• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.126-127
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• 2017

An accurate State Of Charge (SOC) estimation of battery is the most important technique for Electric Vehicles (EVs) and Energy Storage Systems (ESSs). In this paper a new integrated Unscented Kalman Filter-Particle Filter (UKF-PF) is employed to estimate the SOC of a $LiFePO_4$ battery cell and a significant improvement is obtained as compared to the other methods. The parameters of the battery is modeled by the second order Auto Regressive eXogenous (ARX) model and estimated by using Recursive Least Square (RLS) method to calculate value of each element in the model. The proposed algorithm is established by combining a parameter identification technique using RLS method with ARX model and an SOC estimation technique using UKF-PF.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.5
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• pp.490-496
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• 2023

Unmanned aerial vehicles (UAVs) research is recently actively underway. Especially, fuel cell battery hybrid systems are widely used to overcome the limitations of continuous operation. However, fuel cell systems must be operated in combination with a battery due to their low specific output characteristics. Therefore, a hybrid power system model for UAVs is developed. The rule-based strategy is applied to the model to properly distribute power to batteries and fuel cells. As a result, the designed rule-based power distribution control operates UAVs while maintaining battery state of charge(SOC) at an appropriate level.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.126-131
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• 2015

When a battery is discharging, the battery's current and terminal voltage must both be measured to estimate its state of charge (SOC). If the SOC can be estimated by using only the current or voltage, hardware costs will decrease. This paper proposes an SOC estimation algorithm that needs to measure only the terminal voltage while a battery is discharging. The battery's SOC can be deduced from its open circuit voltage (OCV) through the relationship between SOC and OCV. But when the battery is discharging, it is not possible to measure the OCV due to the voltage drop in the battery's internal resistance (IRdrop). The proposed algorithm calculates OCV by estimating IRdrop using a dynamic terminal voltage measurement. This paper confirms the results of applying the algorithm in a hardware environment via algorithm binarization. To evaluate the algorithm, a Simulink battery model based on actual values was used.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.4
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• pp.303-310
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• 2020

Estimating the accurate internal state of lithium ion batteries to increase their safety and efficiency is crucial. Various algorithms are used to estimate the internal state of a lithium ion battery, such as the extended Kalman filter and sliding mode observer. A state-space model is essential in using algorithms to estimate the internal state of a battery. Two principal methods are used to express the state-space model, namely, continuous time and discrete time. In this work, the extended Kalman filter is employed to estimate the internal state of a battery. Moreover, this work presents and analyzes the estimation performance of algorithms consisting of a continuous time state-space model and a discrete time state-space model through static and dynamic profiles.

• Journal of the military operations research society of Korea
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• v.23 no.2
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• pp.155-170
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• 1997

Currently, increasing the number of artillery units requires more deployment space in FABA. However, available positions of artillery units in FEBA is limited due to mountainous terrains. Therefore, it is hard to find enough artillery position space in accordance with the field artillery mannual. This paper studies on determination of the size of battery position in order to maximize the firing-effectiveness and to minimize the enemy threat. Also, it studies the possibility of reducing the size of a battery position. The optimum size of a battery position id obtained by using Dantzig's model and Supper Quick II model which produces the probability of kill data with various input data. As a result, it shows that the size of battery position can be reduced without decreasing the firing-effectiveness.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.6
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• pp.532-538
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• 2012

This paper proposes the Mathematical Modeling for HEV High-power Lithium-Polymer Battery. The nonlinear system of the Lithium Battery electrical characteristic express mathematical state equation. We also test charge/discharge and temperature experimental used to identify parameters of the cell find parameter of the least error. The proposed model experimental results is used with battery cycler to verify of the proposed model.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.1
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• pp.123-128
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• 2006

The proposed mathematical model of the starter-generator system incorporates the motor speed, battery voltage and the desired current to estimate the moment generation capabilities of the starter-generator and the actual current of the battery system. The fundamentals for this mathematical modeling are the simulated results of the experimental data. These pertinent data are used in establishing the governing equations for the determination of motor moments, actual battery currents and efficiencies of the system's operation at different loading characteristics and speed regions. The derived equations will be used into simulation programs to predict the fuel efficiency, vehicle characteristics of a hybrid electric vehicle equipped with a transmission starter-generator which will be developed.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.3
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• pp.227-234
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• 2020

This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.

• Journal of the military operations research society of Korea
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• v.18 no.1
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• pp.74-85
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• 1992

Increasing the number of artillery units requires more deployment space in the field operation area. However, there is limited space available in FEBA due to mountainous terrains. Therefore most artillery units cannot occupy enough deployment space which is proposed in the field artillery mannual(FM) to maximize the firing-effectiveness and to minimize the enemy threat. This paper studies the problems of reducing the size of a battery deployment space being applied currently without decreasing the firing-effectiveness of the battery. The optimum size of a battery position is obtained by using Lemus and David's allocation model and Supper Quick II Model which produces the probability of kill data with various input data. The result shows that the battery deployment space can be reduced without decreasing the firing-effectiveness in the example problem.

• Korean Journal of Chemical Engineering
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• v.36 no.1
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• pp.12-20
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• 2019

An energy storage system consisting of a battery and a power-to-methanol (PtM) unit was investigated to develop an energy storage system for renewable energy systems. A nonlinear programming model was established to optimize the energy storage system. The optimal installation capacities of the battery and power-to-methanol units were determined to minimize the cost of the energy system. The cost from a renewable energy system was assessed for four configurations, with or without energy storage units, of the battery and the power-to-methanol unit. The proposed model was applied to the modified electricity supply and demand based on published data. The results show that value-adding units, such as PtM, need be included to build a stable renewable energy system. This work will significantly contribute to the advancement of electricity supply and demand management and to the establishment of a nationwide policy for renewable energy storage.