Journal of Power Electronics

  • 제23권3호
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  • Pages.499-509
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  • 2023
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  • 1598-2092(pISSN)
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  • 2093-4718(eISSN)
전력전자학회 (The Korean Institute of Power Electronics)
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DOI QR코드

DOI QR Code

Multi-condition dynamic model control strategy of the direct drive motor of electric vehicles based on PIO-LightGBM algorithm

  • Fang Xie (School of Electrical Engineering and Automation, Anhui University) ;
  • Wenyu Zhang (School of Electrical Engineering and Automation, Anhui University) ;
  • Mengyuan Shen (School of Electrical Engineering and Automation, Anhui University) ;
  • Jinqiang Zhang (School of Electrical Engineering and Automation, Anhui University)
  • 투고 : 2022.06.12
  • 심사 : 2022.10.30
  • 발행 : 2023.03.20
⟨ 이전 논문 다음 논문 ⟩

초록

Permanent magnet synchronous motor (PMSM) is widely used in new energy vehicles. At present, to make electric vehicles have a wider speed range, the motor can reach the rated speed above through the field-weakening control. However, when the traditional field-weakening control strategy is above the rated speed, the dynamic response ability of the vehicle declines. Problems such as torque oscillation and current jump occur. To solve these problems, based on a pigeon-inspired optimization (PIO) algorithm and optimized light gradient boosting machine (LightGBM), the dynamic response capability of the permanent magnet synchronous motor is improved. The robust adaptability of the control system to disturbances and parameter changes is also further improved. By collecting experimental data, the importance of relevant variables is analyzed, and the variable with the largest weight is selected as the input of the model. PIO is used to optimize LightGBM, and the loss function is optimized. Finally, the regression model is established. Simulation and experimental results show that the method is effective.

키워드

과제정보

This work was supported by Natural Science Foundation of Anhui Province (2108085ME179) and National Natural Science Foundation of China (51607002).

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