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<p>This study aims to improve the precision of deep drawing by using electro-permanent magnet technology to provide blank holder force in a green and energy-efficient way. A finite element model was established to analyze the effects of punch feed rate, blank thickness, blank diameter, and magnetizing current on springback during the deep drawing process. Furthermore, a back-propagation neural network was developed based on simulation data to predict the required punch feed depth to achieve a target drawing height with high accuracy. The results show that the punch feed amount significantly influences both height and radial springback, while magnetizing current has the greatest effect on height springback and blank thickness has the greatest effect on radial springback. The experimental validation demonstrates that the predicted drawing height and outer diameter deviations can be controlled within 0.1&#xa0;mm, indicating that the proposed method can achieves precise and green deep drawing of flange components, which provides an effective solution for high-accuracy sheet metal forming.</p>

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Research on precision deep drawing technology of electro-permanent magnet

  • 期刊论文

  • 发表日期：

    2025年8月22日

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  • Jiacheng Zhang,
  • Siji Qin,
  • Sicheng He,
  • Zhicheng Liu,
  • Zhongrui Xu,
  • Yonggen Sun

摘要

This study aims to improve the precision of deep drawing by using electro-permanent magnet technology to provide blank holder force in a green and energy-efficient way. A finite element model was established to analyze the effects of punch feed rate, blank thickness, blank diameter, and magnetizing current on springback during the deep drawing process. Furthermore, a back-propagation neural network was developed based on simulation data to predict the required punch feed depth to achieve a target drawing height with high accuracy. The results show that the punch feed amount significantly influences both height and radial springback, while magnetizing current has the greatest effect on height springback and blank thickness has the greatest effect on radial springback. The experimental validation demonstrates that the predicted drawing height and outer diameter deviations can be controlled within 0.1 mm, indicating that the proposed method can achieves precise and green deep drawing of flange components, which provides an effective solution for high-accuracy sheet metal forming.