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Cogging torque causes major operational setbacks for Permanent Magnet (PM) machine operation, particularly in applications where a quiet performance is desired. This paper presents a heuristic optimization framework to optimize the cogging torque in Surface Mounted Permanent Magnet (SPM) machines consisting of a hybrid magnetic structure (i.e., rare-earth and ferrite magnets). To avoid excessive computational time and volume associated with Finite Element (FE)-based optimization solutions, analytical approach is paired up with the optimization algorithm to determine the optimal design while FE is utilized for verification and validation purposes. First, analytical expressions are established for individual objective functions (i.e., airgap PM flux distribution, and cogging torque), and their corresponding spatial harmonics are identified using the air-gap field modulation theory. Next, the presented analytical model is utilized to optimize the system (i.e., minimize the cogging torque) to the desired target level via two different solutions (i.e., Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)), and their respective performance are compared. To determine the efficacy of the presented solutions, the optimal hybrid machine response is compared against the baseline structure.

Analytical Investigation and Heuristic Optimization of Surface Mounted Permanent Magnet Machines With Hybrid Magnetic Structure