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Parameter and Order Identification of Fractional Systems with Application to a Lithium-Ion Battery

Author

Listed:
  • Oliver Stark

    (Faculty of Electrical Engineering and Information Technology, Institute of Control Systems (IRS), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Martin Pfeifer

    (Faculty of Electrical Engineering and Information Technology, Institute of Control Systems (IRS), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Sören Hohmann

    (Faculty of Electrical Engineering and Information Technology, Institute of Control Systems (IRS), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

Abstract

This paper deals with a method for the parameter and order identification of a fractional model. In contrast to existing approaches that can either handle noisy observations of the output signal or systems that are not at rest, the proposed method does not have to compromise between these two characteristics. To handle systems that are not at rest, the parameter, as well as the order identification, are based on the modulating function method. The novelty of the proposed method is that an optimization-based approach is used for the order identification. Thus, even if only noisy observations of the output signal are available, an approximate identification can be performed. The proposed identification method is, then, applied to identify the parameters and orders of a lithium-ion battery model. The experimental results illustrate the practical usefulness and verify the validity of our approach.

Suggested Citation

  • Oliver Stark & Martin Pfeifer & Sören Hohmann, 2021. "Parameter and Order Identification of Fractional Systems with Application to a Lithium-Ion Battery," Mathematics, MDPI, vol. 9(14), pages 1-19, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:14:p:1607-:d:590435
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    References listed on IDEAS

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    1. Hu, Minghui & Li, Yunxiao & Li, Shuxian & Fu, Chunyun & Qin, Datong & Li, Zonghua, 2018. "Lithium-ion battery modeling and parameter identification based on fractional theory," Energy, Elsevier, vol. 165(PB), pages 153-163.
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    Cited by:

    1. Peng Guo & Xiaobo Wu & António M. Lopes & Anyu Cheng & Yang Xu & Liping Chen, 2022. "Parameter Identification for Lithium-Ion Battery Based on Hybrid Genetic–Fractional Beetle Swarm Optimization Method," Mathematics, MDPI, vol. 10(17), pages 1-11, August.

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