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

• Proceedings of the KIPE Conference
• /
• 2012.11a
• /
• pp.157-158
• /
• 2012

본 논문은 리튬 폴리머 배터리의 수명 감소에 대한 경향성 테스트를 토대로 이중 확장 칼만 필터(Dual EKF)를 이용하여 배터리의 SOC(State-of-Charge) 및 SOH(State-of-Charge) 방법을 제안하였다. 배터리에 수명에 따른 임피던스 변화를 테스트를 수행함으로써 등가회로 모델상에서 수명에 따른 변화가 가장 큰 내부 저항을 선택함으로써 배터리의 SOH 추정을 위해 선택하였다. 배터리 모델은 4.2V, 1440mAh의 리튬폴리머 전지에서 추출되었다. 배터리는 Bulk 커패시터, 두 개의 R-C회로, 직렬 저항을 사용하여 모델링하였다. Dual EKF를 모델에 적용하기 위해 캐패시터 전압은 개방 회로 전압(OCV)을 나타내는데 사용된다. Dual EKF는 충/방전 기기인 TOSCAT-5200에 의해 얻은 실험 데이터로 테스트하였다.

• Proceedings of the KIPE Conference
• /
• 2011.11a
• /
• pp.275-276
• /
• 2011

본 논문은 풍력과 태양광 등의 신재생 에너지 전력저장뿐만 아니라 계통 안정화 및 전력품질 관리에 적용 가능한 BESS(Battery Energy Storage System)에서 대용량 에너지를 안정적으로 충전하고 방전할 수 있는 BCS(Battery Conditioning System) 개발에 대해 기술하였다. 충 방전시 배터리 냉각을 고려한 열유동 해석, 외부 환경조건 및 국내외 운송을 고려한 구조해석 등의 과정을 거쳐 설계 제작하였으며, 충 방전 성능시험을 수행하였다.

• Proceedings of the KIPE Conference
• /
• 2016.11a
• /
• pp.81-82
• /
• 2016

최근 퍼스널 모빌리티 분야에 적용되는 배터리는 대부분 리튬계열 배터리가 차지하고 있다. 각광받는 이유로는 작은 부피, 무게에 비해 큰 용량을 가지는 장점이 있고 셀당 전압의 경우에도 기존 니켈수소 및 카드뮴 등과 같은 수계전해액의 전지에 비해 3배 정도 높다는 장점을 가진다. 이러한 리튬이온배터리를 제품에 적용하기 위해서는 직병렬 구조의 팩 단위로 구성하여야 하며, 단일 셀이 아닌 다수의 셀 조합이기 때문에 충방전을 진행하는 과정에서 직렬구성 셀의 특성이 달리지게 되어 최종적으로는 전압의 차로 검출되게 된다. 이러한 전압의 차는 배터리의 용량을 저감시키고 특정 셀에 스트레스를 가중시켜 셀의 수명을 단축시키는 요인으로 작용한다.

• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.163-172
• /
• 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 the Korea Convergence Society
• /
• v.11 no.6
• /
• pp.7-14
• /
• 2020

A Battery Monitoring System capable of State-of-Charge(SOC) estimation using the Extended Kalman Filter(EKF) is described in this paper. In order to accurately estimate the SOC of the battery, the battery cells were modeled as the Thevenin equivalent circuit model. The Thevenin model's parameters were measured in experiments. For the Battery Monitoring System, we designed a battery monitoring device that can calculate the SOC estimation using the EKF and a monitoring server that controls multiple battery monitoring devices. We also develop a web-based dashboard for controlling and monitoring batteries. Especially the computation of the monitoring server could be reduced by calculating the battery SOC estimation at each Battery Monitoring Device.

• Proceedings of the KAIS Fall Conference
• /
• 2011.05b
• /
• pp.753-756
• /
• 2011

지속적인 충/방전에 의하여 표준 수명 보다 더 빠른 노화 현상을 일으키는 배터리의 효율적인 관리를 위하여, 배터리의 내부 상태를 모니터링 하였다. 정확한 배터리 모니터링을 위해서 해당하는 배터리의 잔존 용량 및 잔존 수명을 정확히 예측할 수 있어야 하며, 이를 위해 Open Voltage를 사용한 실험, 에너지 보존 법칙에 의한 충전 전류 측정법, 시동 시 최대 전류와 내부 저항의 변화량을 알아내는 실험을 하였다. Open Voltage 실험 결과, SOC수치에 따른 특정 전압의 범위를 알 수 있었고, 이 전압은 온도에 의해 변동된다는 것을 확인할 수 있었다. 충전 그래프를 그려본 결과 충전횟수와 완충에 걸리는 시간은 반비례하며, 배터리 내부에 충전되는 총 전류의 양과도 관계가 있었다. 시동 실험에서는 최저 전압 드롭 값과 최대 공급 전류의 범위를 알 수 있었으며, 특정 SOC 구간 내 내부 저항의 값을 차이를 알 수 있었다. 이 값들은 각 SOC의 수치에 비례한 결과를 보였다. 이 결과들을 정리하여, 배터리 내부 상태를 예측하는 방법을 제안하고자 한다.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.37 no.4
• /
• pp.313-322
• /
• 2013

Batteries, which are being used as energy sources in various applications, tend to degrade, and their capacity declines with repeated charging and discharging cycles. A battery is considered to fail when it reaches 80% of its initial capacity. To predict this, prognosis techniques are attracting attention in recent years in the battery community. In this study, a method is proposed for estimating the battery health and predicting its remaining useful life (RUL) based on the slope of the charge voltage curve. During this process, a Bayesian framework is employed to manage various uncertainties, and a Particle Filter (PF) algorithm is applied to estimate the degradation of the model parameters and to predict the RUL in the form of a probability distribution. Two sets of test data-one from the NASA Ames Research Center and another from our own experiment-for an Li-ion battery are used for illustrating this technique. As a result of the study, it is concluded that the slope can be a good indicator of the battery health and PF is a useful tool for the reliable prediction of RUL.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.5
• /
• pp.1067-1074
• /
• 2024

Various monitoring systems are in operation in large-scale production facilities such as Yeosu Industrial Complex and the power equipment for operating these systems uses protective devices with built-in low-power lithium-ion batteries to cope with poor environments. In this study, a wireless monitoring system was designed and implemented to analyze the usage characteristics of these lithium-ion batteries. By using the system, the temperature and humidity of the protective device including the battery, gas generation due to charging and discharging of the battery within the protective device, and changes in battery characteristics can be monitored wirelessly at all times. Through this system, the stable management and power supply of batteries required for monitoring devices in industrial complexes are provided, thereby contributing to the establishment of an efficient operation and management system for factory production facilities.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.9
• /
• pp.1202-1208
• /
• 2020

In line with the current era of the 4th Industrial Revolution, it is necessary to prepare for the future by integrating AI elements in the ship sector. In addition, it is necessary to respond to this in the field of power management for the appearance of autonomous ships. In this study, we propose a battery-linked electric propulsion system (BLEPS) algorithm using machine learning's DNN. For the experiment, we learned the pattern of ship power consumption for each operation mode based on the ship data through LabView and derived the battery status through Python to check the flexibility of the generator and battery interlocking. As a result of the experiment, the low load operation of the generator was reduced through charging and discharging of the battery, and economic efficiency and reliability were confirmed by reducing the fuel consumption of 1% of LNG.