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Traction Load Modeling and Parameter Identification Based on Improved Sparrow Search Algorithm

Author

Listed:
  • Zhensheng Wu

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Deling Fan

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Fan Zou

    (Department of Earth Science, Uppsala University, 62157 Visby, Sweden)

Abstract

In this paper, a traction load model parameter identification method based on the improved sparrow search algorithm (ISSA) is proposed. According to the load characteristics of the AC traction power supply system under transient disturbance, the model structure of the traction load is equated to the composite load model structure of the static load shunt induction motor’s dynamic load. The traditional sparrow search algorithm is improved to enhance its accuracy and convergence. The generalization ability of the model was tested, and the accuracy of the proposed model was verified. Using the ISSA to determine the load model from the measured data, the results can verify the effectiveness of the ISSA for comprehensive load model parameter identification. Comparing the ISSA with the traditional SSA and PSO algorithms, it shows that the ISSA has better accuracy and convergence.

Suggested Citation

  • Zhensheng Wu & Deling Fan & Fan Zou, 2022. "Traction Load Modeling and Parameter Identification Based on Improved Sparrow Search Algorithm," Energies, MDPI, vol. 15(14), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5034-:d:859562
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