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<p>The electric machines in vehicles are major coupling paths for electromagnetic emission. Accurate modeling is critical for ensuring electromagnetic compatibility (EMC), but is computationally expensive due to complex geometries. This paper proposes a&#xa0;multi-fidelity (MF) surrogate modeling approach that combines low-fidelity (LF) equivalent-circuit models with high-fidelity (HF) 3D electromagnetic simulations. A&#xa0;novel frequency-adaptive Kriging method is introduced, using frequency-wise correlation to selectively merge LF and HF data. This method is demonstrated on a&#xa0;simplified electric machine model to illustrate and validate the effectiveness of the proposed MF strategy. Compared to conventional MF approaches, the proposed method improves accuracy near resonances while reducing reliance on costly HF simulations, enabling scalable and efficient EMC analysis and optimization of electric machines and surrounding systems.</p>

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Multi-fidelity surrogate modeling of electric machines

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月3日

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  • Bibhu Prasad Nayak,
  • Stefan Sallinger,
  • Jan Hansen

摘要

The electric machines in vehicles are major coupling paths for electromagnetic emission. Accurate modeling is critical for ensuring electromagnetic compatibility (EMC), but is computationally expensive due to complex geometries. This paper proposes a multi-fidelity (MF) surrogate modeling approach that combines low-fidelity (LF) equivalent-circuit models with high-fidelity (HF) 3D electromagnetic simulations. A novel frequency-adaptive Kriging method is introduced, using frequency-wise correlation to selectively merge LF and HF data. This method is demonstrated on a simplified electric machine model to illustrate and validate the effectiveness of the proposed MF strategy. Compared to conventional MF approaches, the proposed method improves accuracy near resonances while reducing reliance on costly HF simulations, enabling scalable and efficient EMC analysis and optimization of electric machines and surrounding systems.