DOI: 10.3390/en19163845 ISSN: 1996-1073

Performance Analysis and Experimental Validation of Outer-Rotor Permanent Magnet Synchronous Motors for Drone Propulsion Systems

Min-Mo Koo, Hyeon-Jae Shin

As the drone industry expands rapidly, the demand for high-performance propulsion systems with high power density, superior energy efficiency, and lightweight characteristics has grown significantly. Outer-rotor permanent magnet synchronous motors (OR-PMSMs) are particularly well-suited for drone propulsion, due to their superior torque density and efficient thermal management, compared to inner-rotor structures. However, achieving accurate performance prediction during the initial design phase remains challenging due to complex electromagnetic phenomena. This paper proposes an analytical methodology using the subdomain method to evaluate the electromagnetic performance of OR-PMSMs, specifically accounting for slotting effects caused by stator geometry. Rather than focusing on complex optimization algorithms, this study prioritizes comprehensive performance evaluation and experimental validation. Key electromagnetic parameters and circuit constants—including air-gap flux density, back-EMF, winding resistance, inductance, and electromagnetic torque—are calculated efficiently using the proposed analytical model. To complement the limitations of analytical formulation regarding core saturation and flux leakage, the finite element method (FEM) is conducted for comparative evaluation. Furthermore, a physical prototype of the OR-PMSMs for drone propulsion was fabricated, and experimental tests were performed to validate the analytical and numerical results. The analytical predictions demonstrate strong agreement with both the FEM simulations and experimental measurements, confirming the accuracy and reliability of the proposed framework. Consequently, this study addresses the inherent constraints of conventional analytical methods and provides a computationally efficient, yet precise, evaluation procedure, serving as valuable baseline data for the design and development of high-efficiency, lightweight drone propulsion motors.

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