TY - JOUR
T1 - Model Predictive Torque Control of Switched Reluctance Machines With Torque Sharing Function and PWM Control Signals Based on Linear Polynomial Fitting
AU - Ge, Lefei
AU - Guo, Jixuan
AU - Gong, Chao
AU - Zhang, Guoqiang
AU - Ding, Xiaofeng
AU - Song, Shoujun
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2025
Y1 - 2025
N2 - In the combination of torque sharing function (TSF) and model predictive torque control (MPTC), the finite set prediction with only three evaluated switching states can not fully exploit the capability of MPTC. This letter proposes a novel MPTC with the TSF and pulse width modulation (PWM) control signals based on linear polynomial fitting for the torque ripple suppression of the switched reluctance machine (SRM). The sinusoidal TSF is used to distribute the reference torque to each phase. To fully utilize the flexibility of PWM control signals, the linear polynomial fitting method is adopted to expand the predictive data obtained by the prediction model, which avoids the redundant lookup table calculation. Then, the optimal duty cycle corresponding to the minimum torque tracking error is found and applied. The experimental results show that the proposed MPTC has good reference torque tracking capability and torque ripple suppression performance.
AB - In the combination of torque sharing function (TSF) and model predictive torque control (MPTC), the finite set prediction with only three evaluated switching states can not fully exploit the capability of MPTC. This letter proposes a novel MPTC with the TSF and pulse width modulation (PWM) control signals based on linear polynomial fitting for the torque ripple suppression of the switched reluctance machine (SRM). The sinusoidal TSF is used to distribute the reference torque to each phase. To fully utilize the flexibility of PWM control signals, the linear polynomial fitting method is adopted to expand the predictive data obtained by the prediction model, which avoids the redundant lookup table calculation. Then, the optimal duty cycle corresponding to the minimum torque tracking error is found and applied. The experimental results show that the proposed MPTC has good reference torque tracking capability and torque ripple suppression performance.
KW - Linear polynomial fitting
KW - model predictive control
KW - switched reluctance machine (SRM)
KW - torque ripple
KW - torque sharing function (TSF)
UR - http://www.scopus.com/inward/record.url?scp=85201632893&partnerID=8YFLogxK
U2 - 10.1109/TPEL.2024.3444891
DO - 10.1109/TPEL.2024.3444891
M3 - 文章
AN - SCOPUS:85201632893
SN - 0885-8993
VL - 40
SP - 40
EP - 45
JO - IEEE Transactions on Power Electronics
JF - IEEE Transactions on Power Electronics
IS - 1
ER -