Teeth Arrangement and Pole–Slot Combination Design for PMLSM Detent Force Reduction

Chung, Shi-Uk; Lee, Ji-Young

doi:10.3390/en14238141

Cited by 5 publications

(1 citation statement)

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“…The number of electrical slots in the optimal design model was increased by incorporating notches in the stator teeth of the PMSM. The peak-to-peak value of cogging torque is inversely proportional to the least common multiple of poles and slots numbers [31]; this contributed toward a reduction in the cogging torque, and consequently, the torque ripple. The FEA results confirmed that the cogging torque of the optimal model was reduced by 33.3% compared with that of the initial model, as shown in Figure 8.…”

Section: Considerationmentioning

confidence: 99%

Optimization of a Permanent Magnet Synchronous Motor for e-Mobility Using Metamodels

Kim

You

2022

Applied Sciences

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Permanent magnet synchronous motors (PMSMs) with rectangular coils in hairpin windings exhibit improved fill factor and reduced end turn of the coils, which in turn improve the efficiency and power density of PMSMs, making them ideal for e-mobility applications. Herein, the shape of a PMSM was optimized for torque ripple reduction using metamodels to improve the noise and vibrational performance of the motor. The objective function of the optimal design aimed to minimize the torque ripple, and the average torque and efficiency were set as constraints. The notch width and depth and barrier length were selected as the design variables to satisfy the objective function and constraints. Using the optimal Latin hypercube design technique, 27 experimental points were selected, and a finite element analysis (FEA) was performed for each point. Furthermore, a function approximation was performed using six metamodels, and the best metamodel was selected using the root mean square error test. Moreover, the optimization was performed by combining the best metamodels for each variable with a sequential two-point diagonal quadratic approximation optimization algorithm. The torque ripple was improved by approximately 1.63% compared with the initial model, whereas the constraint values remained constant. Finally, an FEA was performed on the optimal point, and the FEA results matched with those of the optimal method.

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Section: Considerationmentioning

confidence: 99%