Air-Gap Permeance and Reluctance Network Models for Analyzing Vibrational Exciting Force of In-Wheel PMSM

• Published in: IEEE transactions on vehicular technology Vol. 71; no. 7; pp. 7122 - 7133
• Main Authors: Song, Zaixin, Liu, Chunhua, Chen, Yong, Huang, Rundong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Air gaps; Air-gap permeance; Atmospheric modeling; Design optimization; Finite element method; Flux density; Force; in-wheel motor; Magnetic flux; Mathematical analysis; Mathematical models; Model accuracy; Morphing; Motors; Performance prediction; Permanent magnets; radial force density; Reluctance; reluctance network; Rotors; Stator cores; Synchronous machines; traction; Vibration analysis; Vibrations
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2022.3167131

There is recognized interest in in-wheel motors for vehicle traction. Studies have gradually focused the design of in-wheel motors on electro-mechanical vibration, subject to the demand of driving comfort. It is crucial to model, analyze, and minimize the air-gap exciting force, the dominant source of vibration. In order to qualitatively and quantitatively study the air-gap vibrational exciting force and evaluate its characteristic for an in-wheel outer-runner permanent magnet synchronous machine (PMSM), this research proposes an air-gap permeance model (APM) and a unique adaptive reluctance network model (ARNM). In the process of motor design, APM is a quick means of determining dominant radial force density (RFD) harmonics and minimizing specific components that may produce considerable vibration. Morphing surface-mounted magnets and nonuniform air-gap length are guided by design optimization which complicates the analysis. Yet, proposed ARNM can account for this geometry variation and handle deformed gap geometry by using modified equation-based local permeance and residual flux. The speed and accuracy of proposed model are verified through the comparison of flux density and force mapping data between the calculation by proposed analytical model and the simulation by finite element tools. A 3-kW prototype is fabricated and tested to explore the effectiveness of ARNM-based performance prediction.