배터리 관리 시스템에 관한 연구: 다양한 운영 조건에서 리튬 이온 배터리의 내부 단락 검출 및 모델링 기법

DoctorIn this thesis, detection methods for internal short circuit (ISCr) in lithium-ion battery and an innovative model are proposed for the batteries in various operating conditions. Based on equivalent circuit models such as the Rint model and the Thevenin model, the ISCr can be represented by connecting an ISCr resistance parallel to the battery terminals. As fault index, the ISCr resistance, which directly indicates the degree of ISCr faults, is estimated to detect the ISCr early, and the ISCr resistance estimation methods are proposed in different operating environments: (1) battery cells discharged with load profiles for electric vehicles at 25 ℃, (2) battery packs under the identical conditions as in (1), and (3) battery cells charged with constant current at 25 ℃. Additionally, a simple and novel battery modeling method is proposed for batteries that can be used under various ambient temperatures (-10 ℃ to 30 ℃). The proposed methods in this thesis are verified using the experimental data which is obtained with commercial batteries

Internal Short Circuit Detection in Lithium Ion Battery

MasterEarly detection of an internal short circuit (ISCr) in a Li-ion battery can prevent it from undergoing thermal runaway, and thereby ensure battery safety. In this thesis, we propose an algorithm for estimating an internal short circuit (ISCr) resistance in a Li-ion battery. The open circuit voltage (OCV) and the state of charge (SOC) are estimated by applying the equivalent circuit model of the Li-ion battery with ISCr, and by using the recursive least squares algorithm and the relation between OCV and SOC. As a fault index, the ISCr resistance R_ISCf is estimated from the estimated OCVs and SOCs to detect the ISCr. To improve the accuracy of R_ISCf estimates, the switching model method (SMM) is also proposed. The R_ISCf is used to update the model; this process yields accurate estimates of OCV and R_ISCf. Then the next R_ISCf is estimated and used to update the model iteratively. To verify this algorithm, the simulation data from MATLAB/Simulink model and experimental data are used. The result shows that the proposed algorithm contributes to detect the ISCr fault in Li-ion battery, thereby helping the battery management system to fulfill early detection of the ISCr

리튬 이온 배터리 팩의 정전류 방전 곡선을 이용한 배터리 팩 SOC 불균일 정도 추정

2

유전 알고리즘을 이용한 다양한 온도 환경에서의 리튬 이온 배터리 모델 파라미터 추정

2

Detection of internal short circuit in Li-ion battery by estimating its resistance

1

노화를 고려한 배터리의 내부 단락 진단 및 용량 추정 알고리즘

2

Grey prediction method for forecasting the capacity of lithium-ion batteries

1

셀 밸런싱 동작을 고려한 리튬 이온 배터리 팩의 내부 단락 고장 진단

2

Detection of internal short circuit for lithium-ion battery using convolutional neural networks with data pre-processing

1

State-of-Health Estimation Algorithm of Li-Ion Battery Using Impedance at Low Sampling Rate

1