An Efficient Rotor-Skewing Model for Mitigating Electromagnetic Vibration and Noise in Fractional-Slot Concentrated-Winding Permanent-Magnet Machines

Rotor-skewing is a widely used approach to mitigate electromagnetic (EM) vibration and noise in permanent-magnet (PM) brushless machines, especially for electric vehicles. Current literature primarily depends on EM force superposition (FSUP) across all axial segments to evaluate different rotor-skewing approaches. While FSUP is adequate for addressing single-order EM noise by identifying the skewing approach that minimizes EM forces at the same frequency, it falls short in fractional-slot concentrated-winding PM machines where multiorder EM noises are pronounced. Since multi-order noises cannot be equated directly to force mitigation, optimization of the skewing approach often relies on coupled-field finite-element analysis (CF-FEA) to predict overall noise levels. Considering the low accuracy of the FSUP method and the slow computation speed of the CF-FEA, this article aims to propose an efficient model that offers both speed and precision. For the first time, a segmented model is proposed to address the impacts of axially uneven distribution of mode shapes, improving the accuracy of rotor-skewing assessments. The design of rotor-skewing is discussed and a high-efficiency optimization framework is established. A 12-slot/10-pole spoke-type PM machine is taken as the case study, where two main noises are mitigated at the same time. The effectiveness of the proposed model is validated by experimental results.