• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 1998년도 학술발표회논문집
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• pp.177-180
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• 1998

To manage lead-acid battery efficiently and to use it longer in UPS, the state of charge(SOC) indicator of the battery is needed. So a new approach to developing battery SOC indicator for UPS is discussed in this paper. This method to determining SOC by combining the available data of discharge characteristics of a battery with neural networks(NN) is presented. The 3-layered NN with back propagation algorithm has been used. Exprement results show that the proposed method is appropriate as SOC indicator of the battery.

• 전력전자학회논문지
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• 제26권1호
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• pp.1-8
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• 2021

For the safe and reliable operation of lithium-ion batteries in electric vehicles or energy storage systems, having accurate information of the battery, such as the state of charge (SOC), is essential. Many different techniques of battery SOC estimation have been developed, such as the Kalman filter. However, when this filter is applied to multiple batteries, it has difficulty maintaining the accuracy of the estimation over all cells owing to the difference in parameter values of each cell. The difference in the parameter of each cell may increase as the operation time accumulates due to aging. In this paper, a novel deep neural network (DNN)-based SOC estimation method for multi-cell application is proposed. In the proposed method, DNN is implemented to determine the nonlinear relationships of the voltage and current at different SOCs and temperatures. In the training, the voltage and current data obtained at different temperatures during charge/discharge cycles are used. After the comprehensive training with the data obtained from the cycle test with a cell, the resulting algorithm is applied to estimate the SOC of other cells. Experimental results show that the mean absolute error of the estimation is 1.213% at 25℃ with the proposed DNN-based SOC estimation method.

• Journal of Power Electronics
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• 제16권3호
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• pp.1131-1140
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• 2016

A simple design for a sliding mode observer is proposed for EV lithium battery SOC estimation in this paper. The proposed observer does not have the limiting conditions of existing observers. Compared to the design of previous sliding mode observers, the new observer does not require a solving matrix equation and it does not need many observers for all of the state components. As a result, it is simple in terms of calculations and convenient for engineering applications. The new observer is suitable for both time-variant and time-invariant models of battery SOC estimation, and the robustness of the new observer is proved by Liapunov stability theorem. Battery tests are performed with simulated FUDS cycles. The proposed observer is used for the SOC estimation on both unchanging parameter and changing parameter models. The estimation results show that the new observer is robust and that the estimation precision can be improved base on a more accurate battery model.

• 전력전자학회논문지
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• 제13권5호
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• pp.360-368
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• 2008

하이브리드 전기자동차용 리튬이온 배터리 시스템의 모델링 및 모델기반 상태 관측기 설계에 관한 연구를 수행하였다. 배터리의 동적 특성을 모사하기 위한 모델은 전기적 등가회로로 단순화하여 제안하였다. 모델 파라미터는 최소 자승 이론에 의거 다양한 운전조건에 따라 추정하였고, 실험 검증하였다. 검증된 모델을 기반으로 하는 비례-적분(PI) 제어의 상태 관측기를 구성하였고, 제어 이득 선정방법을 제안하였다. 제안된 상태 관측기의 강인성은 시뮬레이션 및 실험에 의거 다양한 운전조건 변동에 따른 민감도를 분석하여 검증하였다.

• 한국산업융합학회 논문집
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• 제23권5호
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• pp.853-863
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• 2020

As the battery ages, the internal resistance of the battery increases, so the loss due to the internal resistance increases at the same charging current, causing the battery temperature to rise, which further accelerates battery aging. Therefore, it is necessary to optimize the charging conditions according to the aging of the battery or the current charge amount, and to accurately estimate this, estimation of the parameters of the equivalent circuit is most important. This paper proposes a new measurement technique that can measure the internal resistance of a battery by analyzing a specific high frequency voltage and current applied to the battery. In addition, in order to test the validity of the proposed measurement technique, the current charging amount was estimated based on the measured internal resistance, and the terminal voltage of the constant current charging mode was automatically set and operated. As a result, good results were obtained regardless of the battery voltage. If this equipment is installed in the charging device, it is believed that it will be of great help in the stability management of the aging reusable battery.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2018년도 추계학술대회
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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.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 춘계학술대회 논문집
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• pp.534-537
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• 2008

하이브리드자동차의 연료소비율 시험 시 초기 SOC 조건에 따른 SOC와 연비 변화 특성을 파악하기 위해 2종의 차종을 선택하여 UDDS 모드주행 실험을 실시하였다. 실험결과 Strong type 자동차는 주행시작 약 550초 경과 후 SOC 52 $\sim$ 54%로 수렴하였다. 또한 일반 시가지 주행조건에서는 SOC를 50$\sim$55 % 범위에서 제어함을 알 수 있으며, 초기 SOC 조건에 따라 연비는 약 79%의 편차가 나타났다. 이는 저속구간에서 순수 전기자동차 구동이 구현됨으로써 SOC 70%에서 큰 연비 상승 효과가 나타나는 것으로 판단 된다. Mild type 자동차는 연비가 초기 SOC 조건에 따라 약 5%의 편차가 나타남을 알 수 있었으며, SOC 변화특성은 배터리 충전상태에 따라 충전량 제어는 이루어지나 가속 시 어시스트만 이루어지는 시스템적 특성상 효율적인 SOC 제어가 이루어지지 않아 연비에는 큰 영향을 주지 않는 것으로 생각된다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2019년도 전력전자학술대회
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• pp.204-206
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• 2019

본 논문은 이중 확장 칼만 필터를 통한 SOC (State of charge) 및 용량 추정과 배터리 모델 파라미터를 이용한 폐배터리의 최대 출력을 추정하는 방법을 연구 및 제안한다. 배터리의 단순 전압 측정을 통해 상태를 진단할 경우, 부하 조건에 따라 급격한 전압 상승 및 강하로 인해 정밀한 안전 진단 및 운용에 어려움이 따르지만, 폐배터리는 일반 배터리에 비해 전압 변동율이 크기 때문에 상태 진단에 큰 어려움이 존재한다. 따라서 본 논문에서는 폐배터리의 정밀한 안전진단을 하기 위해 SOC 영역 및 충/방전에 따른 최대 출력을 계산하여 사전에 배터리의 상태를 진단할 수 있는 알고리즘을 제안한다. 또한, 배터리의 노화도에 따른 최대 출력을 실험 및 시뮬레이션을 통해 결과를 제시하여 유효한 방식임을 검증한다.

• Journal of applied mathematics & informatics
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• 제39권5_6호
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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.

• 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.