Feedback-based mitigation of torque harmonics in interior permanent magnet synchronous machines

Vaks, Nir; Pekarek, Steve; Horvath, D. C.

doi:10.1109/iemdc.2013.6556151

Cited by 2 publications

(1 citation statement)

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“…Among them, a common method is to obtain optimal current value for generating constant torque on the basis of the relationship between current and torque of the motor, and then accordingly suppress torque or speed ripple with proposed torque or speed control algorithm. In [8], the quantity relationship between each harmonic of torque and the relevant harmonic of current is analyzed, and then the optimal current is calculated according to the current fedback to the controller. In [9], the current and back EMF are modeled in multidimensional space, and the current value for generating constant torque with minimized ohmic losses are derived by utilizing artificial neural networks.…”

Section: Introductionmentioning

confidence: 99%

Torque Ripple Minimization of PMSM Using Parameter Optimization Based Iterative Learning Control

Xia¹,

Deng²,

Shi³

et al. 2016

Journal of Electrical Engineering and Technology

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-In this paper, a parameter optimization based iterative learning control strategy is presented for permanent magnet synchronous motor control. This paper analyzes the mechanism of iterative learning control suppressing PMSM torque ripple and discusses the impact of controller parameters on steady-state and dynamic performance of the system. Based on the analysis, an optimization problem is constructed, and the expression of the optimal controller parameter is obtained to adjust the controller parameter online. Experimental research is carried out on a 5.2kW PMSM. The results show that the parameter optimization based iterative learning control proposed in this paper achieves lower torque ripple during steady-state operation and short regulating time of dynamic response, thus satisfying the demands for both steady state and dynamic performance of the speed regulating system.

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Section: Introductionmentioning

confidence: 99%