Transactions of the Korean Society of Automotive Engineers (한국자동차공학회논문집)

The Korean Society of Automotive Engineers (한국자동차공학회)
권호 표지

Modeling and Characteristic Analysis of HEV Li-ion Battery Using Recursive Least Square Estimation

최소 자승법을 이용한 하이브리드용 리튬이온 배터리 모델링 및 특성분석

  • Kim, Ho-Gi (Hybrid Vehicle Development Division, Hyundai Motor Company) ;
  • Heo, Sang-Jin (Hybrid Vehicle Development Division, Hyundai Motor Company) ;
  • Kang, Gu-Bae (Hybrid Vehicle Development Division, Hyundai Motor Company)
  • 김호기 (현대자동차(주) 하이브리드개발실) ;
  • 허상진 (현대자동차(주) 하이브리드개발실) ;
  • 강구배 (현대자동차(주) 하이브리드개발실)
  • Published : 2009.01.01
Download PDF
⟨ Previous Next ⟩

Abstract

A lumped parameter model of Li-ion battery in hybrid electric vehicle(HEV) is constructed and system parameters are identified by using recursive least square estimation for different C-rates, SOCs and temperatures. The system characteristics of pole and zero in frequency domain are analyzed with the parameters obtained from different conditions. The parameterized model of Li-ion battery indicates highly dependant of temperatures. The system pole and internal resistance changes 6.6 and 18 times at $-20^{\circ}C$, comparing with those at $25^{\circ}C$, respectively. These results will be utilized on constructing model-based state observer or an on-line identification and an adaptation of the model parameters in battery management systems for hybrid electric vehicle applications.

Keywords

References

  1. S. Buller, Impedance-Based Simulation Models for Energy Storage Devices in Advanced Automotive Power Systems, Ph. D. Dissertation, RWTH Aachen, 2002
  2. H. Yeo, D.H. Kim, T.C. Kim, C.S. Kim, S.H. Hwang and H.S. Kim, "Development of Regenerative Braking Control Algorithm for a 4WD Hybrid Electric Vehicle," Transactions of KSAE, pp.38-47, 2005
  3. B. Schweighofer, K. M. Raab and G. Brasseur, "Modeling of High Power Automotive Batteries by the Use of an Automated Test System," IEEE Transactions on Instrumentation and Measurement, Vol.52, No.4, pp.1087-1091, 2003 https://doi.org/10.1109/TIM.2003.814827
  4. M. Chen and G. A. Rincon-Mora, "Accurate Electrical Battery Model Capable of Predicting Runtime and I-V Performance," IEEE Trans. on Energy Conversion, Vol.21, No.2, pp.504-511, 2006 https://doi.org/10.1109/TEC.2006.874229
  5. L. Gao and S. Liu, "Dynamic Lithium-Ion Battery Model for System Simulation," IEEE Trans. on Components and Packaging Technologies, Vol.25, No.32, pp.495-505, 2002 https://doi.org/10.1109/TCAPT.2002.803653
  6. G. L. Plett, "Extended Kalman Filtering for Battery Management Systems of LiPB-based HEV Battery Packs, Part 2. Modeling and Identification," J. Power Sources, Vol.134, pp.262-276, 2004 https://doi.org/10.1016/j.jpowsour.2004.02.032
  7. C. C. Chan, E. W. C. Lo and S. Weixiang, "The Available Capacity Computation Model Based on Artificial Neural Network for Lead-Acid Batteries in Electric Vehicles," J. Power Sources, Vol.87, pp.201-204 https://doi.org/10.1016/S0378-7753(99)00502-9
  8. P. Singh, C. Fennie, D. Reisner and A. Salkind, "A Fuzzy Logic Approach to State-of-Charge Determination in High Performance Batteries with Applications to Electric Vehicles," Electric Vehicle Symposium, EVS-15, 1998
  9. IEEL(Idaho National Engineering & Environmental Laboratory), "Freedom CAR Battery Test Manual for Power-Assit Hybrid Electrical Vehicles, DOE/ID-11069, 2003
  10. G. F. Franklin and J. D. Powell, Digital Control of Dynamic Systems, Addison Wesley, 1980