2026-07-29
Software-Validated Computational Framework for Axial and Radial Magnetic Force Prediction in Misaligned Air-Core Coil Systems with Surrogate Modeling
By
Progress In Electromagnetics Research B, Vol. 118, 56-71, 2026
Abstract
Accurate prediction of magnetic forces in air-core coil systems is essential for the design and optimization. Accurate magnetic-force prediction in air-core coil systems is essential for electromagnetic actuators, wireless power transfer, inductive coupling, magnetic calibration, and coil-based positioning systems. This paper presents a software-validated computational framework for predicting axial and radial magnetic forces in practical air-core coil systems under aligned and misaligned conditions. The framework extends ideal coaxial coil-force analysis by including lateral offset, angular tilt, finite coil dimensions, discrete winding geometry, helical winding pitch, finite conductor diameter, and nonuniform conductor placement. Three complementary physics-based methods are implemented and compared: a semi-analytical elliptic-integral method for rapid coaxial and near-coaxial evaluation, a direct numerical-integration method based on the Lorentz-force interaction integral, and a filament-based discrete-winding method for practical conductor geometry. Independent Ansys Maxwell simulations are used as the finite-element software-validation reference under identical geometric and electrical conditions. This work is limited to software-based validation; physical experimental validation using real coil pairs is identified as future work. The validation results show strong agreement among the proposed methods and Ansys Maxwell simulations. The final software mesh-independence change is 0.15%, the boundary-domain sensitivity is 0.12%, and the maximum relative half-spread among the physics-based methods is 0.55%. The maximum axial-force deviation in the coaxial separation sweep is 0.62%, and the radial-force sign-symmetry error remains below 0.23%. Including practical winding details reduces the model-to-software vector error from 2.87% for the continuous-current approximation to 0.10% for the full practical winding model. A feedforward neural-network surrogate model trained using 12,000 validated samples is also introduced for rapid interpolation within the sampled design domain. The surrogate achieves R2=0.996-0.998, mean relative error below 1.20%, and maximum relative error of 5.00% on unseen test data. The proposed framework provides an accurate, efficient, and physically interpretable tool for axial and radial force prediction in practical misaligned air-core coil systems.
Citation
Ali Jebelli, Nafiseh Lotfi, Arezoo Mahabadi, and Mustapha C. E. Yagoub, "Software-Validated Computational Framework for Axial and Radial Magnetic Force Prediction in Misaligned Air-Core Coil Systems with Surrogate Modeling," Progress In Electromagnetics Research B, Vol. 118, 56-71, 2026.
doi:10.2528/PIERB26061101
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