• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 추계학술대회 논문집
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• pp.60-62
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• 2007

The open circuit voltage (OCV) is widely used to estimate the state of charge (SOC) in many estimation algorithms. However, the relationship between the OCV and SOC can not be exactly same for all batteries. Because the conventional OCV-SOC differs between batteries, there is a problem that the relationship of the OCV-SOC should be measured to accurately estimate the SOC. Therefore, the conventional OCV-SOC is modified to a new relationship in this paper. Thus, problems resulting from the defects of the extended Kalman filter (EKF) can be avoided by preventing the relationship from varying. In this paper, SOC and capacity of the lithium-ion battery are estimated using the dual EKF with the proposed method.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 추계학술대회 논문집
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• pp.75-76
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• 2016

The relationship of widely used Open circuit Voltage (OCV) versus State of Charge (SOC) is critical for any reliable SOC estimation technique. However, the hysteresis existing in all type of battery which has been come to the market leads this relationship to a complicated one, especially in Lithium Iron Phosphate (LiFePO4) battery. An accurate model for hysteresis phenomenon is essential for a reliable SOC identification. This paper aims to investigate and propose a method for hysteresis modeling. The SOC estimation is done by using Extended Kalman Filter (EKF), the parameter of the battery is modeled by Auto Regressive Exogenous (ARX) and estimated by using Recursive Least Square (RLS) filter to tract each element of the parameter of the model.

• 한국융합학회논문지
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• 제8권6호
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• pp.237-243
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• 2017

배터리 팩 수명에 대한 무지는 무인항공기의 추락을 야기할 수 있으며 이로 인해 잔존수명 예측이 잔존 용량 예측에 있어서 중요 요소가 되었다. 전기자동차와는 달리, 소형 무인항공기는 무겁고 복잡한 배터리 관리 시스템을 운반 할 수 없기 때문에, 사고를 예방하기 위해서는 간단하고, 가볍고, 저렴하고, 강력한 배터리 관리 시스템을 적용하는 것이 필요하다. 본 논문에서는, 두 가지 잔존수명 예측 방법들을 보여주는데, 한 가지는 내부 저항을 이용하는 것이며 다른 한 가지는 상보필터를 이용한 $SOC_I$와 $SOC_V$를 사용하는 방법이다. 결과를 통해 30 방전 사이클 후의 잔존용량은 92%로 계산되었다.

• IEIE Transactions on Smart Processing and Computing
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• 제4권2호
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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.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2024년도 제69차 동계학술대회논문집 32권1호
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• pp.449-452
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• 2024

본 논문에서는 리튬이온 배터리의 SOC(State Of Charge) 초기 정보의 정확도 향상을 위하여 확장칼만필터(EKF) 방법을 적용한 효율적 SOC 추정 알고리즘을 제안한다. 일반적인 전류적산법을 사용하는 방법은 초기 조건이 부정확한 경우에 오차가 발생하고 시간에 따라 누적 오차가 커지는 단점이 있다. 이러한 문제점 해결을 위하여 초기 SOC 추정값에 EKF 방법을 동시에 적용하는 알고리즘을 제안한다. 제안 알고리즘의 평가를 위한 실험을 통하여 제안 방법이 기존 SOC 추정 방법보다 추정 오차가 개선됨을 확인하였다.

• Journal of Power Electronics
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• 제10권6호
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• pp.769-776
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• 2010

The ultracapacitor module has recently been recast for use in hybrid energy storage systems (HESSs). As a result, accurate state-of-charge (SOC) estimation for an ultracapacitor module is as important as that of primary sources in order to be utilized efficiently in an energy storage system (ESS). However, while SOC estimation via the open-circuit voltage (OCV) method is generally used due to its linear characteristics compared with other ESSs, this method results in many errors in cases of highcurrent charging/discharging within a short time period. Accordingly, this paper introduces a dynamic SOC estimation algorithm that is capable of SOC compensation of an ultracapacitor module even when there is a current input and output. A cycle profile that simulates the operating conditions of a mild-HEV was applied to a vehicle simulator to verify the effectiveness of the proposed algorithm.

• 한국농공학회논문집
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• 제61권6호
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• pp.1-8
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• 2019

Carbon dioxide is one of the major driving forces causing climate changes, and many countries have been trying to reduce carbon dioxide emissions from various sources. Soil stores more carbon dioxide(two to three times) amounts than atmosphere indicating that soil organic carbon emission management are a pivotal issue. In this study, we developed a Soil Organic Carbon(SOC) storage estimation model to predict SOC storage amounts in soils. Also, SOC storage values were assessed based on the carbon emission price provided from Republic Of Korea(ROK). Here, the SOC model calculated the soil hydraulic properties based on the soil physical and chemical information. Base on the calculated the soil hydraulic properties and the soil physical chemical information, SOC storage amounts were estimated. In validation, the estimated SOC storage amounts were 486,696 tons($3.526kg/m^2$) in Jindo-gun and shown similarly compared to the previous literature review. These results supported the robustness of our SOC model in estimating SOC storage amounts. The total SOC storage amount in ROK was 305 Mt, and the SOC amount at Gyeongsangbuk-do were relatively higher than other regions. But the SOC storage amount(per unit) was highest in Jeju island indicating that volcanic ashes might influence on the relatively higher SOC amount. Based on these results, the SOC storage value was shown as 8.4 trillion won in ROK. Even though our SOC model was not fully validated due to lacks of measured SOC data, our approach can be useful for policy-makers in reducing soil organic carbon emission from soils against climate changes.

• 전기학회논문지
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• 제63권8호
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• pp.1085-1091
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• 2014

A model based SOC estimation scheme using parameter identification is described and applied to a Lithium-ion battery module that can be installed in electric vehicles. Simulation studies are performed to verify the effect of sensor faults on the SOC estimation results for terminal voltage sensor and load current sensor. The sensor faults should be detected and isolated as soon as possible because the SOC estimation error due to any sensor fault seriously affects the overall performance of the BMS. A new fault detection and isolation(FDI) scheme by which the fault of terminal voltage sensor and load current sensor can be detected and isolated is proposed to improve the reliability of the BMS. The proposed FDI scheme utilizes the parameter estimation of an input-output model and two fuzzy predictors for residual generation; one for terminal voltage and the other for load current. Recently developed dual polarization(DP) model is taken to develope and evaluate the performance of the proposed FDI scheme. Simulation results show the practical feasibility of the proposed FDI scheme.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2014년도 전력전자학술대회 논문집
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• pp.542-543
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• 2014

In this paper, an estimation scheme based on an augmented sigma-point Kalman filter to estimate the state of charge (SOC) of the battery is presented, where the battery parameters of the series resistance ($R_o$), diffusion capacitance ($C_1$) and resistance ($R_1$) are also estimated through the recursive least squares (RLS) for better accuracy of the SOC. The effectiveness of the proposed method is verified by simulation results.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2014년도 전력전자학술대회 논문집
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• pp.401-402
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• 2014

State of Charge (SOC) and State of Health (SOH) are the key issues for the application of Absorbent Glass Mat (AGM) type battery in Idle Start Stop (ISS) system which is popularly integrated in Electric Vehicles (EVs). However, battery parameters strongly depend on SOC, current rate and temperature and significantly change over the battery life cycles. In this research, a novel method for SOC, SOH estimation which combines the Auto Regressive with external input (ARX) method using for online parameters prediction and Dual Extended Kalman Filter (DEKF) algorithm considering hysteresis is proposed. The validity of the proposed algorithm is verified by the simulation and experiments.