Abstract
This work presents a novel abc-based model applicable to surface-mounted permanent magnet AC (SM-PMAC) machines with sinusoidal and non-sinusoidal back-electromotive force (back-emf). It is capable of predicting the electromagnetic performance metrics such as torque waveforms, machine inductances, flux linkages and back-emf. The closed form expressions of the model, which can be evaluated with a high computational efficiency, are derived from basic geometric and winding parameters. Validation of the model is carried out numerically and experimentally with a very good match in results. Finally, the computational efficiency of the model is highlighted by considering a multi-objective evolutionary optimization design of SM-PMAC machine with a relatively large number of design parameters, where results are presented and discussed.
Original language | British English |
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Pages (from-to) | 101844-101854 |
Number of pages | 11 |
Journal | IEEE Access |
Volume | 10 |
DOIs | |
State | Published - 2022 |
Keywords
- AC motors
- analytical model
- electric machines
- multiple reference frame transformation (MRFT)
- park transformation
- permanent magnet motors