Torque Compensation Method of Switched Reluctance Motor Adopting MPC Based on TSF-Ditc

Yang, Yang; Xu, Aidong; Li, Bing; Sun, Jian; Li, Kuo

doi:10.2528/pierm22040803

Cited by 1 publication

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…J k max J p max Proposed TSF 85% 38.8% OCTSF [20] 66.67% 6.19% TSF-MPC [19] 54% 7.14% Modified TSF [21] 67.21% 7.49%…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Control Method of Switched Reluctance Motor Based on Non-unity TSF and Adaptive Overlapping Angle

Huang¹,

Cao²,

Sun³

et al. 2023

PIER C

View full text Add to dashboard Cite

Aiming at the problems of conventional torque sharing function (TSF) control method, such as large torque ripple, high peak current, and high copper loss, a non-unity TSF control method with adaptive overlapping angle is proposed. Firstly, on the basis of explaining the conventional TSF control logic, according to the characteristics of inductance, the conduction region is redivided, and the two-phase exchange region is subdivided into region 1 and region 2, which together with the single-phase conduction region form three regions in the winding conduction region. A non-unity TSF is designed in each region, which conforms to the torque variation trend. Then, an adaptive overlapping angle algorithm is designed, which can automatically adjust the overlapping angle under different speeds and load torques. Finally, taking a three-phase 6/20-pole switched reluctance motor as the control object, the simulation and experimental verification show that the control method can restrain torque ripple and reduce peak current and copper loss at the same time.

show abstract

“…J k max J p max Proposed TSF 85% 38.8% OCTSF [20] 66.67% 6.19% TSF-MPC [19] 54% 7.14% Modified TSF [21] 67.21% 7.49%…”

Section: Methodsmentioning

confidence: 99%

“…In [18], the torque ripple is reduced by off-line optimization of TSF, so as to obtain the best TSF. In [19], the vector table is optimized by combining TSF and model prediction, which reduces the generation of torque ripple, but the peak current is large. Ref.…”

Section: Introductionmentioning

confidence: 99%