• Journal of Power Electronics
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• 제12권1호
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• pp.40-48
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• 2012

This paper proposes the State-of-charge (SOC) estimator of a LiPB Battery using the Extended Kalman Filter (EKF). EKF can work properly only with an accurate model. Therefore, the high accuracy electrical battery model for EKF state is discussed in this paper, which is focused on high-capacity LiPB batteries. The battery model is extracted from a single cell of LiPB 40Ah, 3.7V. The dynamic behavior of single cell battery is modeled using a bulk capacitance, two series RC networks, and a series resistance. The bulk capacitance voltage represents the Open Circuit Voltage (OCV) of battery and other components represent the transient response of battery voltage. The experimental results show the strong relationship between OCV and SOC without any dependency on the current rates. Therefore, EKF is proposed to work by estimating OCV, and then is converted it to SOC. EKF is tested with the experimental data. To increase the estimation accuracy, EKF is improved with a single dominant varying parameter of bulk capacitance which follows the SOC value. Full region of SOC test is done to verify the effectiveness of EKF algorithm. The test results show the error of estimation can be reduced up to max 5%SOC.

• 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.

• 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.

• 한국항공우주학회지
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• 제42권2호
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• pp.150-157
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• 2014

리튬-이온 배터리는 이전의 전기 화학 배터리에 비교해 무게, 열 소산 및 자가 방전 등의 장점으로 인해 현재 대부분의 인공위성에서 사용되고 있다. 리튬-이온 배터리의 성능 해석 모델은 새로운 위성 전력계 설계를 지원하기 위해 필요하다. 본 논문은 정지궤도위성 전력계 설계 및 에너지 밸런스 해석에 활용하기 위해 리튬-이온 배터리 성능 해석 모델을 개발하였다. 해석 모델은 위성체 버스 전력, 태양전지배열기 전력 및 배터리 온도를 입력 받고 배터리 전압, 충방전 전류, 테이퍼 지수, 충전 상태 및 소산 전력을 제공한다. 성능 해석 모델의 결과는 모델을 검증하기 위해 정지궤도위성의 비행 데이터와 비교 분석하였다. 비교된 결과는 비행 데이터와 현저한 차이가 없었다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 Proceedings ICPE 98 1998 International Conference on Power Electronics
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• pp.554-559
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• 1998

Equalizing the state of charge of cell that affects the charge/discharge quality and efficiency of the battery through the charge/discharge characteristic experiments of battery source, we develope the high efficiency charge/discharge system which would be used in serial HEV with the constant engine-generator output. For this, establishes the electrical model of Ni-MH battery appropriate to the high efficiency charge/discharge conditions. There is no model of Ni-MH cell, so we used Ni-Cd model and obtain the Ni-MH model through the experiment. A reason that each cell has the same charge/discharge property for applying the cell model to serial/parallel connected battery source extensively is needed. Therefore, in this paper, propose the Ni-MH charger/discharger has the equalization charging function and selectable cut-off function.

• 한국환경과학회지
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• 제33권7호
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• pp.523-532
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• 2024

In popular tourist destinations such as Jeju and Gangwon, electric rental cars are increasingly adopted. However, sudden battery drain due to weather conditions can pose safety issues. To address this, we developed a battery consumption analysis model that considers resistive energy factors such as acceleration, rolling resistance, and aerodynamic drag. Focusing on the effects of ambient temperature and wind speed, the model's performance was evaluated during an empirical validation period from November to December 2023. Comparing predicted and actual state of charge (SoC) across different routes identified ambient temperature, wind speed, and driving time as major sources of error. The mean absolute error (MAE) increased with lower temperatures due to reduced battery efficiency. Higher wind speeds on routes 1 and 6 resulted in larger errors, indicating the model's limitation in considering only tailwinds for aerodynamic drag calculations. Additionally, longer driving times led to higher actual SoC than predicted, suggesting the need to account for varying driver habits influenced by road conditions. Our model, providing more accurate SoC predictions to prevent battery depletion incidents, shows high potential for application in navigation apps for electric vehicle users in tourist areas. Future research should endeavor to the model by including wind direction, HVAC system usage, and braking frequency to improve prediction accuracy further.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2002년도 학술대회지
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• pp.651-654
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• 2002

Study of electric vehicle is popular with automobile company. However, battery cooling problem has delayed development of electric vehicle. Lifetime of electric vehicle's battery depends on the cooling effect for the battery tray. One model was simulated by 3-D, steady state, incompressible, k-e turbulent model simulation. It is found that flow inlet, outlet and inlet position are very important design parameters.

• 소프트웨어공학소사이어티 논문지
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• 제27권1호
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• pp.1-7
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• 2018

제한된 자원인 모바일 디바이스 배터리의 소모는 회로 설계자들이 회로를 분석 및 평가할 때 중요한 척도가 된다. 기존의 모바일 디바이스 배터리 소모 분석을 위해 여러 배터리 소모 모델 생성 연구가 수행되었으며, 배터리 소모 모델 생성 기법은 센서의 사용 유무, 런타임 모델 생성 여부, 검증 및 테스팅 목적으로의 모델 이용 여부 등에 따라 서로 다른 특징을 가진다. 본 연구에서는 모바일 디바이스회로 설계자들이 회로를 분석하는데 도움을 주기 위한 목적으로 지금까지 연구되어 온 배터리 소모 모델 분석 기법들에 대하여 비교 및 평가하고자 한다. 평가 결과를 기반으로 향후 모바일 디바이스 배터리 소모 분석 연구의 발전 방향을 제안한다.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.1035-1037
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• 1997

This paper deals with the mathematical modeling of battery energy storage systems interconnected with the distribution system. This battery model takes account of self-discharge, battery storage capacity, internal resistance and overvoltage. The model components are decided by using an approximation technique and experimental results. This model can be used to evaluate battery performance of battery energy storage systems interconnected with distribution system.