Research Article

Design optimization and experimental assessment of DC motor for robotic actuation using finite element analysis

¹ College of Mechanical Engineering, Baoji University of Arts and Sciences, Baoji 721016, PR China
² Shaanxi Key Laboratory of Advanced Manufacturing and Evaluation of Robot Key Components, Baoji 721016, PR China

^* Corresponding author: gcx_agan@163.com

Received: 23 March 2025
Accepted: 27 October 2025

Abstract

Robotic actuators need to be light weight, compact, and efficient for meeting the requirement of size and controllability. It's capability of achieving high power density is often restricted by limitations in torque output and efficiency. This paper presents a novel multi-module spliced direct-drive outer rotor BLDC motor tailored for robotic systems. This study focuses on a unique multi-module splicing structure that simplifies manufacturing and assembly while significantly enhancing torque density through improved magnetic symmetry and inherent structural modularity. Critical electromagnetic parameters—pole-arc coefficient, air gap, and permanent magnet thickness—are systematically refined using combined theoretical modeling and high-fidelity simulations in ANSYS Maxwell. A quasi-Newton multi-objective optimization algorithm accelerates convergence toward globally optimal configurations, effectively balancing multiple design objectives. Optimized results confirm a peak efficiency of 95.06%, core and copper losses reduced to 22.5 W and 12.8 W respectively, a 38.89% reduction in cogging torque, an 8.33% decrease in air-gap flux density, and torque ripple maintained at 24% in simulations, primarily attributed to the 12th harmonic. Prototype testing validate these improvements, with actual torque ripple slightly higher than the simulated value at 26%, while demonstrating agreement with simulation data in efficiency and losses. By integrating structural design, computational optimization, and experimental verification, this work delivers a robust solution to the persistent high torque density versus manufacturing feasibility trade-off, enabling more efficient, reliable, and scalable robotic actuations.