Finite control-set model predictive current control of five-phase permanent-magnet synchronous machine based on virtual voltage vectors
Finite control-set model predictive current control of five-phase permanent-magnet synchronous machine based on virtual voltage vectors
复制标题
基于虚拟电压矢量的五相永磁同步电机有限控制集模型预测电流控制
DOI：
10.1049/iet-epa.2016.0529
复制
发表时间：
2017-05
影响因子：
1.7
通讯作者：
Feng Xiaoyun
中科院分区：
文献类型：
--
作者：
Xue Cheng;Song Wensheng;Feng Xiaoyun
针对五相永磁同步电机，提出了一种基于虚拟电压矢量的有限控制集模型预测电流控制（FCS-MPCC）方案，旨在降低定子电流中的低次谐波分量。此外，与传统的FCS-MPCC算法相比，该算法在保持快速控制动态响应的同时，还具有计算负担较小、在整个速度范围内开关频率近似恒定、电流谐波含量较低（尤其是三次谐波）等优点。此外，提出的FCS-MPCC方案在数字控制器实现的一步延迟补偿解决方案。最后，通过一系列的计算机仿真和硬件在环（HIL）实验测试，比较了所提出的FCS-MPCC和两个传统的FCS-MPCC方案的性能。仿真和半实物仿真实验结果验证了所提出的基于虚拟电压矢量的FCS-MPCC方案的正确性和有效性。
This study proposes a finite control-set model predictive current control (FCS-MPCC) scheme based on virtual voltage vectors for five-phase permanent magnet synchronous machines, which aims to reduce the low-order harmonic components of stator currents. In addition, comparing with traditional FCS-MPCC algorithms, the proposed algorithm retains fast control dynamic response and brings several other benefits: such as smaller burden of calculation, approximate constant switching frequency in entire speed operation range and lower current harmonics, especially for three-order harmonics. Furthermore, the one-step delay compensate solution of the proposed FCS-MPCC scheme in digital-controller implementation is presented. Finally, a series of computer simulation and hardware-in-loop (HIL) experimental tests are adopted to compare the performances of the proposed FCS-MPCC and two traditional FCS-MPCC schemes. Simulation and HIL experimental results have verified the validity and effectiveness of the proposed FCS-MPCC scheme using virtual voltage vectors.
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影响因子：
4.4
作者：
Eunsoo Jung;Hyun-Jae Yoo;S. Sul;Hong-soon Choi;Yun-Young Choi
通讯作者：
Eunsoo Jung;Hyun-Jae Yoo;S. Sul;Hong-soon Choi;Yun-Young Choi
影响因子：
7.7
作者：
P. Cortes;M. Kazmierkowski;R. Kennel;D. Quevedo;J. Rodríguez
通讯作者：
P. Cortes;M. Kazmierkowski;R. Kennel;D. Quevedo;J. Rodríguez
影响因子：
7.7
作者：
Yuan Ren;Z. Zhu
通讯作者：
Yuan Ren;Z. Zhu
影响因子：
7.7
作者：
C. Lim;E. Levi;Martin Jones;N. Rahim;W. Hew
通讯作者：
C. Lim;E. Levi;Martin Jones;N. Rahim;W. Hew
DOI：
--
发表时间：
2011
期刊：
China Railway Science
影响因子：
--
作者：
Feng Xiaoyun
通讯作者：
Feng Xiaoyun