Global Optimization of a Complementary and Modular Linear Flux-Switching Permanent Magnet Motor Applied for Urban Rail Transit to Reduce Normal Force

Linear flux-switching permanent magnet motors (LFSPM) have outstanding advantages in the urban rail transit, such as higher power factor and higher efficiency compared with linear induction motors (LIM), as well as lower construction cost compared with traditional permanent magnet linear motors (PMLM), since the permanent magnets and armature windings are both located in the short primary mover. Considering that when the LFSPM motor is applied in the rail transit, excessive unilateral normal force will lead to extra energy loss as well as threaten the safety, global optimization with multiple geometry parameters of a complementary and modular LFSPM (CMLFSPM) motor is achieved with the aid of non-dominated sorting genetic algorithm (NSGA-II) in this paper. Firstly, key geometry parameters are selected through sensitivity analysis. Then, the NSGA-II and finite element analysis (FEA) are applied in global optimization. Finally, this paper demonstrates that after global optimization, the normal force of the CMLFSPM motor can be greatly reduced under the premise of enough traction force.