• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.805-811
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• 2021

Currently, batteries use commonly as energy sources for mobile electric devices. Due to the high density of energy, the energy storage state of a battery is very important information. To know the battery's energy storage state, it is necessary to find out the open state voltage of the battery. The open state voltage calculates with a mathematical model, but the computation of the real time state is complicated and requires many calculations. Therefore, the state observer designs to estimate in real time the battery open-circuit voltage as disturbance including model error. Using the estimated open voltage and applying it to the state estimation algorithm, we can estimate the charge. In this study, we first estimate the open-circuit voltage and design an estimation algorithm for estimating the state of battery charge. This includes errors in the system model and has a robust characteristic to noise. It is possible to increase the precision of the charge state estimation.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.851-858
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• 2021

In general, secondary batteries are widely used as an electric energy source. Among them, the state of energy storage of mobile devices is very important information. As a method of estimating a state, there is a method of estimating the state by integrating the current according to an energy storage state of a battery, and a method of designing a state estimator by measuring a voltage and estimating a charge amount based on a battery model. In this study, we designed the state estimator using an extended Kalman filter to increase the precision of the state estimation of the charge amount by including the error of the system model and having the robustness to the noise.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.11a
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• pp.350-351
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• 2005

The electrochemical behavior of Si-C material synthesized by heating the mixture of silicon and polyvinylidene fluoride (PVDF). Coin cells of the type 2025 were made using the synthesized material and the electrochemical studies were performed. Si-C/Li cells were made by using the developed Si-C material. Charge/discharge test was performed at 0.1C hour rate. Initial charge and discharge capacities at Si-C material derived from 20 wt.% of PVDF was found to be 1,830 and 526 mAh/g respectively. Initial charge/discharge characteristics of the electrode were analyzed. The level of reversible specific capacity was about 216 mAh/g at Si-C material derived from 20 wt.% of PVDF, IIE, intercalation efficiency at initial charge/discharge, was 68 %. Surface irreversible specific capacity was 31 mAh/g, and average specific resistance was 2.6 ohm*g.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.12
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• pp.74-83
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• 2014

This paper proposes a study on the configuration of balancing of plant(BOP) and implementation of battery management system(BMS) functions for vanadium redox flow battery(VRFB) and propose a method consists of sensor and required design specifications BOP system configuration. And it proposes an method of the functions implementation and control algorithm of the BMS for flow battery. Functions of BMS include temperature control, the charge and discharge control, flow control, level control, state of charge(SOC) estimation and a battery protection through the sensor signal of BOP. Functions of BMS is implemented by the sensor signal, so it is recognized as a very important factor measurement accuracy of the data. Therefore, measuring a mechanical signal(flow rate, temperature, level) through the BOP test model, and the measuring an electrical signal(cell voltage, stack voltage and stack current) through the VRFB charge-discharge system and analyzes the precision of data in this paper. Also it shows a good charge-discharge test results by the SOC estimation algorithm of VRFB. Proposed BOP configuration and BMS functions implementation can be used as a reference indicator for VRFB system design.

• Proceedings of the KIPE Conference
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• 2018.11a
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• pp.36-38
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• 2018

As the battery capacity requirement increases, battery cells are connected in a parallel configuration. However, the sharing current of each battery cell becomes unequal due to the imbalance between cell's impedance which results the mismatched states of charge (SOC). The conventional fixed-resistance balancing methods have a limitation in battery equalization performance and system efficiency. This paper proposes a battery equalization method based on dynamic resistance technique, which can improve equalization performance and reduce the loss dissipation. Based on the SOC rate of parallel connected battery cells, the switches in the equalization circuit are controlled to change the equivalent series impedance of the parallel branch, which regulates the current flow to maximize SOC utilization. To verify the method, operations of 4 parallel-connected 18650 Li-ion battery cells with 3.7V-2.6Ah individually are simulated on Matlab/Simulink. The results show that the SOCs are balanced within 1% difference with less power dissipation over the conventional method.

• KIEE International Transactions on Electrophysics and Applications
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• v.4C no.1
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• pp.21-25
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• 2004

From the gradual increasing state of charge (GISOC) observations, electrochemical behavior of multi-walled carbon nanotube│(lM LiP $F_{6}$ , EC,DEC,DME 3:5:5 volume ratio)│lithium cells was evaluated using the galvanostatic charge-discharge process. A MWCNT delivers a specific charge capacity of 1,300 mAh/g in a Li cell when cycled up to an end voltage of 0 V (vs. Li/L $i^{＋}$ )at a constant current rate every 10 hours. However, in the present study, the specific discharge capacity obtained is 338 mAh/g, thus amounting to a coulombic efficiency of only 26％. Further, when the MWCNT│Li cells were tested using the GISOC method, two distinguishable linear-fit ranges were observed due to the intercalation/deintercalation of lithium, which were found to have II $E_1$, IIC $s_1$ and II $E_2$of 27.3％, 372 mAh/g, and 25.5％, respectively. Q $c_1$, could be calculated from the data of IIE and IICs of each range by the modified equation "II $C_{sum}$= $\Sigma$( $Q_{C}$- $Q_{D}$)=(II $E_{1}$$^{-1}$ ) $Q_{Dl}$ ＋(II $E_2$$^{-1}$ -1) ( $Q_{D2}$- $Q_{Dl}$ ) ＋ IIC $s_1$= $Q_{Cl}$ - $Q_{Dl}$ ". Results of the GISOC method could be converted to the results of galvanostatic charge-discharge process, irrespective of the state of charge of the cell or battery.ery.y.y.

• 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.

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.62-62
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• 2006

Based on the redox couples of a nitroxide radical, organic radical polymers were utilized as the electrode-active or charge-storage component for a secondary battery. We call a battery composed of the radical polymer electrode as "organic radical battery". Organic radical battery has several advantages: high capacity, high power-rate performance, long cycle ability, and environmentally-benign features. Synthesis and electrochemical studies of nitroxide polymers are described. Battery fabrication and cell performance are also reported.

• Smart Media Journal
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• v.9 no.1
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• pp.84-91
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• 2020

Along with increasing the renewable energy utilization, many researches have paid attention on the utilization and efficiency of energy storage systems. Especially, it is required an operational model in order to actively respond with each system's failure of sub-systems in the solar energy storage system. This paper proposes an energy management scheme by estimating the newly generated power based on the solar power generation samples. With comparing the estimated battery charging power in real time and the total charging power of the battery rack, a charge model is applied to adjust the charging power, As a result, the stability of energy storage system would be improved by suppressing the battery heat while maintaining battery C-Rate.

• Journal of IKEEE
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• v.24 no.1
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• pp.333-338
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• 2020

This paper proposes a method of estimating the SOC(State of Charge) of a battery cell using a neural network algorithm. To this, we implement a battery SOC estimation simulator and derive input and output data for neural network learning through charge and discharge experiments at various temperatures. Finally, the performance of the battery SOC estimation is analyzed by comparing with the experimental value by Ah-counting using Matlab/Simulink program and confirmed that the error rate can be reduced to less than 3%.