배터리 열화진단을 위한 실시간 이미징 분석 기술

신예원 ( Yewon Shin ),이민규 ( Mingyu Lee ),이홍경 ( Hongkyung Lee ) 한국공업화학회 2022 공업화학전망 Vol.25 No.4

With the growing popularity of battery-powered mobility, battery safety and performance reliability have been prioritized by battery industries. Despite advanced manufacturing processes of large-scale commercial Li-ion cells, “latent defects” that can accidentally appear due to imbalanced battery design, invisible faults, and extreme operating conditions still threaten performance degradation and battery fire. Hence, it is urgently necessary to detect such latent defects in advance and understand the impacts of cell parameters and operating conditions on the battery failure scenario. For straightforward analysis of commercial cells, real-time, non-invasive visualizing of battery inside and diagnosing battery aging have been recognized through in-operado battery imaging technology based on X-rays, neutrons, and ultrasound which can penetrate the active materials, cell components, and external packaging. Moreover, a battery imaging technique to visualize the current distribution pattern using a magnetic field induced at batteries under external current load has also been proposed. This review will comprehensively discuss the imaging techniques inside the battery from atomic and molecular levels in electrode materials and interfaces to macro-scale battery systems, and examine qualitative case studies and recently unveiled phenomena.

Battery State Estimation Algorithm for High-Capacity Lithium Secondary Battery for EVs Considering Temperature Change Characteristics

Jinho Park,Byoungkuk Lee,Do-Yang Jung,Dong-Hee Kim 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.5

In this paper, we studied the state of charge (SOC) estimation algorithm of a high-capacity lithium secondary battery for electric vehicles (EVs) considering temperature characteristics. Nonlinear characteristics of high-capacity lithium secondary batteries are represented by differential equations in the mathematical form and expressed by the state space equation through battery modeling to extract the characteristic parameters of the lithium secondary battery. Charging and discharging equipment were used to perform characteristic tests for the extraction of parameters of lithium secondary batteries at various temperatures. An extended Kalman filter (EKF) algorithm, a state observer, was used to estimate the state of the battery. The battery capacity and internal resistance of the high-capacity lithium secondary battery were investigated through battery modeling. The proposed modeling was applied to the battery pack for EVs to estimate the state of the battery. We confirmed the feasibility of the proposed study by comparing the estimated SOC values and the SOC values from the experiment. The proposed method using the EKF is expected to be highly applicable in estimating the state of the high-capacity rechargeable lithium battery pack for electric vehicles.

리튬이온(폴리머) 배터리의 화재위험성 연구

김창수,전형훈,김명관,정용식 한국화재감식학회 2020 한국화재감식학회 학회지 Vol.11 No.3

Because Li-ion battery and Li-Polymer battery have high-energy storage density, they are used for various electronic devices such as electronic cigarette, electronic bicycle, drone, second battery, even golf cart and electronic car. Recently, however, battery explosion is sometimes occurring on electronic devices using Li-ion battery and is becoming serious as bodily harm is breaking out due to explosion. For this, this paper described the Li-ion Battery’s operating principles and Fire was caused through previous research and re-testing based on exposure to foreign substances such as water from the battery in contrast. According to the these experiments, we conducted a study to develope scanning techniques of fire and safety measures. (Most previous studies have been about the risk of fire in the battery due to physical shock, overcharging, and high temperature exposure.)

