Electromagnetic Vibration Analysis and Slot–Pole Structural Optimization for a Novel Integrated Permanent Magnet In-Wheel Motor

Qiang Wang, Pingping Zhao, Xianbin Du, Fen Lin and Xu Li
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Qiang Wang: School of Transportation, Shandong University of Science and Technology, Qingdao 266590, China
Pingping Zhao: College of Chemical and Biological Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Xianbin Du: School of Transportation, Shandong University of Science and Technology, Qingdao 266590, China
Fen Lin: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Xu Li: School of Transportation, Shandong University of Science and Technology, Qingdao 266590, China

Energies, 2020, vol. 13, issue 13, 1-15

Abstract: This paper presents a novel integrated permanent magnet (PM) in-wheel motor (IWM) driving system for electric vehicles (EVs), in order to overcome the disadvantages of electromagnetic vibration and cogging torque in the topology scheme, on the basis of maintaining high output torque. Firstly, the transient magnetic field of the integrated PM motor is analyzed using the improved analytical subdomain model and finite element (FE) model. The harmonic component of magnetic force density (MFD) is obtained with no-load condition. Furthermore, the vertical dynamic model for the dynamic vibration absorber is established to investigate the influence of the magnetic force harmonic on the vibration response of the stator and rotor. On this basis, the multi-objective optimization design of the pole–slot structure parameters is carried out by using the adaptive weighted particle swarm optimization (AWPSO) algorithm. Finally, the optimization results are compared and verified by FE analysis. The investigation shows that the unbalanced magnetic force and cogging torque is significantly reduced by the adjustment of the pole-arc coefficient, PM thickness, stator slot width and slot opening width.

Keywords: in-wheel-motor; magnetic field distribution; electromagnetic vibration; cogging torque; adaptive weighted particle swarm optimization; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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