The Transactions of the Korean Institute of Power Electronics (전력전자학회논문지)

The Korean Institute of Power Electronics (전력전자학회)
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The Research on the Modeling and Parameter Optimization of the EV Battery

전기자동차 배터리 모델링 및 파라미터 최적화 기법 연구

  • Kim, Il-Song (Dept. of Electrical Eng., Korea Nat'l Univ of Transportation)
  • Received : 2020.01.30
  • Accepted : 2020.03.10
  • Published : 2020.06.20
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Abstract

This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.

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References

  1. Jin Xu et al., “The state of charge estimation of lithium-ion batteries based on a proportional-integral observer,” IEEE TRANS. Vehicular Technology, Vol. 63, No. 4, pp. 1614-1621, May 2014. https://doi.org/10.1109/TVT.2013.2287375
  2. L. Xu, J. Wang, and Q. Chen, "Kalman filtering state of charge estimation for battery management system based on a stochastic fuzzy neural network battery model," Energy Convers. Manag., Vol. 53, No. 1, pp. 33-39. Jan. 2012. https://doi.org/10.1016/j.enconman.2011.06.003
  3. X. Hu, F. Sun, and Y. Zou, “Estimation of state of charge of a lithium-ion battery pack for electric vehicles using an adaptive luenberger observer,” Energies, Vol. 3, No. 9, pp. 1586-1603, Sep. 2010. https://doi.org/10.3390/en3091586
  4. C. Lin, F. Zhang, H. Xue, and X. Lu, "Estimation of battery state of charge using H-infinity observer," in Proc. 7th IPEMC, pp. 422-428. 2012.
  5. F. Zhang, G. Liu, L. Fang, and H. Wang, "Estimation of battery state of charge with H$\infty$ observer: Applied to a robot for inspecting power transmission lines," IEEE Trans. Ind. Electron., Vol. 59, No. 2, pp. 1088-1095, Feb. 2012.
  6. A. P. Schmidt et al., "Lumped parameter modeling of electrochemical and thermal dynamics in lithium-ion batteriesm," in IFAC Proc. Volumes, Vol. 43, No. 7, pp. 198-203, Jul. 2010.
  7. K. Y. Oh et al., "A novel phenomenological multi-physics model of li-ion battery cells," Journal of Power Sources, Vol. 326, pp. 447-458, Sep. 2016. https://doi.org/10.1016/j.jpowsour.2016.07.019
  8. A. Fotouhi et al., "A review on electric vehicle battery modelling: From lithium-ion toward lithium-sulphur," Renewable Sustainable Energy Review, Vol. 56, pp. 1008-1021, 2016. https://doi.org/10.1016/j.rser.2015.12.009
  9. S. Nejad, D. T. Gladwin, and D. A. Stone, "A systematic review of lumped-parameter equivalent circuit models for real-time estimation of lithium-ion battery states," Journal of Power Sources, Vol. 316, pp. 183-196. 2016. https://doi.org/10.1016/j.jpowsour.2016.03.042
  10. H. He, R. Xiong, and J. Fan, "Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach," Energies, Vol. 4, pp. 582-598, Mar. 2011. https://doi.org/10.3390/en4040582
  11. C. Lin, "Comparison of current input equvialent circuit models of electrical vehicle battery," Chin. J. Mech. Eng., Vol. 41, pp. 76-81, Dec. 2005. https://doi.org/10.3901/JME.2005.12.076
  12. G. L. Plett, "Extended kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 1. background," Journal of Power Sources, Vol. 134, pp. 252-261, Aug. 2004. https://doi.org/10.1016/j.jpowsour.2004.02.031
  13. G. L Plett, "Extended kalman filtering for battery management systems of LiPB-based HEV battery packs. Part 2. modeling and identification," Journal of Power Sources, Vol. 134, pp. 262-276, Aug. 2004. https://doi.org/10.1016/j.jpowsour.2004.02.032