DOI QR코드

DOI QR Code

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

  • Park, Jinho (Department of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Lee, Byoungkuk (Department of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Jung, Do-Yang (PNE SYSTEMS Corporation) ;
  • Kim, Dong-Hee (Department of Electrical Engineering, Chonnam National University)
  • Received : 2018.01.11
  • Accepted : 2018.04.03
  • Published : 2018.09.01

Abstract

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.

Acknowledgement

Supported by : National Research Foundation of Korea(NRF)

References

  1. D. H. Kim, M. J. Kim, and B. K. Lee, "An Integrated Battery Charger with High Power Density and Efficiency for Electric Vehicles," IEEE Trans. Power Electr., vol. 32, no. 6, pp. 4553-4565, June 2017. https://doi.org/10.1109/TPEL.2016.2604404
  2. A. Emadi, Y. J. Lee, K. Rajashekara, "Power electronics and motor drives in electric, hybrid electric, and plug-in hybrid electric vehicles" IEEE Trans. Ind. Electron., vol. 55, no. 6, pp. 2237-2245, Jun. 2008. https://doi.org/10.1109/TIE.2008.922768
  3. Y. Xing, W. He, M. Pecht, K. L. Tsui, "State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures," Applied Energy, vol. 113, pp. 106-115, Jan. 2014. https://doi.org/10.1016/j.apenergy.2013.07.008
  4. J. Yi, U. S. Kim, C. B. Shin, T. Han, S. Park, "Modeling the temperature dependence of the discharge behavior of a lithium-ion battery in low environmental temperature," Journal of Power Sources, vol. 244, pp. 143-148, Dec. 2013. https://doi.org/10.1016/j.jpowsour.2013.02.085
  5. C. Hu, B. D. Youn, J. Chung "A multiscale framework with extended Kalman filter for lithium-ion battery SOC and capacity estimation," Applied Energy, vol. 92, pp. 694-704, Apr. 2012. https://doi.org/10.1016/j.apenergy.2011.08.002
  6. Plett, G., "Extended Kalman Filtering for Battery Management Systems of LiPB-Based HEV Battery Packs-Part 1: Background," Journal of Power Sources, vol. 134, no. 2, pp. 252-261, Aug. 2004. https://doi.org/10.1016/j.jpowsour.2004.02.031
  7. Plett, G., "Extended Kalman Filtering for Battery Management Systems of LiPB-Based HEV Battery Packs-Part 2: Modeling and Identification," Journal of Power Sources, vol. 134, no. 2, pp. 262-276, Aug. 2004. https://doi.org/10.1016/j.jpowsour.2004.02.032
  8. Plett, G., "Extended Kalman Filtering for Battery Management Systems of LiPB-Based HEV Battery Packs-Part 3: State and Parameter Estimation," Journal of Power Sources, vol. 134, no. 2, pp. 277-292, Aug. 2004. https://doi.org/10.1016/j.jpowsour.2004.02.033
  9. Plett, G., "Recursive approximate weighted total least squares estimation of battery cell total capacity," Journal of Power Sources, vol. 196, no. 4, pp. 2319-2331, Feb. 2011. https://doi.org/10.1016/j.jpowsour.2010.09.048