• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.3
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• pp.227-234
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• 2014

Fuel consumption rates of electric vehicles strongly depend on their battery performance. Because the battery performance is sensitive to the operating temperature, temperature management of the battery ensures its performance and durability. In particular, the temperature distribution among modules in the battery pack affects the cooling characteristics. This study focuses on the thermal modeling of a battery pack to observe the temperature distribution among the modules. The battery model is a prismatic model of 10 NiMH battery modules. The thermal model of the battery consists of heat generation, convective heat transfer through the channel and conduction heat transfer among modules. The heat generation is calculated by the electric resistance heat during the charge/discharge state. The model is used to determine a strategy for proper thermal management in Electric vehicles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2545-2552
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• 2014

This study is aiming to suggest the effective thermal management system design technologies for the high voltage and capacity battery system of the electricity driven vehicles and introduce the theoretical designing methods. In order to investigate the effective operation of the battery system for the electricity driven vehicles, the heat generation model for Li-ion battery system using the chemical reaction while charging and discharging was suggested and the thermal loads of the heat sources (air or liquid) for cooling and heating were calculated using energy balance. Especially, the design methods for the cooling and heating of the battery system for maintaining the optimum operation temperature were investigated under heating, cooling and generated heat (during charging and discharging) conditions. The battery thermal management system for the effective battery operation of the electricity driven vehicles was suggested reasonably depending on the variation of the season and operation conditions. In addition, at the same conditions under summer season, the cooling method using the liquid and active cooling technique showed a relatively high capacity, while cooling method using the passive cooling technique showed a relatively low capacity.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.163-172
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• 2022

Purpose: To secure efficient thermal management technology for Li-ion batteries, the applicability of the system applied with single-phase immersion technology was checked through an experiment. Method: Using JH3 pouch cells produced by LG-Chem, Korea, A 14S2P module was manufactured and immersed in a vegetable-based cooling fluid produced by Cargill, USA, and then charged and discharged at a rate of 0.3C to 1C to check the heat distribution. Result: It was possible to manage and there was no change in the molecular structure of the immersion solution. Conclusion: It was confirmed that the immersion cooling method can be applied to the thermal management of Li-ion batteries.

• Journal of Energy Engineering
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• v.23 no.2
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• pp.57-61
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• 2014

Challenges the automotive industry as the increase in consumption of oil and energy, $CO_2$ emissions of global warming, caused by exhaust emissions and urban air pollution, it is time for a deal is needed. The solution of these highly regarded in the market as there is a demand of electric cars. In this study, electric car motor, battery and high-voltage core components, including the drive motor of the effective thermal management technologies, thermal management of the battery and the drive motor to evaluate the technology and development trends.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.569-582
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• 2023

Lead-acid Battery is the oldest rechargeable battery system and has maintained its position in the rechargeable battery field. The battery causes thermal runaway for various reasons, which can lead to major accidents. Therefore, preventing thermal runaway is a key part of the battery management system. Recently, research is underway to categorize thermal runaway battery cells into machine learning. In this paper, we present a thermal runaway hazard cell detection and verification algorithm using DBSCAN and statistical method. An experiment was conducted to classify thermal runaway hazard cells using only the resistance values as measured by the Battery Management System (BMS). The results demonstrated the efficacy of the proposed algorithms in accurately classifying thermal runaway cells. Furthermore, the proposed algorithm was able to classify thermal runaway cells between thermal runaway hazard cells and cells containing noise. Additionally, the thermal runaway hazard cells were early detected through the optimization of DBSCAN parameters using a grid search approach.

