Interior Permanent Magnet Rotor Notch Optimization for High-Speed Torque Enhancement in Brushless DC Motors

The square-wave driven Brushless DC (BLDC) motor with an Interior Permanent Magnet (IPM) rotor exhibits degraded average torque performance in high-speed regions because of the motor's high winding inductance. To mitigate this issue, an IPM rotor geometry featuring trapezoidal-shaped notches on its quadrature axis is proposed to reduce the inductance. The study first investigates the conventional IPM-BLDC motor, and its performance is compared with the commercially available Surface Permanent Magnet (SPM) BLDC motor, which serves as a benchmark. Then, the proposed motor is introduced, demonstrating enhanced average torque relative to the conventional design. Subsequently, the proposed rotor geometry is optimized using the NSGA-II multi-objective optimization algorithm applied on a Support Vector Regression (SVR) based surrogate model. A Finite Element Analysis (FEA) is performed to evaluate and compare the electromagnetic performance of all the motors under open-circuit and on-load operating conditions. Thereafter, the thermal, demagnetization, and rotor stress analysis is performed to assess the reliability of the proposed motor. The cost analysis is also presented to highlight its commercial viability. Finally, a 1 kW prototype of the proposed IPM-BLDC motor has been developed. Experimental results demonstrate that the proposed motor achieves equivalent performance as the benchmark motor, achieving the rated efficiency of 92.6% at 2767 RPM and 1 kW power.

Authors

Publication Details

Journal
IEEE Transactions on Energy Conversion
Published
2025-01-01
DOI
https://doi.org/10.1109/tec.2025.3605076
Citations
1
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
0.73
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article

Interior Permanent Magnet Rotor Notch Optimization for High-Speed Torque Enhancement in Brushless DC Motors

Durgesh Kumar Banchhor, Amit Kumar Jain, Aditya Sharma
1 citations
IEEE Transactions on Energy Conversion
Electric Motor Design and Analysis
0.73
article

Interior Permanent Magnet Rotor Notch Optimization for High-Speed Torque Enhancement in Brushless DC Motors

Durgesh Kumar Banchhor, Amit Kumar Jain, Aditya Sharma
article en
1 citations

Abstract

The square-wave driven Brushless DC (BLDC) motor with an Interior Permanent Magnet (IPM) rotor exhibits degraded average torque performance in high-speed regions because of the motor's high winding inductance. To mitigate this issue, an IPM rotor geometry featuring trapezoidal-shaped notches on its quadrature axis is proposed to reduce the inductance. The study first investigates the conventional IPM-BLDC motor, and its performance is compared with the commercially available Surface Permanent Magnet (SPM) BLDC motor, which serves as a benchmark. Then, the proposed motor is introduced, demonstrating enhanced average torque relative to the conventional design. Subsequently, the proposed rotor geometry is optimized using the NSGA-II multi-objective optimization algorithm applied on a Support Vector Regression (SVR) based surrogate model. A Finite Element Analysis (FEA) is performed to evaluate and compare the electromagnetic performance of all the motors under open-circuit and on-load operating conditions. Thereafter, the thermal, demagnetization, and rotor stress analysis is performed to assess the reliability of the proposed motor. The cost analysis is also presented to highlight its commercial viability. Finally, a 1 kW prototype of the proposed IPM-BLDC motor has been developed. Experimental results demonstrate that the proposed motor achieves equivalent performance as the benchmark motor, achieving the rated efficiency of 92.6% at 2767 RPM and 1 kW power.

IEEE Transactions on Energy Conversion
Openalex Percentile: Top 24%
Electric Motor Design and Analysis
0.73
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Interior Permanent Magnet Rotor Notch Optimization for High-Speed Torque Enhancement in Brushless DC Motors — Durgesh Kumar Banchhor, Amit Kumar Jain, et al. · IEEE Transactions on Energy Conversion (2025) | TGRS Research Map | TGRS