• Title/Summary/Keyword: predict model

Search Result 8,232, Processing Time 0.033 seconds

State of Health and State of Charge Estimation of Li-ion Battery for Construction Equipment based on Dual Extended Kalman Filter (이중확장칼만필터(DEKF)를 기반한 건설장비용 리튬이온전지의 State of Charge(SOC) 및 State of Health(SOH) 추정)

  • Hong-Ryun Jung;Jun Ho Kim;Seung Woo Kim;Jong Hoon Kim;Eun Jin Kang;Jeong Woo Yun
    • Journal of the Microelectronics and Packaging Society
    • /
    • v.31 no.1
    • /
    • pp.16-22
    • /
    • 2024
  • Along with the high interest in electric vehicles and new renewable energy, there is a growing demand to apply lithium-ion batteries in the construction equipment industry. The capacity of heavy construction equipment that performs various tasks at construction sites is rapidly decreasing. Therefore, it is essential to accurately predict the state of batteries such as SOC (State of Charge) and SOH (State of Health). In this paper, the errors between actual electrochemical measurement data and estimated data were compared using the Dual Extended Kalman Filter (DEKF) algorithm that can estimate SOC and SOH at the same time. The prediction of battery charge state was analyzed by measuring OCV at SOC 5% intervals under 0.2C-rate conditions after the battery cell was fully charged, and the degradation state of the battery was predicted after 50 cycles of aging tests under various C-rate (0.2, 0.3, 0.5, 1.0, 1.5C rate) conditions. It was confirmed that the SOC and SOH estimation errors using DEKF tended to increase as the C-rate increased. It was confirmed that the SOC estimation using DEKF showed less than 6% at 0.2, 0.5, and 1C-rate. In addition, it was confirmed that the SOH estimation results showed good performance within the maximum error of 1.0% and 1.3% at 0.2 and 0.3C-rate, respectively. Also, it was confirmed that the estimation error also increased from 1.5% to 2% as the C-rate increased from 0.5 to 1.5C-rate. However, this result shows that all SOH estimation results using DEKF were excellent within about 2%.

Numerical Study on Thermochemical Conversion of Non-Condensable Pyrolysis Gas of PP and PE Using 0D Reaction Model (0D 반응 모델을 활용한 PP와 PE의 비응축성 열분해 기체의 열화학적 전환에 대한 수치해석 연구)

  • Eunji Lee;Won Yang;Uendo Lee;Youngjae Lee
    • Clean Technology
    • /
    • v.30 no.1
    • /
    • pp.37-46
    • /
    • 2024
  • Environmental problems caused by plastic waste have been continuously growing around the world, and plastic waste is increasing even faster after COVID-19. In particular, PP and PE account for more than half of all plastic production, and the amount of waste from these two materials is at a serious level. As a result, researchers are searching for an alternative method to plastic recycling, and plastic pyrolysis is one such alternative. In this paper, a numerical study was conducted on the pyrolysis behavior of non-condensable gas to predict the chemical reaction behavior of the pyrolysis gas. Based on gas products estimated from preceding literature, the behavior of non-condensable gas was analyzed according to temperature and residence time. Numerical analysis showed that as the temperature and residence time increased, the production of H2 and heavy hydrocarbons increased through the conversion of the non-condensable gas, and at the same time, the CH4 and C6H6 species decreased by participating in the reaction. In addition, analysis of the production rate showed that the decomposition reaction of C2H4 was the dominant reaction for H2 generation. Also, it was found that more H2 was produced by PE with higher C2H4 contents. As a future work, an experiment is needed to confirm how to increase the conversion rate of H2 and carbon in plastics through the various operating conditions derived from this study's numerical analysis results.