전기 차 운행 데이터를 활용한 인공지능 기반의 배터리 분석 및 평가 방법 연구

홍승모 한국정보전자통신기술학회 2023 한국정보전자통신기술학회논문지 Vol.16 No.6

최근 탄소배출을 최소화하기 위해 전기자동차의 사용이 증가함에 따라 핵심 부품인 리튬이온 배터리의 상태 및 성능 분석의 중요성이 대두되고 있다. 따라서 배터리의 상태 및 성능에 영향을 줄 수 있는 배터리의 전압, 전류 및 온도뿐만 아니라 전기 자동차의 운행 데이터 및 충전 패턴 데이터를 활용한 종합적인 분석이 필요하다. 따라서 전기적 이동 수단에서 수집되는 배터리 데이터 수집 및 데이터 전처리, 단순 배터리 데이터에 추가적인 운전자 운전 습관에 대한 데이터 수집 및 전처리 , 분석된 영향인자를 기반으로 인공지능 알고리즘 세부 설계 및 수정, 해당 알고리즘을 기반으로 하는 배터리 분석 및 평가 모델 설계하였다. 본 논문에서는 실시간 전기버스를 대상으로 운행 데이터와 배터리 데이터를 수집하여 Random Forest 알고리즘 활용하여 학습시킨 후, XAI 알고리즘을 통해 배터리 상태 중요 영향인자로 배터리의 상태, 운행 및 충전 패턴 데이터 등을 종합적으로 고려하여 운행 패턴에서 급가속, 급 감속, 급정지와 충 방전 패턴에서 일 주행횟수, 일일 누적 DOD와 셀 방전에서 셀 전압 차 , 셀 최대온도, 셀 최소온도의 요소가 배터리 상태에 많은 영향을 미치는 인자로 확인되었으며, Random Forest 알고리즘 기반으로 배터리 분석 및 평가 모델을 설계하고 평가하였다. As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

Battery State Estimation Algorithm for High-Capacity Lithium Secondary Battery for EVs Considering Temperature Change Characteristics

Park, Jinho,Lee, Byoungkuk,Jung, Do-Yang,Kim, Dong-Hee The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.5

In this paper, we studied the state of charge (SOC) estimation algorithm of a high-capacity lithium secondary battery for electric vehicles (EVs) considering temperature characteristics. Nonlinear characteristics of high-capacity lithium secondary batteries are represented by differential equations in the mathematical form and expressed by the state space equation through battery modeling to extract the characteristic parameters of the lithium secondary battery. Charging and discharging equipment were used to perform characteristic tests for the extraction of parameters of lithium secondary batteries at various temperatures. An extended Kalman filter (EKF) algorithm, a state observer, was used to estimate the state of the battery. The battery capacity and internal resistance of the high-capacity lithium secondary battery were investigated through battery modeling. The proposed modeling was applied to the battery pack for EVs to estimate the state of the battery. We confirmed the feasibility of the proposed study by comparing the estimated SOC values and the SOC values from the experiment. The proposed method using the EKF is expected to be highly applicable in estimating the state of the high-capacity rechargeable lithium battery pack for electric vehicles.

정상 충방전 데이터에 기반한 리튬 이온 배터리 고장 탐지

이건희(Geonhui Lee) 한국정보과학회 2021 정보과학회 컴퓨팅의 실제 논문지 Vol.27 No.1

배터리의 고장은 탑재된 응용 전체의 성능 저하를 일으킬 뿐만 아니라, 심각한 사고로도 이어질 수 있기 때문에 고장 배터리의 진단은 매우 중요한 문제이다. 하지만 진단을 위해 고장 배터리를 확보하는 것이 현실적으로 어렵기 때문에, 정상 배터리의 데이터만을 활용해서 배터리의 고장을 찾아낼 수 있어야 한다. 이 논문에서는 머신 러닝에 기반해, 정상적인 배터리만을 사용해 고장을 진단할 수 있는 기술을 최초로 제시한다. 제안 방법론은 배터리의 정상 데이터와 이를 구성하는 인자 사이의 관계를 정의하고, 그 관계를 정확하게 예측할 수 있는 모델을 만들어 임의의 방전 프로필이 모델에 얼마나 적합한지 확인하는 방식으로 이루어진다. 제안 방법론을 검증하기 위해, NCR18650B 배터리를 사용한 실험을 진행하였고, 과방전 및 과충전 고장 데이터를 만들어 이를 구분하는지 확인했다. 그 결과, 정상 배터리 데이터의 약 96%를 정상으로 진단하는 모델을 이용해 약 97%의 정확도로 고장 배터리를 진단했다. The diagnosis of the lithium-ion battery is an important problem because of the degradation of entire application performance, as well as also the serious accidents by faulty batteries. Considering the issues of battery diagnosis, only normal battery data should be used to detect the faulty batteries, because it is practically impossible to obtain a faulty battery and its data. In this paper, we propose the first diagnosis approach using only the normal battery data based on machine learning. The approach is as follows. We define the normal battery data and the relationship between the features that constitute it, then we derive a model that can accurately predict the normal batteries. We determine the faults of the given unknown batteries by verifying how poorly the given discharging data fits the model. We evaluated the proposed methodology by conducting a case study using the NCR18650B batteries and constructing the normal battery model. We made a sample of the abnormal battery data from the overdischarge(OD) and overcharge(OC) batteries to verify if it can be diagnosed through the normal battery model. The experimental results showed that the accuracy to diagnose normal data as normal battery was approximately 96%, and the accuracy to diagnose abnormal data as faulty battery was approximately 97%.

