF algorithm is used to approximate the actual SOC with low computational complexity. The effect of the number of sampling particles in the PF is also evaluated. Finally, experimental results are used to verify the superiority of the combined method over other individual algorithms.