TY - GEN
T1 - Research On Multi-Objective Optimization Of Coreless Permanent Magnet Synchronous Planar Motor
AU - Cheng, Han
AU - Wang, Mingyi
AU - Li, Junchi
AU - Zhang, Lu
AU - Li, Liyi
N1 - Publisher Copyright:
© 2025 Korean Institute of Electrical Engineers Electrical Machinery and Energy Conversion Systems Society.
PY - 2025
Y1 - 2025
N2 - To address the thrust ripple issue in slotless permanent magnet synchronous planar motors (SPMPMs) used in flexible intelligent transport systems, this study proposes a multi-objective optimization framework integrating a Kriging surrogate model with an improved particle swarm optimization (MOPSO) algorithm. An electromagnetic coupling model is built, and sensitivity analysis identifies key design variables influencing thrust ripple. A high-precision Kriging model is constructed using Latin hypercube sampling (LHS) to predict motor performance. The MOPSO algorithm is then applied under magnetic-force coupling constraints for collaborative parameter optimization. Finite element simulation results confirm the method's effectiveness, showing that thrust ripple is significantly suppressed while rated thrust is maintained. The obtained Pareto-optimal solutions provide a scientific basis for multidimensional design trade-offs in SPMPMs, improving system reliability and operational stability.
AB - To address the thrust ripple issue in slotless permanent magnet synchronous planar motors (SPMPMs) used in flexible intelligent transport systems, this study proposes a multi-objective optimization framework integrating a Kriging surrogate model with an improved particle swarm optimization (MOPSO) algorithm. An electromagnetic coupling model is built, and sensitivity analysis identifies key design variables influencing thrust ripple. A high-precision Kriging model is constructed using Latin hypercube sampling (LHS) to predict motor performance. The MOPSO algorithm is then applied under magnetic-force coupling constraints for collaborative parameter optimization. Finite element simulation results confirm the method's effectiveness, showing that thrust ripple is significantly suppressed while rated thrust is maintained. The obtained Pareto-optimal solutions provide a scientific basis for multidimensional design trade-offs in SPMPMs, improving system reliability and operational stability.
KW - Kriging Model
KW - Multi-objective Optimization
KW - SPMPPM
KW - Thrust Characteristics
UR - https://www.scopus.com/pages/publications/105032881548
U2 - 10.23919/ICEMS66262.2025.11317645
DO - 10.23919/ICEMS66262.2025.11317645
M3 - 会议稿件
AN - SCOPUS:105032881548
T3 - ICEMS 2025 - 28th International Conference on Electrical Machines and Systems
SP - 197
EP - 201
BT - ICEMS 2025 - 28th International Conference on Electrical Machines and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th International Conference on Electrical Machines and Systems, ICEMS 2025
Y2 - 16 November 2025 through 19 November 2025
ER -