[논문]Optimal Design of Double-Pole Magnetization BLDC Motor and Comparison with Single-Pole Magnetization BLDC Motor in Terms of Electromagnetic Performance

Shin, Hyo-Seob; Jang, Gang-Hyeon; Jung, Kyung-Hun; Cho, Seong-Kook; Choi, Jang-Young; Shin, Hyeon-Jae

doi:10.3390/machines9010018

[해외논문] Optimal Design of Double-Pole Magnetization BLDC Motor and Comparison with Single-Pole Magnetization BLDC Motor in Terms of Electromagnetic Performance 원문보기

Machines, v.9 no.1, 2021년, pp.18 -

Shin, Hyo-Seob (Department of Electrical Engineering, Chungnam National University, Daejeon 34134, Korea) , Jang, Gang-Hyeon (Department of Electrical Engineering, Chungnam National University, Daejeon 34134, Korea) , Jung, Kyung-Hun (Research and Development Center, Hanon Systems, Daejeon 34325, Korea) , Cho, Seong-Kook (Research and Development Center, Hanon Systems, Daejeon 34325, Korea) , Choi, Jang-Young (Department of Electrical Engineering, Chungnam National University, Daejeon 34134, Korea) , Shin, Hyeon-Jae (Research and Development Center, Hanon Systems, Daejeon 34325, Korea)

Abstract ▼ AI-Helper

This study presents an optimal double-pole magnetization brushless DC (BLDC) motor design, compared to a single-pole magnetization BLDC motor in terms of electromagnetic performance. Initially, a double-pole model is selected based on the permanent magnet (PM) of the single-pole model. The pole separation space, which is generated in the magnetization process of the double-pole PM, is selected based on the pole space of the single-pole model. Moreover, the PM offset is selected considering the PM volume of the single-pole model. Further, an optimal model is selected using the multiple response optimal method, which is a type of response surface methodology (RSM). The objective of the optimal design is to maintain the back EMF and decrease the cogging torque; the design variables include the pole separation space and PM offset. The experimental points of the initial model are designed using the central composite method (CCD). Finally, the optimization is verified by comparing the experimental and analysis results of the single-pole model with the analysis results of the optimal model.

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