• 방재와보험
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• s.137
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• pp.38-43
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• 2010

트랜지스터 또는 "트랜지스터 라디오" 배터리라고 부르고 어디에서나 흔히 볼 수 있는 9V PP3 건전지는 일반적으로 작은 크기로 인한 내부위험 또는 소각하여 폐기할 때에 발생하는 폭발 위험 이외의 중대한 위험을 내포하지 않는 것으로 알려져 있다. 후자의 위험은 모든 다른 배터리에도 적용된다. 그러나 약간 높은 에너지 밀도와 PP3 배터리 단자의 구조는 일부 사례에서 배터리의 낮은 내부 임피던스와 결합하여 단락 물질에 충분한 열을 발생시켜서 그것과 접촉하고 있는 가연물을 손상시키거나 점화시킬 수 있는 단락위험을 발생시킬 수 있다. 이 현상을 증명하기 위해 이 논문은 PP3 건전지의 단락시험에서 기록된 자료와 관찰사항을 기술한 것이다. 이 시험에는 2개 세트의 배터리, 완전 충전된 새 배터리와 완전 방전되지 않은 배터리(이 문서에서 "일부 사용된 배터리"라고 한다)를 사용하였다.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.37-39
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• 2020

리튬이온 배터리는 동작하는 과정에서 필연적으로 열이 발생하기 때문에 적절한 열 관리에 대한 전략이 필요하다. 배터리에서의 발열은 가역적인 발열과 비가역적인 발열로 분류될 수 있으며 배터리의 용도별, 동작 조건 별 발열 특성이 상이하기 때문에, 배터리의 열적 안전성 확보를 위해서는 열적 특성에 대한 분석이 필수적이다. 본 연구에서는 고용량/고출력 리튬이온 배터리의 전기적 특성 실험을 수행하고 열적 안전성 분석을 위하여 발열 특성 분석을 수행하였다. 고용량/고출력 배터리 특성에 따라 가역적 발열과 비가역적 발열이 나타나는 특성이 상이한 것으로 확인되었으며, 또한 온도 측정 정보로부터 배터리의 내부 상태 특성을 추정하고 고장 진단 및 수명 특성에 활용될 수 있음을 확인하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.22-28
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• 2017

The performance of lithium ion batteries used in electric vehicles (EV) varies greatly depending on the battery temperature. In this paper, the finite difference method was used to evaluate the temperature change, state of charge (SOC), internal resistance, and voltage change of the battery due to heat generation in the battery. The simulation model was linked with AMESim to calculate the driving range of an EV traveling in New European Driving Cycle (NEDC) mode. As the temperature dropped below $25^{\circ}C$, the internal resistance of the battery increased, which increased the amount of heat generated and decreased the driving range of EV. At battery temperatures above $25^{\circ}C$, the driving range was also decreased due to reduced SOC that deteriorated the battery performance. The battery showed optimal performance and the driving range was maximized at $25^{\circ}C$. When battery temperatures of $-20^{\circ}C$ and $45^{\circ}C$, the driving range of EV decreased by 33% and 1.8%, respectively. Maintaining the optimum battery temperature requires heating the battery at low temperature and cooling it down at high temperature through efficient battery thermal management. Approximately 500 W of heat should be supplied to the battery when the ambient temperature is $-20^{\circ}C$, while 250 W of heat should be removed for the battery to be maintained at $25^{\circ}C$.

• Journal of Institute of Convergence Technology
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• v.10 no.1
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• pp.37-40
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• 2020

Automotive battery system consists of various components such as battery cells, mechanical structures, cooling system, and control system. Recently, various computational technologies are required to develop an automotive battery system. Physics-based cell modeling is used for designing a new battery cell by conducting optimization of material selection and composition in electrodes. Structural analysis plays an important role in designing a protective system of battery system from mechanical shock and vibration. Thermal modeling is used in development of thermal management system to maintain the temperature of battery cells in safe range. Finally, vehicle simulation is conducted to validate the performance of electric vehicle with the developed battery system.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.56-58
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• 2019

배터리의 효율적인 관리와 안정적인 운영을 위해서는 배터리의 노화에 따른 배터리의 모니터링이 필요하다. 하지만 모델 기반의 SOH 예측 모델의 경우 파라미터의 변화에 대한 정확한 정보가 반영되지 않을 경우 심각한 오류를 야기 할 수 있다. 따라서 본 논문에서는 비 모델인 시계열 예측 기법 ARIMA 모델을 제안하고 전기적 특성 실험을 통한 내부 파라미터에 대한 분석과 파라미터에 대한 상관분석, 이를 통한 SOH 예측을 통해 ARIMA 모델의 특성 및 정확성에 대해 제안한다.