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State of Charge Estimation for Lithium-Ion Battery by Using Dual Square Root Cubature Kalman Filter

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  • Luping Chen
  • Liangjun Xu
  • Ruoyu Wang

Abstract

The state of charge (SOC) plays an important role in battery management systems (BMS). However, SOC cannot be measured directly and an accurate state estimation is difficult to obtain due to the nonlinear battery characteristics. In this paper, a method of SOC estimation with parameter updating by using the dual square root cubature Kalman filter (DSRCKF) is proposed. The proposed method has been validated experimentally and the results are compared with dual extended Kalman filter (DEKF) and dual square root unscented Kalman filter (DSRUKF) methods. Experimental results have shown that the proposed method has the most balance performance among them in terms of the SOC estimation accuracy, execution time, and convergence rate.

Suggested Citation

  • Luping Chen & Liangjun Xu & Ruoyu Wang, 2017. "State of Charge Estimation for Lithium-Ion Battery by Using Dual Square Root Cubature Kalman Filter," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-10, December.
    • Handle: RePEc:hin:jnlmpe:5489356
    DOI: 10.1155/2017/5489356
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    Cited by:

    1. Shuaishuai Zhang & Youhong Wan & Jie Ding & Yangyang Da, 2021. "State of Charge (SOC) Estimation Based on Extended Exponential Weighted Moving Average H ∞ Filtering," Energies, MDPI, vol. 14(6), pages 1-15, March.

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