Optimization of in-wheel PM motor by fuzzy-based Taguchi method

In this paper, a novel systematic and efficient approach, using the fuzzy-based Taguchi method with multiple performance characteristics index (MPCI), is employed for obtaining the robust design of an in-wheel permanent-magnet (PM) motor with both lower torque ripple factor and higher efficiency. According to the geometric parameters of the PM motor, we select the controllable factors and their levels, such as the permanent magnet thickness in rotor, air-gap width, opening slot width and slot tooth width at stator. The proposed method first establishes the orthogonal array (OA) that is recommended by the Taguchi method. Then the multiple targets are coordinated by the fuzzy inference mechanism to obtain the better combination of the geometric parameters for achieving multiple quality targets. The finite element method (FEM) is used as the tool for analyzing the torque ripple and performance of PM motor. Results have shown that the proposed method can obtain the suitable motor´s geometric parameters for reducing the cogging torque and enhancing the operating efficiency.