BMS 에너지 효율 향상을 위한 리튬 배터리 SOC 계수 보정 알고리즘

이대건,정원재,임세미,채형일,박준석 한국정보통신설비학회 2016 한국정보통신설비학회 학술대회 Vol.2016 No.09

This paper describes a battery equivalent model’s SOC(state of charge) coefficient calibration method to improve the accuracy of the battery equivalent model. The battery SOC difference between each cells is a major factor of decreasing the battery life. BMS (battery management system) has been developed in order to reduce the inter-cell battery SOC deviation. however, since the general battery cell balancing techniques operate by measuring only the voltage of the battery cell, they can not keep up with the electrical characteristics due to variation of the internal resistance of the capacitor. In this paper, we propose the battery equivalent model’s SOC coefficient calibration algorithm : (1)choses the battery and battery model, (2)measure the battery charging and discharging characteristics, (3)extracting the resistance and the capacitor value on the simulation, following the actual battery charge and discharge characteristic curve. in this paper, we use a 3.7 V, 280 mAh and 650 mAh lithium battery. And a RC Tank based battery equivalent model is adopted. The maximum error of charging and discharging characteristic between measurement and modeling is approximately 2.13 %.

Implementation of the Battery Monitoring and Control System Using Edge-Cloud Computing

Alexander M. Pascual,Angela C,임완수 한국통신학회 2022 韓國通信學會論文誌 Vol.47 No.5

Battery monitoring and control are the key parts of a battery management system and are integrated on purely edge-based applications. However, purely edge-based applications face issues such as 1) difficulty in integrating methods with high computational power and complexity, 2) low speed and accuracy, and 3) limited data storage capability. Despite of those issues, previous studies only focus on battery monitoring system without considering battery control. In contrast, few studies about battery control systems still lack in control during battery discharging. In this paper, edge is integrated to cloud, performing both battery monitoring and controlling of charge and discharge states. Integrating the edge to cloud resolves the aforementioned challenges and keeps the battery within its safe operating area. In addition, a web user-interface is developed to monitor and control the battery’s state remotely. To measure the performance of the proposed system, a prototype is also developed. Using the prototype, battery control commands are sent to edge for 50 trials each without any errors encountered. Also, results shows that data transmission from edge to cloud does not skip or missed any data from 0 to 18,000 seconds and achieved the appropriate sampling time of 0.1s. Therefore, accurate and complete storing of historical data of the battery pack is achieved.

