Design and Optimization of a Pole Changing Flux Switching Permanent Magnet Motor

Abstract

A flux switching permanent magnet (FSPM) motor is designed and optimized in this paper to achieve high torque density and expanded speed regulation range from a design viewpoint of pole-changing (PC). Based on the field modulation theory, the PM field in the FSPM motor is modulated by the stator and rotor teeth, generating rich harmonics with different pole-pair numbers in the air-gap flux density. By adopting an appropriate slot pole combination, working harmonics with different slot pitch angles are obtained to establish a basic of the PC-FSPM motor. Then, different working harmonics can be used to achieve different energy conversions with different winding configurations, so the PC operation can be performed to realize the high torque and wide speed regulation range by switching the working modes. Based on the field modulation theory, the operation principle of conventional and PC-FSPM motors are analyzed and compared. Then, according to the design principle of PC-FSPM motor, a 24/22-pole PC-FSPM motor with E-core is designed and optimized by a multi-level optimization method. Finally, the electromagnetic performances are analyzed by finite element analysis and the test results of the prototype verified the feasibility of the motor.

Advancements in Flux Switching Machine Optimization: Applications and Future Prospects

“…Previous studies have predominantly focused on deterministic optimization (DO) strategies integrated with multiobjective, multilevel, or multimode optimization methodologies [28], [29], [30]. For instance, in [29], the FSM was optimized using the DO method to reduce the cogging torque by focusing on the pole embraces of the stator and rotor.…”

“…In addition, [33] introduced a multi-objective optimization method for FSMs that entailed two objectives, three constraints, and 16 design parameters in the optimization process. To mitigate computational costs and enhance optimization efficiency, [30] proposed a multilevel design optimization method in which optimization variables were divided into two levels, each optimized individually. A system-level optimization strategy using multi-objective and multilevel techniques was also pre-sented in [24].…”