• 전력전자학회논문지
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• 제23권3호
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• pp.174-181
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• 2018

This study introduces a systematic approach to selecting the internal parameters applied to the equivalent electrical-circuit model (EECM) of a lithium titanium oxide ($Li_4Ti_5O_{12}$; LTO) rechargeable cell. Based on the dynamic characteristic of the cell, a simplified EECM consisting of an open-circuit voltage (OCV), an ohmic resistance, and an RC ladder is fabricated. To select the internal parameters of a simplified EECM, experiments on discharge capacity, OCV, and discharge/charge resistances are performed using hybrid pulse power characterization and direct current internal resistance (DCIR) measurements over the full state-of-charge (SOC) range. The experimental results of the LTO rechargeable cell highlight the importance of correct selection of internal parameters that can reduce EECM errors. This study clearly provides experimental procedures, internal parameters results, and EECM guidelines for adaptive control-based SOC estimation for LTO rechargeable cells.

• 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.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1664-1673
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• 2016

Lithium rechargeable cells are used in many industrial applications, because they have high energy density and high power density. For an effective use of these lithium cells, it is essential to build a reliable battery management system (BMS). Therefore, the state of charge (SOC) estimation is one of the most important techniques used in the BMS. An appropriate modeling of the battery characteristics and an accurate algorithm to correct the modeling errors in accordance with the simplified model are required for practical SOC estimation. In order to implement these issues, this approach presents the comparative analysis of the SOC estimation performance using equivalent electrical circuit modeling (EECM) and noise suppression technique (NST) in three representative $LiCoO_2/LiFePO_4/LiNiMnCoO_2$ cells extensively applied in electric vehicles (EVs), hybrid electric vehicles (HEVs) and energy storage system (ESS) applications. Depending on the difference between some EECMs according to the number of RC-ladders and NST, the SOC estimation performances based on the extended Kalman filter (EKF) algorithm are compared. Additionally, in order to increase the accuracy of the EECM of the $LiFePO_4$ cell, a minor loop trajectory for proper OCV parameterization is applied to the SOC estimation for the comparison of the performances among the compared to SOC estimation performance.

• 전기전자학회논문지
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• 제23권2호
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• pp.667-674
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• 2019

최근 발생한 원전 사고는 소외전원 및 비상전원의 기능이 상실되어 발전소 전체 정전이 발생한 사례를 계기로 원전의 비상전원공급용 배터리의 중요성이 부각되고 있다. 현재 원전의 비상전원공급용 배터리는 기존의 납축전지를 대신하여 리튬계열 배터리로 교체가 고려되고 있는 상황이다. 이에 따라 원통형 리튬 배터리의 적용성을 판단하기 위해 여러 가지 리튬 계열 배터리의 전기적 특성 실험을 진행하여 결과를 분석해야 한다. 본 논문은 현재 ESS(Energy Storage Systems)에 많이 사용되는 세 가지 타입의 리튬 배터리의 전기적 특성실험을 통해 적절한 배터리 타입을 선정하고, 선정된 배터리가 비상전원공급용 배터리로 사용될 때 최적의 C-rate를 제안한다. 또 배터리 모델링을 통해 배터리의 상태를 추정하며 문제점을 제시한다.

• 전력전자학회논문지
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• 제26권6호
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• pp.381-389
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• 2021

Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis.