IMPROVED MODEL PREDICTIE TORQUE CONTROL OF SYNCHRONOUS RELUCTANCE MOTOR

Zhao Zhengyang; Du Qinjun; Ling Hui; Yang Shuxin; Feng Han; Li Cunhe

doi:10.19912/j.0254-0096.tynxb.2022-0233

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (6) : 469-476. DOI: 10.19912/j.0254-0096.tynxb.2022-0233

IMPROVED MODEL PREDICTIE TORQUE CONTROL OF SYNCHRONOUS RELUCTANCE MOTOR

Zhao Zhengyang, Du Qinjun, Ling Hui, Yang Shuxin, Feng Han, Li Cunhe

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Abstract

Aiming at the problem of large torque ripple and large influence of inductance parameters in synchronous reluctance motor model predictive torque control, an improved model predictive torque control method for synchronous reluctance motor is proposed. The recursive least square method with forgetting factor is used to identify the inductance parameters. The identified inductance parameters are used in the model predictive torque control, which improves the accuracy of the mathematical model in the model predictive control and reduces the influence of the change of inductance parameters on the performance of the model predictive torque control. Discrete space vector modulation technology is introduced, which improves the steady-state performance of the system by synthesizing a large number of virtual vectors. At the same time, a simplified method for voltage vector selection is proposed to avoid calculating all voltage vectors and reduce the amount of calculation. The simulation results show that this method has small torque and flux ripple and good dynamic and steady-state performance.

Key words

wind turbines / model predictive control / parameter identification / torque control / synchronous reluctance motor / discrete space vector modulation

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Zhao Zhengyang, Du Qinjun, Ling Hui, Yang Shuxin, Feng Han, Li Cunhe. IMPROVED MODEL PREDICTIE TORQUE CONTROL OF SYNCHRONOUS RELUCTANCE MOTOR[J]. Acta Energiae Solaris Sinica. 2023, 44(6): 469-476 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0233

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