Multi-Objective Optimization of a Split-Tooth Permanent Magnet Vernier Motor for Robotic Joint Applications

This article mainly proposes a multi-objective optimization framework for a split-tooth permanent magnet vernier motor (ST-PMVM) to improve output torque and overload capability in robotic joint applications. The overload performance of permanent magnet vernier motors (PMVMs) is first analyzed and compared with that of permanent magnet synchronous motors (PMSMs). The results reveal a design trade-off between high output torque and overload capability in the PMVM, especially for ST-PMVM. A multi-objective optimization framework is subsequently established for the ST-PMVM. The key design variables are identified through sensitivity analysis, followed by the construction of response surface models (RSM). The non-dominated sorting genetic algorithm II (NSGA-II) is then employed to obtain a set of Pareto-optimal solutions, from which the optimal values of the key design variables are identified. Simulations based on the finite element analysis (FEA) confirm that the optimal ST-PMVM achieves effective improvements in both output torque and overload capability.