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A Parameter Identification Method for Dynamics of Lithium Iron Phosphate Batteries Based on Step-Change Current Curves and Constant Current Curves

Author

Listed:
  • Zhichao He

    (Department of Automation, Tsinghua University, Beijing 100084, China)

  • Geng Yang

    (Department of Automation, Tsinghua University, Beijing 100084, China)

  • Languang Lu

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China)

Abstract

Parameterization of battery dynamics based on terminal operating data is a main concern in engineering applications of batteries. The key technology is designing an adequate test procedure and a data processing procedure to excite different inner dynamics and then estimate the parameters of a corresponding equivalent circuit model (ECM). This paper proposes a parameter identification method that utilizes the terminal voltage curves (TVC) under step-change current conditions and constant current conditions. With this method, I - V characteristics of battery’s Ohmic resistance, mass diffusion process, thermal process and SOC varying process are decoupled and parametric functions of an ECM are obtained. Experimental results show that the method is easy to be implemented and modeling accuracy is sufficient for applications.

Suggested Citation

  • Zhichao He & Geng Yang & Languang Lu, 2016. "A Parameter Identification Method for Dynamics of Lithium Iron Phosphate Batteries Based on Step-Change Current Curves and Constant Current Curves," Energies, MDPI, vol. 9(6), pages 1-24, June.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:6:p:444-:d:71749
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    References listed on IDEAS

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    1. Daehyun Kim & Keunhwi Koo & Jae Jin Jeong & Taedong Goh & Sang Woo Kim, 2013. "Second-Order Discrete-Time Sliding Mode Observer for State of Charge Determination Based on a Dynamic Resistance Li-Ion Battery Model," Energies, MDPI, vol. 6(10), pages 1-14, October.
    2. Shifei Yuan & Hongjie Wu & Chengliang Yin, 2013. "State of Charge Estimation Using the Extended Kalman Filter for Battery Management Systems Based on the ARX Battery Model," Energies, MDPI, vol. 6(1), pages 1-27, January.
    3. Fei Feng & Rengui Lu & Chunbo Zhu, 2014. "A Combined State of Charge Estimation Method for Lithium-Ion Batteries Used in a Wide Ambient Temperature Range," Energies, MDPI, vol. 7(5), pages 1-29, May.
    4. Jaeshin Yi & Boram Koo & Chee Burm Shin, 2014. "Three-Dimensional Modeling of the Thermal Behavior of a Lithium-Ion Battery Module for Hybrid Electric Vehicle Applications," Energies, MDPI, vol. 7(11), pages 1-16, November.
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    Cited by:

    1. Yingjie Chen & Geng Yang & Xu Liu & Zhichao He, 2019. "A Time-Efficient and Accurate Open Circuit Voltage Estimation Method for Lithium-Ion Batteries," Energies, MDPI, vol. 12(9), pages 1-20, May.
    2. Qingxia Yang & Jun Xu & Binggang Cao & Xiuqing Li, 2017. "A simplified fractional order impedance model and parameter identification method for lithium-ion batteries," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.

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