• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1759-1768
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• 2018

The energy density, power density and ohm resistance of battery change significantly as results of battery aging, which lead to decrease in the accuracy of the equivalent model. A parameter identification method of the equivale6nt circuit model with 3 R-C branches based on the test database of battery life cycle is proposed in this paper. This database is built on the basis of experiments such as updating of available capacity, charging and discharging tests at different rates and relaxation characteristics tests. It can realize regular update and calibration of key parameters like SOH, so as to ensure the reliability of parameters identified. Taking SOH, SOC and T as independent variables, lookup table method is adopted to set initial value for the parameter matrix. Meanwhile, in order to ensure the validity of the model, the least square method based on variable forgetting factor is adopted for optimizing to complete the identification of equivalent model parameters. By comparing the simulation data with measured data for charging and discharging experiments of Li-ion battery, the effectiveness of the full life cycle database and the model are verified.

• 한국전기화학회:학술대회논문집
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• 한국전기화학회 2001년도 전지기술심포지움
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• pp.145-161
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• 2001

Novel characterization of thermal properties of a battery has been introduced by defining its frequency-dependent thermal impedance function. Thermal impedance function can be approximated as a thermal impedance spectrum by analyzing experimental temperature transient which is related to the thermal impedance function through Laplace transformation. In order to obtain temperature transient, a process has been devised to generate external heat pulse with heating wire and to measure the response of battery. This process is used to study several commercial Li-ion batteries of cylindrical type. The thermal impedance measurements have been performed using potentionstat/galvanostate controlled digital signal processor, which is more commonly available than flow-meter usually applied for thermal property measurements. Thermal impedance spectra obtained for batteries produced by different manufactures are found to differ considerably. Comparison of spectra at different states of charge indicates independence of thermal impedance on charging state of battery. It is shown that thermal impedance spectrum can be used to obtain simultaneously thermal capacity and thermal conductivity of battery by non-linear complex least-square fit of the spectrum to thermal impedance model. Obtained data is used to simulate a response of the battery to internal heating during discharge. It is found that temperature inside the battery is by one-third larger that on its surface. This observation has to be considered to prevent damage by overheating.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권3호
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• pp.133-140
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• 2023

리튬 이온 배터리는 사용 환경과 양극재 조합 비율에 따라 배터리의 성능이 좌우된다. 고성능 리튬 이온 배터리를 개발하기 위해서는 양극재 비율을 다양하게 변화시켜가면서 배터리를 제작하고 성능을 측정해야 한다. 하지만 모든 변수 조합에 대해 배터리를 제작하고 성능을 측정하기에는 많은 시간과 비용이 소모된다. 그렇기 때문에 최근에는 데이터 기반으로 인공지능 모델을 활용하여 배터리의 성능을 예측하고자 하는 연구가 활발히 진행되고 있다. 그러나 기존 공개 배터리 데이터는 동일한 배터리로 측정 실험을 하였기 때문에 양극재 조합 비율은 고정되어 있어서 데이터 속성으로 포함되지 않았다. 본 논문에서는 양극재 소재 조합 비율에 따른 배터리의 성능을 예측할 수 있는 인공지능 모델 개발에 필요한 학습 데이터 모델을 정의한다. 우리는 리튬 이온 배터리의 성능에 영향을 미칠 수 있는 요인을 분석하여 양극재 소재별 질량과 배터리 사용 환경을 입력데이터로, 배터리의 출력과 용량을 목적 데이터로 정의하였다. 공개 배터리 데이터 중에는 양극재 비율이 포함된 데이터가 없어 양극재 비율을 모두 동일한 값으로 설정한 제한된 데이터로 다중 선형회귀 분석, 서포트 벡터 회귀분석, 다중 로지스틱 회귀 분석, LSTM 분석을 수행하였다. 실험 환경이 다른 배터리 데이터에서 각각의 배터리 데이터는 고유한 패턴을 유지하였으며, 배터리 분류 모델은 각각의 배터리를 약 2%의 오차로 분류하는 것으로 나타났다.

• Journal of Power Electronics
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• 제18권4호
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• pp.1127-1139
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• 2018

A reduced particle-unscented Kalman filter estimation method, along with a splice-equivalent circuit model, is proposed for the state-of-charge estimation of an aeronautical lithium-ion battery pack. The linearization treatment is not required in this method and only a few sigma data points are used, which reduce the computational requirement of state-of-charge estimation. This method also improves the estimation covariance properties by introducing the equilibrium parameter state of balance for the aeronautical lithium-ion battery pack. In addition, the estimation performance is validated by the experimental results. The proposed state-of-charge estimation method exhibits a root-mean-square error value of 1.42% and a mean error value of 4.96%. This method is insensitive to the parameter variation of the splice-equivalent circuit model, and thus, it plays an important role in the popularization and application of the aeronautical lithium-ion battery pack.

