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심층 연산자 네트워크(DeepONet)를 이용한 리튬이온 배터리 열폭주 예측
정진호,곽은지,김준형,오기용 한국비파괴검사학회 2023 한국비파괴검사학회지 Vol.43 No.2
The development of lithium-ion batteries (LIBs) has rapidly increased owing to their significant advantages. However, LIBs have several concerns related to their safety, including fires and explosions, and they suffer from the thermal runaway phenomenon, which limit their applications. This study proposes a deep operator network (DeepONet) for predicting the thermal runaway phenomenon of LIBs under a variety of thermal operational and abuse conditions. In particular, the DeepONet aims to use the functional mapping derived from a heating curve to predict the evolution of surface temperature and the dimensionless concentrations of the dominant components of LIBs, such as the anode, cathode, electrolyte, and solid-electrolyte interphase. Temperature evolution under various thermal operational and stress conditions was simulated using the high-fidelity finite element analysis (FEA) method, because thermal runaway measurements in batteries are complicated. A comparison of the DeepONet, high-fidelity FEA model, and experimental results revealed that the DeepONet has high accuracy and robustness under various thermal operational and abuse conditions. Moreover, the proposed surrogate model was considerably faster than the FEA model. Thus, the proposed surrogate model is thought to be effective for the thermal, power, and energy management of battery management systems during application. 최근 리튬이온 배터리의 다양한 장점 덕분에 리튬이온 배터리 사용량이 급격히 증가함에 따라 배터리 관련 다양한 사고사례가 급격히 증가하고 있다. 특히 리튬이온 배터리의 열폭주 현상은 폭발 및 화염으로 인하여 인명사고를 유발할 수 있기 때문에 더욱 예측 및 관리가 필요하다. 본 연구는 다양한 열 운전조건 및 남용 조건에서 배터리의 열폭주 현상을 예측하기 위한 심층 연산자 네트워크(DeepONet)를 제안한다. 구체적으로, 제안하는 심층 연산자 네트워크는 배터리에 인가되는 다양한 열 운전조건에 대한 배터리의 온도와 양극, 음극, 전해질 그리고 고체 전해질 계면의 농도 변화를 예측 가능한 모델이다. 본 연구에서 배터리의 열폭주 현상의 측정은 상당히 제한적이기 때문에 본 연구에서는 열폭주 현상을 모사 가능한 정밀한 유한 요소모델을 기반으로 다양한 열 작동 및 남용 조건에서의 데이터를 생성하고 제안 신경망을 학습하였다. 학습된 심층 연산자 네트워크는 실제 열폭주 실험결과 및 다양한 열 운전조건에서의 유한 요소 분석 결과를 통해 정확성과 견고성을 검증하였다. 제안 기법은 데이터 생성을 위해 사용한 정밀 유한요소해석 모델과 비교하여 빠르지만 동일한 정확도를 갖기 때문에, 배터리 관리 시스템에 탑재하여 효과적인 열, 전력 및 에너지 관리에 사용 가능할 것으로 사료된다.
리튬 이온 배터리의 열적 특성을 고려한 전기자동차 시뮬레이션 모델링 및 성능 분석
최원세(Wonse Choi),박태상(Taesang Park) 한국자동차공학회 2020 한국자동차공학회 부문종합 학술대회 Vol.2020 No.7
With growing concerns over fossil fuel depletion and the increasing price of crude oil, hybrid electric vehicles (HEVs), electric vehicles (EVs) and fuel cell vehicles (FCEVs) have gained more interest as a mode of transportation. Especially EV is spotlighted because platform is simple and can be easily tuned with different size motors, batteries and gear ratio. Among electric vehicle components, batteries play an increasingly critical role because the performance of EV is highly dependent on battery capacity. Specially the battery temperature is critical factor for battery operating performance. In order to investigate EV performance according to battery temperatures, this paper builds an electro-thermal model of Li-ion battery and EV powertrain using 0D/1D simulation code, AVL CRUISE M. The EV powertrain model is validated with energy consumption and 0-100km/h performance. Also, 3D CFD model of battery using AVL FIRE M is modeled which uses the same electro-thermal model and parameters with 1D battery model. This model will be used as battery cells of battery module in future research to model the battery thermal management systems (BTMS) in 0D/1D and 3D.
