Multi-Objective-Layered Optimization of a Magnetic Planetary Gear for Hybrid Powertrain

Abstract

In this article, an objective-layered optimization strategy is proposed and investigated for the magnetic planetary gear (MPG). The key and novelty are to comprehensively consider the sensitive relationships between objective and objective, as well as objective and parameter. From this, the sensitivity analysis method is utilized purposely. According to the result of sensitivity analysis, the optimization objectives are classified into two groups, thus the optimization process is divided into two layers. And, it is noted that the multi-objective genetic algorithm (MOGA) and double-side PM shaping method are respectively utilized in the two layers. In addition, the harmonic analysis of airgap flux density, cogging torque, and steady torque characteristics of MPG are also investigated in detail. Finally, a prototype machine and its hybrid system are built and tested. Both the theoretical analysis and experimental results verify the effectiveness of the proposed optimization strategy and studied MPG.