TY - GEN
T1 - Multiobjective Torque Ripple Minimization of a BLDC Motor Using NSGA-II
AU - Gadea-Vázquez, José D.
AU - Jiménez-Carballo, Carlos A.
N1 - Publisher Copyright:
© 2026 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2026
Y1 - 2026
N2 - Torque stability in ventricular assist devices (VADs) is critical to maintaining continuous blood flow and reducing adverse hemodynamic effects. This work presents a multi-objective geometric optimization of a brushless DC (BLDC) motor with an axial, shaftless design for VAD applications. A two-dimensional finite element model in COMSOL Multiphysics was coupled with MATLAB via LiveLink™ to evaluate candidate geometries. Five rotor and stator parameters were selected as design variables, and three objectives were defined: minimizing torque variation, enforcing a minimum average torque of 50 mN·m, and regulating the air-gap area. Optimization was performed using the NSGA-II algorithm with approximately 5000 evaluations. Results reduced torque ripple from 14.8% in the baseline design to below 5% within the Pareto set while satisfying the torque constraint. A trade-off between ripple reduction and average torque was observed. The proposed framework proves to be an effective tool for the electromagnetic optimization of BLDC motors in biomedical applications.
AB - Torque stability in ventricular assist devices (VADs) is critical to maintaining continuous blood flow and reducing adverse hemodynamic effects. This work presents a multi-objective geometric optimization of a brushless DC (BLDC) motor with an axial, shaftless design for VAD applications. A two-dimensional finite element model in COMSOL Multiphysics was coupled with MATLAB via LiveLink™ to evaluate candidate geometries. Five rotor and stator parameters were selected as design variables, and three objectives were defined: minimizing torque variation, enforcing a minimum average torque of 50 mN·m, and regulating the air-gap area. Optimization was performed using the NSGA-II algorithm with approximately 5000 evaluations. Results reduced torque ripple from 14.8% in the baseline design to below 5% within the Pareto set while satisfying the torque constraint. A trade-off between ripple reduction and average torque was observed. The proposed framework proves to be an effective tool for the electromagnetic optimization of BLDC motors in biomedical applications.
KW - BLDC motor
KW - NSGA-II
KW - evolutionary algorithms
KW - ripple torque
KW - ventricular assist device
UR - https://www.scopus.com/pages/publications/105048829223
U2 - 10.18687/LACCEI2026.1.1.2462
DO - 10.18687/LACCEI2026.1.1.2462
M3 - Contribución a la conferencia
AN - SCOPUS:105048829223
T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
BT - Proceedings of the 24th LACCEI International Multi-Conference for Engineering, Education and Technology - Engineering without Borders
A2 - Petrie, Maria M. Larrondo
A2 - Texier, Jose
A2 - Matta, Rodolfo Andres Rivas
PB - Latin American and Caribbean Consortium of Engineering Institutions
T2 - 24th LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2026
Y2 - 16 June 2026 through 18 June 2026
ER -