Abstract

In this paper, the effects of magnetization patterns on the performance of Hybrid Electrical Vehicle (HEV) are investigated. HEVs have three magnetic field sources: armature winding, permanent magnets, and field winding. To initiate the investigation, the magnetic field distributions produced by these three sources are obtained. By using the magnetic field distributions, the machine is analyzed under no-load and on-load conditions, and the operational indices, such as self and mutual inductance, cogging-, reluctance- and instantaneous torque, and unbalance magnetic force (UMF) in x- and y direction are calculated. Various magnetization patterns are considered to investigate their influences on the performance of the machine. This step was done with Maxwell software. Furthermore, instantaneous torque and magnitude of UMF are expressed in term of pole arc to pole pitch ratio by using artificial intelligence. The optimal of the pole arc to pole pitch ratio to maximize the average of instantaneous torque and minimize the magnitude of UMF by some multi-objective algorithms is also computed. The modeling and optimization are performed by Matlab Software.

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