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A New State of Charge Estimation Method for LiFePO 4 Battery Packs Used in Robots

Author

Listed:
  • Ming-Hui Chang

    (Department of Mechanical Engineering, National Taiwan University, Taipei 10617, Taiwan)

  • Han-Pang Huang

    (Department of Mechanical Engineering, National Taiwan University, Taipei 10617, Taiwan)

  • Shu-Wei Chang

    (Graduate Institute of Industrial Engineering, National Taiwan University, Taipei 10617, Taiwan)

Abstract

The accurate state of charge (SOC) estimation of the LiFePO 4 battery packs used in robot applications is required for better battery life cycle, performance, reliability, and economic issues. In this paper, a new SOC estimation method, “Modified ECE + EKF”, is proposed. The method is the combination of the modified Equivalent Coulombic Efficiency (ECE) method and the Extended Kalman Filter (EKF) method. It is based on the zero-state hysteresis battery model, and adopts the EKF method to correct the initial value used in the Ah counting method. Experimental results show that the proposed technique is superior to the traditional techniques, such as ECE + EKF and ECE + Unscented Kalman Filter (UKF), and the accuracy of estimation is within 1%.

Suggested Citation

  • Ming-Hui Chang & Han-Pang Huang & Shu-Wei Chang, 2013. "A New State of Charge Estimation Method for LiFePO 4 Battery Packs Used in Robots," Energies, MDPI, vol. 6(4), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:4:p:2007-2030:d:24808
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    References listed on IDEAS

    as
    1. Xiaosong Hu & Fengchun Sun & Yuan Zou, 2010. "Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer," Energies, MDPI, vol. 3(9), pages 1-18, September.
    2. Sun, Fengchun & Hu, Xiaosong & Zou, Yuan & Li, Siguang, 2011. "Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles," Energy, Elsevier, vol. 36(5), pages 3531-3540.
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