홍성곤(Sunggoen Hong),강덕훈(Deokhun Kang),박성윤(Seongyun Park),이평연(Pyeongyeon Lee),한승윤(Seungyun Han),김종훈(Jonghoon Kim) 한국자동차공학회 2022 한국 자동차공학회논문집 Vol.30 No.2
As the use of lithium-ion batteries increases, battery management becomes important. Among them, battery temperature management significantly affects the safety and performance of the battery. Studying battery temperature estimation is difficult, as mechanical, electrical, and chemical actions must be considered. It is also tricky to detect when temperature imbalance occurs in a parallel battery pack. In this paper, instead of detecting battery temperature imbalance through temperature estimation, temperature imbalance in a parallel battery pack can be detected through a commonly used battery parameter extraction method. As a way of detecting temperature imbalance in a battery pack, battery internal parameters through the ECM model are used. In this paper, a methodology for detecting non-uniform temperature through internal parameters is also studied. The difference based on the method was studied through parameter extraction by using the HPPC test method and the OCV recovery section. Furthermore, parameters were extracted for each SOC. Through this methodological study, the long-term performance and the safety of the battery can be improved.
xEV 배터리의 열관리를 위한 온도 예측 모델 개발에 관한 연구
정대봉(Daebong Jung),손동기(Dongkee Sohn),전진용(Jinyong Jeon) 한국자동차공학회 2016 한국자동차공학회 부문종합 학술대회 Vol.2016 No.5
In recent, xEV has been emerged as alternative solution to resolve the environment problem since it can improve fuel economy and reduce exhaust gas emission. Especially, a lithium ion battery (LIB) which has higher power and energy density than other type battery is core part of xEV since it has significant effect on the performance of xEV. However, it should be noted that thermal management system is necessary to use LIB because it is very sensitive to temperature. In this study, the thermal network model which can estimate the battery temperature in the battery module or pack has been developed based on fundamental heat transfer mechanism. The target battery module consists of cells, coolant circuit, and fixing plates. Each part is modeled as thermal mass and connected to each other through conduction and convection models. To improve accuracy of the model, multi-mass model is applied to fixing plate and coolant circuit. The simulation results were validated with the experimental data and showed good agreement by ±1℃.
원통형 리튬 이온 배터리 셀의 방전 조건에 따른 열적 특성 모델링
최원세(Won-Se Choi),김한상(Han-Sang Kim),임종훈(Jong-Hoon Im),최승현(Seung-Hyon Choi) 한국자동차공학회 2019 한국자동차공학회 학술대회 및 전시회 Vol.2019 No.11
With growing concerns over fossil fuel depletion and the increasing price of crude oil, hybrid electric vehicles (HEVs), electric vehicles (EVs) and fuel cell vehicles (FCEVs) have gained more interest as a mode of transportation. Especially EV is spotlighted because platform is simple and can be easily tuned with different size motors, batteries and gear ratio. The battery is the main energy provider which is responsible for the supply of all the electric components. But the battery cell voltage and life time are various depending on the temperature and SOC at charging-discharging conditions due to internal resistance. Hence a battery thermal management system that can provide a suitable temperature environment for working batteries is important. This paper will build an electro-thermal model which can simulate a thermal performance of NCR18650B Li-ion battery cell and developed electro-thermal model will be applied to 1D and 3D CFD codes, CRUISE M and FIRE.
김상우(Sangwoo Kim),송정용(Jungyong Song),이주열(Jooyoul Lee),도칠훈(Chilhoon Doh) 한국자동차공학회 2022 한국자동차공학회 부문종합 학술대회 Vol.2022 No.6
It is essential to design for safety as demand for lithium-ion batteries increases. In particular, thermal runaway is being dealt with in depth in the field of battery safety, and various designs are being examined in the industry. In this paper, 1D modeling is presented to make it possible to predict temperature until it reaches the battery thermal runaway state. Heat-Wait Search (HWS) test was conducted utilizing Accelerated Rate Calorimetry (ARC) equipment, and the external heat and the amount of heat generated by the battery cell itself were measured. Convection heat transfer caused by external heat and exothermic reaction spurred by internal reaction of cell and cell Equivalent Circuit Model (ECM) were 1D modeled through AMESIM S/W. In order to reduce the gap with the experimental value, the heat transfer coefficient value was corrected in the HWS section, and the internal parameters were readjusted in the exothermic reaction section. It is possible to quickly review the state of cell thermal runaway in accordance with external heating conditions, initial temperature, SOC and current conditions by utilizing the implemented 1D modeling. It is expected that the safety margin of prototypes can be considered in advance based on this study.