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Analytical Modeling and Optimization of Partitioned Permanent Magnet Consequent Pole Switched Flux Machine With Flux Barrier
oleh: Wasiq Ullah, Faisal Khan, Shahid Hussain, Muhammad Yousaf, Siddique Akbar
| Format: | Article |
|---|---|
| Diterbitkan: | IEEE 2022-01-01 |
Deskripsi
Switched Flux Permanent Magnet Machine (SFPMM) encompass unique features of conventional direct current machine, permanent magnet (PM) synchronous machine and switch reluctance machine therefore, applicable for high-speed applications. However, conventional SFPMM exhibits demerits of high PM volume <inline-formula> <tex-math notation="LaTeX">$(V_{PM})$ </tex-math></inline-formula>, high torque ripples <inline-formula> <tex-math notation="LaTeX">$(T_{rip})$ </tex-math></inline-formula>, higher cogging torque <inline-formula> <tex-math notation="LaTeX">$(T_{cog})$ </tex-math></inline-formula>, lower torque density <inline-formula> <tex-math notation="LaTeX">$(T_{den})$ </tex-math></inline-formula> and significant stator flux leakage. In this paper, a new topology of consequent pole (CP) SFPMM (CPSFPMM) is proposed having partitioned PM that improved flux modulation phenomena utilizing flux barriers. Moreover, due to non-linear behaviour of PM and complex stator structure alternate analytical sub-domain model is utilizes for initial design. However, initial design offers lower open-circuit phase flux linkage <inline-formula> <tex-math notation="LaTeX">$(\Phi)$ </tex-math></inline-formula>, average mechanical torque <inline-formula> <tex-math notation="LaTeX">$(T_{avg})$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$T_{den}$ </tex-math></inline-formula>. Aforementioned electromagnetic key performance indicator with <inline-formula> <tex-math notation="LaTeX">$T_{cog}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$T_{rip}$ </tex-math></inline-formula>, total harmonics distortion in <inline-formula> <tex-math notation="LaTeX">$\Phi $ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\Phi _{THD}$ </tex-math></inline-formula>), average power <inline-formula> <tex-math notation="LaTeX">$(P_{avg})$ </tex-math></inline-formula> and power density <inline-formula> <tex-math notation="LaTeX">$(P_{den})$ </tex-math></inline-formula> are refined utilizing Geometric-Based Deterministic Optimization (GBDO). Analysis reveals that proposed new topology of CPSFPMM with flux barriers reduces <inline-formula> <tex-math notation="LaTeX">$T_{cog}$ </tex-math></inline-formula> by 34.90%, <inline-formula> <tex-math notation="LaTeX">$T_{rip}$ </tex-math></inline-formula> by 20.27%, <inline-formula> <tex-math notation="LaTeX">$\Phi _{THD}$ </tex-math></inline-formula> by 28.08% whereas it enhanced <inline-formula> <tex-math notation="LaTeX">$P_{avg}$ </tex-math></inline-formula> by 17.79%, <inline-formula> <tex-math notation="LaTeX">$T_{den}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$P_{den}$ </tex-math></inline-formula> by 34.38%.