• 한국재료학회:학술대회논문집
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• 한국재료학회 2012년도 춘계학술발표대회
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• pp.97.2-97.2
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• 2012

This study examined the utility of two zwitterions, nitrile-functionalized zwitterions and a zwitterion without a nitrile group (MF-ZI), were used as additives along with 1 M $LiPF_6$ in ethylene carbonate (EC):diethylene carbonate (DEC) (3:7 V/V) (E-0) to form an electrolyte solution for use in lithium ion batteries comprising graphite and $LiCoO_2$ electrodes. The presence of NF-ZI (E-NF-ZI) in the electrolyte produced an ion conductivity comparable to that of E-0 and higher than that of an electrolyte containing MF-ZI (E-MF-ZI). Linear sweep voltammetry data revealed that the intensity of the E-NF-ZI reduction peak was lower than that of E-0. Furthermore, the successful formation of an SEI layer in the E-NF-ZI over graphite was confirmed by cyclic voltammetry data. These results were attributed to the adsorption of NF-ZI on the electrode surface, as verified by differential capacity measurements.

• 대한의용생체공학회:의공학회지
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• 제24권1호
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• pp.45-53
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• 2003

Based on the 4-compartmental pharmacokinetic model developed in PART1, target-controlled infusion(TCI) pump system was designed and evaluated. The TCI system consists of digital board including microcontroller and digital signal process(DSP), analog board, motor-driven actuator, user friendly interface, power management and controller. It provides two modes according to the drugs: plasma target concentration and effect target concentration. Anaesthetist controls the depth of anaesthesia for patients by adjusting the required concentration to maintain both plasma and effect site in drug concentration. The data estimated in DSP include infusion rate, initial load dose, and rotation number of motor encoder. During TCI operation, plasma concentration. effect site concentration, awaken concentration, context-sensitive decrement time and system error information are displayed in real time. Li-ion battery guarantees above 2 hours without power line failure. For high reliability of the system, two microprocessors were used to perform independent functions for both pharmacokinetic algorithm and motor control strategy.

• Bulletin of the Korean Chemical Society
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• 제22권2호
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• pp.189-193
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• 2001

The irreversible capacities caused by the reduction of solvent on the surface of a negative electrode (KMFC:Kawasaki Mesophase Fine Carbon) were examined during the initial cycle in ethylene carbonate (EC)-diethyl carbonate (DEC) electrolyte solut ions at various concentrations of LiPF6. Chronopotentiograms, linear sweep voltammograms, and impedance spectra clearly showed differences in irreversible capacity and that those differences are related to the concentration of electrolyte during the initial charge. These differences were caused by the amount of solvent decomposition as a function of the concentration of LiPF6 electrolytic salt. The data are discussed with reference to the concentration of electrolytic salt and the properties of passivation film formed by solvent decomposition.

• 전력전자학회논문지
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• 제27권4호
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• pp.332-338
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• 2022

This study proposes a battery state-of-health estimation method by applying a feature extraction technique. The technique that can improve estimation performance is the process of identifying and extracting meaningful data. To apply a data-driven-based aging state estimation method to batteries, health indicators are used as training data. However, limitations occur in extracting health indicators from charge/discharge cycles. This study proposes a deep-learning-based battery state-of-health estimation method that applies feature extraction techniques to compensate for this problem. According to the performance evaluation result of the proposed method, it has a low estimation error of 0.3887% based on an absolute error evaluation method.

• 전력전자학회논문지
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• 제24권1호
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• pp.16-24
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• 2019

The performance of the battery management system (BMS) algorithm is important for ensuring the stability and efficient operation of battery packs. Such a performance is determined by the internal parameters of the electrical equivalent circuit model (EECM). This study proposes a performance improvement and verification of battery parameters for the BMS algorithm using electrical experiments and tools. The parameters were extracted through electrical characteristic experiments, and an EECM based on Ah counting was designed. Simulation results using the EECM were compared with actual experimental data to determine the best parameter extraction method.

• 로봇학회논문지
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• 제18권1호
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• pp.88-92
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• 2023

Lithium-ion batteries are actively used in various industrial sites such as field robots, drones, and electric vehicles due to their high energy efficiency, light weight, long life span, and low self-discharge rate. When using a lithium-ion battery in a field, it is important to accurately estimate the SoC (State of Charge) of batteries to prevent damage. In recent years, SoC estimation using data-based artificial neural networks has been in the spotlight, but it has been difficult to deploy in the embedded board environment at the actual site because the computation is heavy and complex. To solve this problem, neural network lightening technologies such as network pruning have recently attracted attention. When pruning a neural network, the performance varies depending on which layer and how much pruning is performed. In this paper, we introduce an optimized pruning technique by improving the existing pruning method, and perform a comparative experiment to analyze the results.