Abstract
Interior rotor brushless DC motors (BLDCMs) are lightweight, compact, and efficient, offering high torque over a wide speed range, which makes them well suited for electric vehicle (EV) applications. However, cogging torque (CGT) remains a significant challenge, as it leads to noise, vibration, torque ripple, and jerky operation in EVs. In this work, an interior rotor BLDCM is designed with a focus on magnet orientation tuning combined with rotor skew angle adjustment, which is distinctly different from conventional magnet geometry modification or slot skewing approaches reported in prior literature. Twelve prototype design cases (PDCs) are developed by varying the permanent magnet orientation and skew angle using Motorsolve finiteelement simulations. The models are evaluated based on key performance parameters, including torque, CGT, back electromotive force, and efficiency. Response Surface Methodology (RSM) is employed to identify the optimal design that simultaneously maximizes torque and efficiency while minimizing CGT. The optimal design (PDC9), evaluated with respect to the baseline configuration PDC1, achieves a 43% improvement in torque, a near-zero CGT.The selected model is further prototyped and experimentally validated, confirming the simulation results. The proposed magnet orientation-based optimization strategy provides an effective and practical solution for developing high-performance BLDCMs for EV applications such as hybrid mopeds.
Data availability
All data analyzed during this study are included in this article.
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Acknowledgements
The authors acknowledge Kumaraguru College of Technology for providing permission to use the MotorSolve simulation software utilized in this study.
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Conceptualization: V.C. Data curation: V.C. Investigation: P.S.M., G.T. Methodology: V.C. Project administration: P.S.M., G.T. Supervision: P.S.M., Validation: P.S.M., J.H. Writing-original draft: V.C.
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Chandra, V., Manoharan, P.S., Thenmozhi, G. et al. Investigation of magnetic orientation effects on interior rotor BLDC motor performance for EVs: a response surface methodology approach. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37981-2
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DOI: https://doi.org/10.1038/s41598-026-37981-2
