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Eunsong Kim,Minseon Kim,Juo Kim,Joonchul Kim,Jung-Hwan Park,Kyoung-Tak Kim,Joung-Hu Park,Taesic Kim,Kyoungmin Min 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.24 No.7
Lithium-ion batteries are widely used in electric vehicles, electronic devices, and energy storage systems owing to their high energy density, long life, and outstanding performance. However, various internal and external factors affect the battery performance, leading to deterioration and ageing. Accurately estimating the state of health (SOH), state of charge (SOC), and remaining useful life (RUL) of batteries is challenging owing to complex operating characteristics and changing internal physical parameters. With the increasing availability of shared battery data and improved computer performance, the use of data-driven methods for battery health estimations and RUL predictions has gained popularity. We provide a comprehensive review of several studies in which data-driven methods were used for SOC and SOH estimation and RUL prediction. Specifically, we focus on the importance of open battery-cycling databases, various prediction methods used, and results obtained using each of these methods. Moreover, we aim to facilitate further research by providing a comprehensive description of the current state-of-the-art methods employed in battery health estimation and RUL prediction using open databases and machine-learning algorithms. Thus, we hope that this review will help researchers to develop accurate and reliable predictive models for battery health assessment in the future.
IEEE 2030.5 네트워크 프로토콜을 이용한 실시간 Hardware-in-the-Loop (HIL) 분산 에너지 자원 시스템 시뮬레이터
김진산(Jin San Kim),노영태(Young Tae Noh),Taesic Kim 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
본 논문은 최근 분산 에너지 자원의 표준 네트워크 프로토콜로 선정된 IEEE 2030.5를 이용하여 분산 에너지 자원들을 실시간 시뮬레이션할 수 있는 Hardware-in-the-Loop (HIL) 시뮬레이터를 제안한다. 파워 인버터를 기반으로 하는 분산 자원들은 Matlab/Simulink에서 생성되었으며, OPAL-RT를 연동하여 실시간 분산 자원 시뮬레이션 모델을 제작하였다. 각 분산 자원 네트워크 레이어를 라즈베리파이로 구현하였고 분산 자원 컨트롤 서버를 구축하였다. 그리고 IEEE 2030.5의 클라이언트와 서버 프로토콜을 라즈베리 파이와 컨트롤 서버에 각각 구현하여 실시간 분산 자원 통신을 모사하였다.
모델링 기법과 에너지 흐름 측정 방법을 활용한 하이브리드 차량의 연비 분석 및 개발
박태식(Taesic Park),김석준(Seokjoon Kim),이종호(Jongho Lee),민병순(Byungsoon Min) 한국자동차공학회 2010 한국자동차공학회 부문종합 학술대회 Vol.2010 No.5
As oil prices rise and the government strengthens fuel economy regulation, fuel economy became an important factor in buying a car. To develop high mileage vehicles, analysis of effect of each component on fuel economy is needed. Effect of each component on fuel economy is calculated by measuring energy flow between components and it depends on efficiency of component and control logic of system. In this paper, analysis method for different kinds of systems such as series, parallel and power-split was described and it applied on developing vehicle. Through comparison between competitive vehicle and developing vehicle, strength and weakness of system were found and effect of system improvement was measured. Modeling technique was used to analyze control logic of competitive vehicle and show fuel economy effect of control logic.
Chun Wei,Mouhacine Benosman,Taesic Kim 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.11
Accurate state-of-power (SOP) estimation is critical for building battery systems with optimized performance and longer life in electric vehicles and hybrid electric vehicles. This paper proposes a novel parameter identification method and its implementation on SOP prediction for lithium-ion batteries. The extremum seeking algorithm is developed for identifying the parameters of batteries on the basis of an electrical circuit model incorporating hysteresis effect. A rigorous convergence proof of the estimation algorithm is provided. In addition, based on the electrical circuit model with the identified parameters, a battery SOP prediction algorithm is derived, which considers both the voltage and current limitations of the battery. Simulation results for lithium-ion batteries based on real test data from urban dynamometer driving schedule (UDDS) are provided to validate the proposed parameter identification and SOP prediction methods. The proposed method is suitable for real operation of embedded battery management system due to its low complexity and numerical stability.
주행 상황 예측을 통한 하이브리드 차량의 연비 향상 기술 개발
민병순(Byungsoon Min),박태식(Taesic Park),김인섭(Insup Kim),서범주(BuhmJoo Suh),이재헌(Jaeheon Lee),김석준(Seokjoon Kim) 한국자동차공학회 2011 한국자동차공학회 학술대회 및 전시회 Vol.2011 No.11
It is well known that the hybrid electric vehicle (HEV) which can improve the efficiency of power train by the control of electric power source has better fuel economy than the conventional vehicles. However, the electric power source can be limited because of stability of PE components and continuity of control satisfying any driving condition so that the fuel economy may be lowered according to driving condition. At this moment, if the driving condition such as road and traffic condition can be predicted, the use of electric power source will be controlled appropriately in order to improve the fuel economy of HEV. For example, if a hill road is expected in a few minutes, the controller of HEV will charge a battery sufficiently in order to avoid operating at full load part of engine as driving on the uphill road. When the vehicle is expected to drive downhill, the battery of HEV will be discharged to low SOC so that the battery is more charged from regenerative braking than a HEV with normal control strategy during downhill. Consequently, the fuel economy of HEV is improved. Additionally, while the vehicle is predicted to meet congestion, charging the battery and discharge during congestion improve the efficiency of vehicle. This paper proposes the fuel economy improvement technique for hybrid electric vehicle by using driving condition prediction. The effectiveness of the algorithm and method for using driving environment prediction has been confirmed by PSAT simulation as well as driving test. After collecting the GPS data of a specific route, the improvement of fuel economy is confirmed by using simulation model of Sonata Hybrid at PSAT and by fleet test of Sonata HEV.