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<p>The laminated nanocrystalline-ferrite core benefits from the high saturation capability of nanocrystalline material and the low-loss behavior of ferrite, enabling improved power density under acceptable loss conditions. To realize these gains, appropriate parameter design of the laminated core is required. However, the original model fails to account for material nonlinearity and the nonuniform flux density at the corners, leading to bias in flux prediction and inaccuracies in core loss estimation. Therefore, accurate modeling is essential for laminated core design. An improved equivalent magnetic circuit model was developed, incorporating nonlinear magnetization and corner flux distribution, and it was validated against finite-element analysis (FEA), with core loss prediction errors below 8%. The optimal layer thickness ratio was determined using the non-dominated sorting genetic algorithm-II (NSGA-II) and entropy weight-TOPSIS. A prototype transformer was built, achieving 97% efficiency. Compared with the ferrite core, the efficiency and power density increased by 2.7% and 10.55%, with additional gains of 1.2% and 5.4% over the laminated design optimized using the original model.</p>

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Optimization of nanocrystalline ferrite-laminated core based on nonlinear modeling with refined corner representation

  • 期刊论文

  • 发表日期：

    2026年5月22日

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  • Nenghong Xia,
  • Chaoyang Gao,
  • Kai Li,
  • Hetong Wang

摘要

The laminated nanocrystalline-ferrite core benefits from the high saturation capability of nanocrystalline material and the low-loss behavior of ferrite, enabling improved power density under acceptable loss conditions. To realize these gains, appropriate parameter design of the laminated core is required. However, the original model fails to account for material nonlinearity and the nonuniform flux density at the corners, leading to bias in flux prediction and inaccuracies in core loss estimation. Therefore, accurate modeling is essential for laminated core design. An improved equivalent magnetic circuit model was developed, incorporating nonlinear magnetization and corner flux distribution, and it was validated against finite-element analysis (FEA), with core loss prediction errors below 8%. The optimal layer thickness ratio was determined using the non-dominated sorting genetic algorithm-II (NSGA-II) and entropy weight-TOPSIS. A prototype transformer was built, achieving 97% efficiency. Compared with the ferrite core, the efficiency and power density increased by 2.7% and 10.55%, with additional gains of 1.2% and 5.4% over the laminated design optimized using the original model.