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An Overview of Complex Instability Behaviors Induced by Nonlinearity of Power Electronic Systems with Memristive Load

Author

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  • Hongbo Cao

    (State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Faqiang Wang

    (State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

The proposal of the memristor, considered as the fourth basic circuit element, suggests a new possibility for the design of high-performance power electronic systems. However, it also brings new challenges. At present, more and more electrical equipment and systems have demonstrated that their external characteristics can exhibit “8”-shaped hysteresis loops and can be regard as memristive equipment and systems. In order to satisfy the requirements of controllability, flexibility, efficiently, and so on, most memristive equipment and systems are not directly connected to the power grid but instead obtain their own required powering through various forms of power electronic converters. Note that memristive loads are distinctive and demonstrate unique nonlinear behaviors. Similarly, there can be nonlinearity from the resistor ( R ), inductor ( L ), or capacitor ( C ) load, but there is no combination of only R , L , and C that could produce memristive characteristics. In particular, the memristance of memristive devices changes continuously during the operation process; in addition, practical power electronic systems composed of memristive devices and power supplies have strong nonlinear characteristics, which are more likely to result in various complex behaviors and are not conducive to the stable operation of the systems. Therefore, exploring complex instability behaviors of power electronic systems with strong nonlinearity in depth is necessary for better protection and utilization of memristive devices. This paper provides an outline of the status of research on complex behaviors of power electronic systems with memristive load; it is expected to provide guidance for the study of complex behavior of strongly nonlinear systems.

Suggested Citation

  • Hongbo Cao & Faqiang Wang, 2023. "An Overview of Complex Instability Behaviors Induced by Nonlinearity of Power Electronic Systems with Memristive Load," Energies, MDPI, vol. 16(6), pages 1-25, March.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2528-:d:1090278
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    References listed on IDEAS

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    1. Bao, Bocheng & Zhang, Xi & Bao, Han & Wu, Pingye & Wu, Zhimin & Chen, Mo, 2019. "Dynamical effects of memristive load on peak current mode buck-boost switching converter," Chaos, Solitons & Fractals, Elsevier, vol. 122(C), pages 69-79.
    2. Yuehui Chen & Zhao Huang & Zhenfeng Duan & Pengwu Fu & Guandong Zhou & Longfu Luo, 2019. "A Four-Winding Inductive Filtering Transformer to Enhance Power Quality in a High-Voltage Distribution Network Supplying Nonlinear Loads," Energies, MDPI, vol. 12(10), pages 1-13, May.
    3. Sun, Yuanyuan & Xie, Xiangmin & Wang, Qingyan & Zhang, Linghan & Li, Yahui & Jin, Zongshuai, 2020. "A bottom-up approach to evaluate the harmonics and power of home appliances in residential areas," Applied Energy, Elsevier, vol. 259(C).
    4. Yu, Pei & Leung, A.Y.T., 2007. "The simplest normal form and its application to bifurcation control," Chaos, Solitons & Fractals, Elsevier, vol. 33(3), pages 845-863.
    5. Dmitri B. Strukov & Gregory S. Snider & Duncan R. Stewart & R. Stanley Williams, 2008. "The missing memristor found," Nature, Nature, vol. 453(7191), pages 80-83, May.
    6. Guokai Zhao & Bin You & Xuan Wen & GuoQing Luo, 2022. "A reconfigurable dual-band bandpass filter using memristive switches," Journal of Electromagnetic Waves and Applications, Taylor & Francis Journals, vol. 36(1), pages 115-130, January.
    7. Xiu, Chunbo & Zhou, Ruxia & Liu, Yuxia, 2020. "New chaotic memristive cellular neural network and its application in secure communication system," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    Full references (including those not matched with items on IDEAS)

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