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Frequency and time domain modelling and online state of charge monitoring for ultracapacitors

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  • Tian, Jinpeng
  • Xiong, Rui
  • Shen, Weixiang
  • Wang, Ju

Abstract

Ultracapacitors are common power sources for new energy vehicles with the advantage of providing high current and power. Modelling and state of charge (SOC) estimation of ultracapacitors are still a research focus. In this study, a fractional order model (FOM), which is derived from the analysis of electrochemical impedance spectroscopy, is established for ultracapacitors and validated in frequency and time domains. After analyzing characteristics of an ultracapacitor and its open circuit voltage, the established FOM is combined with a fractional order Unscented Kalman filter to realize SOC estimation for ultracapacitors. Results show that the proposed method can estimate SOC more accurately than traditional SOC methods. Furthermore, an online joint estimation method for SOC and FOM parameters is proposed and validated by a hardware-in-the-loop platform, indicating that the FOM can be used for onboard applications.

Suggested Citation

  • Tian, Jinpeng & Xiong, Rui & Shen, Weixiang & Wang, Ju, 2019. "Frequency and time domain modelling and online state of charge monitoring for ultracapacitors," Energy, Elsevier, vol. 176(C), pages 874-887.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:874-887
    DOI: 10.1016/j.energy.2019.04.034
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    References listed on IDEAS

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    1. Wang, Ju & Xiong, Rui & Li, Linlin & Fang, Yu, 2018. "A comparative analysis and validation for double-filters-based state of charge estimators using battery-in-the-loop approach," Applied Energy, Elsevier, vol. 229(C), pages 648-659.
    2. Li, Yanwen & Wang, Chao & Gong, Jinfeng, 2016. "A combination Kalman filter approach for State of Charge estimation of lithium-ion battery considering model uncertainty," Energy, Elsevier, vol. 109(C), pages 933-946.
    3. Wang, Chun & He, Hongwen & Zhang, Yongzhi & Mu, Hao, 2017. "A comparative study on the applicability of ultracapacitor models for electric vehicles under different temperatures," Applied Energy, Elsevier, vol. 196(C), pages 268-278.
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    Cited by:

    1. Wang, Chun & Yang, Ruixin & Yu, Quanqing, 2019. "Wavelet transform based energy management strategies for plug-in hybrid electric vehicles considering temperature uncertainty," Applied Energy, Elsevier, vol. 256(C).

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