KEPCO Journal on Electric Power and Energy

Korea Electric Power Corporation (한국전력공사)
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Computational Simulation on Power Prediction of Lithium Secondary Batteries by using Pulse-based Measurement Methods

펄스 측정법에 기반한 리튬이차전지 출력 측정에 관한 전산 모사

  • Park, Joonam (Department of Chemical and Biological Eng., Hanbat National Univ.) ;
  • Byun, Seoungwoo (Department of Chemical and Biological Eng., Hanbat National Univ.) ;
  • Appiah, Williams Agyei (Department of Chemical and Biological Eng., Hanbat National Univ.) ;
  • Han, Sekyung (Department of Electrical Engineering, Kyungpook National University) ;
  • Choi, Jin Hyeok (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Ryou, Myung-Hyun (Department of Chemical and Biological Eng., Hanbat National Univ.) ;
  • Lee, Yong Min (Department of Chemical and Biological Eng., Hanbat National Univ.)
  • Published : 2015.09.30
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Abstract

Energy storage systems (ESSs) have been utilized widely in the world to optimize the power operation system and to improve the power quality. As lithium secondary batteries are the main power supplier for ESSs, it is very important to predict its cycle and power degradation behavior. In particular, the power, one of the hardest electrochemical properties to measure, needs lots of resources such as time and facilities. Due to these difficulties, computer modelling of lithium secondary batteries is applied to predict the DC-IR and power value during charging and discharging as a function of state of charge (SOC) by using pulse-based measurement methods. Moreover, based on the hybrid pulse power characteristics (HPPC) and J-Pulse (JEVS D 713, Japan Electric Vehicle Association Standards) methods, their electrochemical properties are also compared and discussed.

시간대별 효율적인 전력 운영과 전력품질 향상을 위해 ESS (Energy Storage System)의 보급이 세계적으로 활발하게 이루어지고 있다. 이러한 ESS용 전원소자로 리튬이차전지의 채용이 급격히 늘어남에 따라, 리튬이차전지의 수명 및 출력 열화 거동을 측정 및 예측하는 기술이 시급히 요구되고 있다. 특히, ESS 운영에 있어 핵심 특성인 리튬이차 전지 출력은 측정이 어려울 뿐만 아니라, 정확한 측정을 위해서는 많은 시간이 소요되는 문제점이 있다. 따라서, 본 연구에서는 ESS용 리튬이차전지 단전지를 전산 모델링 한 후, 펄스 측정법을 적용하여 충전상태에 따른 방전 및 충전시의 직류저항(DC-IR)과 출력을 예측한다. 또한, 두 가지 펄스 측정법인 HPPC (Hybrid Pulse Power Characteristics)와 J-Pulse (JEVS D 713, Japan Electric Vehicle Association Standards)의 결과를 비교 분석한다.

Keywords

References

  1. Cho, J., Jeong, S. & Kim, Y., "Commercial and research battery technologies for electrical energy storage applications," Progress in Energy and Combustion Science, 48, pp.84-101, June, 2015.
  2. Hongjae Myung., "Consideration for Technical Trend of Large Scale BESS PCS," Power Electronics Annual Conference, The Korean Institute of Power Electronics, Koera, yesan, 2011, pp.273-272
  3. Geon-Pyo Lim, Hyun-Gyu Han, Byung-Hoon Chang, Seung-Kwon Yang, Yong-Beum Yoon, "Demonstration to Operate and Control Frequency Regulation of Power System by 4MW Energy Storeage System," The Transactions of the Korean Institute of Electrical Engineers P, 2014, pp.169-177
  4. Divya, K. & O stergaard, J., "Battery energy storage technology for power systems An overview," Electric Power Systems Research, 79, pp.511-520, September, 2009. https://doi.org/10.1016/j.epsr.2008.09.017
  5. Poullikkas, A. "A comparative overview of large-scale battery systems for electricity storage," Renewable and Sustainable Energy Reviews, 27, pp.778-788, July, 2013. https://doi.org/10.1016/j.rser.2013.07.017
  6. Doyle, M., Fuller, T. F. & Newman, J., "Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell," Journal of the Electro chemical Society, 140, pp.1526-1533, January, 1993. https://doi.org/10.1149/1.2221597
  7. Doyle, M., Newman, J., Gozdz, A. S., Schmutz, C. N. & Tarascon, J. M., "Comparison of modeling predictions with experimental data from plastic lithium ion cells," Journal of the Electrochemical Society, 143, pp.1890-1903, June, 1996. https://doi.org/10.1149/1.1836921
  8. Mao, J., Tiedemann, W. & Newman, J., "Simulation of temperature rise in Li-ion cells at very high currents," Journal of Power Sources, 271, pp.444-454, August, 2014. https://doi.org/10.1016/j.jpowsour.2014.08.033
  9. Hyewon Lee & Yong Min Lee., "Principles and Comparative Studies of Various Power Measurement Methods for Lithium Secondary Batteries ," Journal of the Korean Electrochemical Society, 10(3), pp.115-123, August, 2012.
  10. Younghoon Kim, Songhun Yoon, "Electrochemical Characterization Methods for Lithium Secondary Batteries,"Polymer Science and Technology, 23(3), pp.307-312, June, 2012.
  11. Sukbeom You, Joosik Jung, Kyeong-Beom Cheong and Jooyoung Go., "Numerical Simulation of Lithium-Ion Batteries for Electic Vehicles," 'Journal of Mechanical Science and Technology B, 35(6), pp.649-656, March, 2011.
  12. Dae-Hyun Lee & Do-young Yoon., "Computational Modeling of Charge-Discharge Characteristics of Lithium-Ion Batteries," Journal of Energy Engineering, 20(4), pp.278-285, November, 2011. https://doi.org/10.5855/ENERGY.2011.20.4.278
  13. Wang, C.-W. & Sastry, A. M., "Mesoscale modeling of a Li-ion polymer cell," Journal of The Electrochemical Society, 154(11), A1035-A1047, August, 2007. https://doi.org/10.1149/1.2778285
  14. Vyroubal, P., Maxa, J., Kazda, T. & Vondrak, J., "The Finite Element Method in Electrochemistry Modelling of the Lithium-Ion Battery," ECS Transactions, Journal of Power Sorces, U.S. San Francisco, 2014, 48, pp.289-296 https://doi.org/10.1149/04801.0289ecst
  15. Xu, M., Zhang, Z., Wang, X., Jia, L. & Yang, L., "A pseudo three-dimensional electrochemical-thermal model of a prismatic LiFePO 4 battery during discharge process," Energy, 80, pp.303-317, February, 2015. https://doi.org/10.1016/j.energy.2014.11.073

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