배터리 기술 발전 동향과 항공 우주 임무의 전기구동 시스템 (PART 1 : 리튬계열 배터리 및 전기추진 항공기 개발 동향)

김건영,이형진,김준겸,허환일 한국항공우주학회 2023 韓國航空宇宙學會誌 Vol.51 No.10

리튬은 낮은 밀도에 비해 단위 질량당 전기 용량이 높아 배터리의 에너지 성능을 크게 증가시켰다. 전력계의 경량화, 고효율 시스템을 구현하기 위해서는 리튬계열 배터리의 활용은 필수적이며, 항공 우주 분야는 배터리 기술 개발 트렌드에 빠르게 반응하기 때문에 배터리 종류별 특징을 이해하고 기술 개발 동향에 대한 사례 조사가 필요하다. 본 논문은 일ㆍ이차전지의 특성 및 차세대 전지와 전기추진 항공기에 대한 기술 개발 동향을 분석하였다. 차세대 이차전지에서는 리튬 금속의 음극 활용, 고체 전해질 기술이 배터리의 에너지 성능과 안정성을 향상시킬 수 있는 주요 기술로 파악된다. 항공 분야는 중ㆍ대형 항공기에 전기동력 추진 시스템을 적용하기 위한 기술 개발이 이루어지고 있으며, 차세대 전지가 적용된 비행 기술 시연 사례가 보고되고 있다. Lithium based battery, which has a high specific capacities, significantly improved battery performance. To implement a lightweight and high-efficiency power system, it is necessary to utilize lithium-based batteries. In addition, it is important to understand the characteristics of different types of batteries and the development trends of batteries, as the aerospace industry is rapidly adopting recent battery technologies. This paper analyzes the characteristics of each type of battery and the technology development trends for a next-generation battery and electrified aircraft were analyzed. In the next-generation secondary batteries, a lithium metal anode and a solid-state electrolyte are recognized as core technologies which can increase the energy performance and stability of batteries. The electrified aircraft technology is underway to apply to a medium and large sized aircraft. In addition, flight technology demonstration using a next-generation batteries is being reported.

컴퓨터 시스템 및 이론 : 배터리 자동 교체형 전기버스 운영 시스템의 개념적 설계 및 시뮬레이션

김한얼 ( Han Ur Kim ),박준석 ( Jun Seok Park ),오하령 ( Ha Ryoung Oh ),성영락 ( Yeong Rak Seong ) 한국정보처리학회 2014 정보처리학회논문지. 컴퓨터 및 통신시스템 Vol.3 No.3

배터리 교체형 전기버스는 친환경 공공교통 수단이다. 그러나 기술적 한계로 인하여, 이 버스는 소모된 배터리를 충전된 배터리로 반복해서 교체해야 한다. 현재 국내에서 연구 중인 배터리 자동 교체형 전기버스는 배터리 무인 자동교체소에서 자동으로 배터리를 교체할 수 있다. 본 논문에서는 배터리 자동 교체형 전기버스 운영 시스템을 제안한다. 제안하는 시스템은 두 가지 서비스를 제공한다. 첫째, 이 시스템은 버스 도착 알림 서비스를 제공한다. 이 서비스는 기존 대도시에서 서비스 중인 버스정보시스템의 기능으로, 버스 승객들에게 버스를 얼마나 기다려야 하는지를 알려준다. 둘째, 배터리 교체 스케줄링 서비스를 제공한다. 이 서비스는 배터리 잔량이 얼마 남아있지 않거나 배터리 교체를 원하는 버스를 완충된 배터리를 저장하고 있는 배터리 무인 자동교체소로 할당하는 역할을 한다. 제안된 시스템을 검증하기 위해서 시스템을 DEVS 형식론으로 모델링하였다. 시뮬레이션 결과, 제안된 시스템은 위의 서비스들을 충실히 수행함을 알 수 있었다. The exchangeable battery electric bus is an eco-friendly public transportation vehicle. Due to the technological limitation, however, it should repeatedly change batteries with charged ones. The unmanned battery exchangeable electric bus being studied in Korea can exchange batteries automatically by using a battery swapping system. In this paper, we propose an unmanned battery exchangeable electric bus management system. The proposed system provides two services: the bus information service and the battery change scheduling service. The bus information service is the existing traditional metropolitan area bus information systems, which inform bus passengers how long they should wait for the buses. Our second service assigns a low-battery bus, which needs to change the batteries, to the battery swapping system, which stores fully-charged batteries. To validate the proposed system, we model the system by using the DEVS formalism. The simulation result shows that the proposed system provides the services properly.