Combined Finite Element Simulation and Regression Modeling for Predicting Final Protrusion Length of Twisted Hairpin Legs in Stators

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This study presents an integrated finite element-based framework for analyzing the final protrusion length of enameled copper hairpins during stator manufacturing. Protrusion uniformity is essential for reliable laser welding, yet it is often degraded by layer-dependent deformation during expanding and twisting. To clarify the mechanisms governing protrusion variation, a bilayer material model for the copper–enamel system was developed and validated using tensile tests, indentation-based inverse characterization, and three-point bending experiments. Mechanically consistent boundary conditions for expanding and twisting were reconstructed from manufacturing observations and incorporated into FE simulations. The results indicate that twisting governs protrusion length through axial material redistribution, whereas expanding mainly serves as a feasibility-enabling step that establishes stable tool engagement. Based on these insights, a physics-guided regression formulation was introduced to relate key twisting kinematics to protrusion length. The proposed framework provides a mechanistic basis for understanding protrusion variability and supports further development toward rapid prediction and variability control.

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Solid State Phenomena (Volume 389)

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51-58

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April 2026

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[1] W. Maddumage, S. Ouenzerfi, S. Harmand, A. Cairns, A. Paykani, Thermal management of hairpin winding traction motors in electric vehicles: Parametric evaluation of impinging oil jet cooling using CFD simulations, Appl. Therm. Eng. 273 (2025) 126414.

DOI: 10.1016/j.applthermaleng.2025.126414

Google Scholar

[2] A. Dannier, F. Di Bruno, F. Fiume, E. Fedele, G. Brando, Hairpin Winding Technology for Electric Traction Motors: Design, Prototyping, and Connection Rules, Proc. 2022 International Conference on Electrical Machines (ICEM), IEEE, p.1170–1175.

DOI: 10.1109/icem51905.2022.9910851

Google Scholar

[3] H. Yu, L. Li, J. Wu, Laser welding method and quality analysis of hairpin windings in electric drive motors, Opt. Laser Technol. 174 (2024) 110452.

Google Scholar

[4] T. Will, A. Olowinsky, M. Gillner, Prediction of electrical resistance of laser‑welded copper pin‑pairs with surface topographical information from inline post‑process observation by optical coherence tomography, Int. J. Adv. Manuf. Technol. 127 (2023) 2947–2961.

DOI: 10.1007/s00170-022-10796-x

Google Scholar

[5] H. Choi, P. Fazily, J. Park, Y. Kim, J.H. Cho, J. Kim, J.W. Yoon, Artificial intelligence for springback compensation with electric vehicle motor component, Int. J. Mater. Form. 15 (3) (2022) 22.

DOI: 10.1007/s12289-022-01671-x

Google Scholar

[6] X. Long, X. Liu, H. Zhang, Indentation reverse algorithm of mechanical response for metallic coatings based on neural network and finite element method, Materials 16 (7) (2023) 2617.

Google Scholar

[7] A.R. Hosseinzadeh, F. Berto, G. Meneghetti, Determination of mechanical properties using sharp macro-indentation test and inverse analysis, Theor. Appl. Fract. Mech. 89 (2017) 1–10.

Google Scholar

[8] B.B. An, R.R. Wang, D.S. Zhang, Region-dependent micro damage of enamel under indentation, Acta Mech. Sin. 28 (6) (2012) 1651–1658.

DOI: 10.1007/s10409-012-0203-7

Google Scholar

[9] Z. Wang, K. Wang, W. Xu, X. Gong, F. Zhang, Mapping the mechanical gradient of human dentin–enamel junction at different intratooth locations, Dent. Mater. 34 (3) (2018) 376–388.

DOI: 10.1016/j.dental.2017.11.001

Google Scholar

[10] I.N. Chou, S.C. Wang, Finite element analysis and optimization of springback reduction in U-channel bending, J. Mater. Process. Technol. 89–90 (1999) 340–347.

Google Scholar

[11] N.A. Maske, J.K. Sawale, Taguchi approach for investigation of springback effect in aluminum sheet, Int. J. Mech. Eng. Rob. Res. 2 (3) (2013) 322–329.

Google Scholar

[12] D.T. Nguyen, J.E. Park, D.H. Kim, Optimization of influential process parameters on the deep drawing of aluminium 6061 sheet using Taguchi method and finite element analysis, in: Proc. KSME Spring Conf., 2009, p.1045–1050.

DOI: 10.1139/tcsme-2015-0047

Google Scholar

[13] C. Depoorter, K. Faes, J. Penning, Mechanical heterogeneity in drawn copper wires due to microstructural gradients, Mater. Sci. Eng. A 666 (2016) 229–238.

Google Scholar

[14] S.H. Choi, Y.S. Kim, J.W. Lee, Effect of drawing sequences on mechanical inconsistency in copper conductors, J. Mater. Process. Technol. 265 (2019) 1–10.

Google Scholar

[15] N.V. Nguyen, J.J. Kim, S.E. Kim, Methodology to extract constitutive equation at a strain rate level from indentation curves, Int. J. Mech. Sci. 152 (2019) 363–377.

DOI: 10.1016/j.ijmecsci.2018.12.023

Google Scholar