针对永磁同步电机无差拍预测控制共模电压较大的问题,在一个控制周期内采用相位相反的基本电压矢量来生成虚拟零电压矢量抑制共模电压,并采用动态选择虚拟电压矢量生成方式来减小开关频率。为了提升无差拍预测控制性能,构造12个虚拟非零电压矢量来增加备选电压矢量。仿真结果表明:与7个基本备选电压矢量相比,基于19个备选电压矢量的无差拍预测控制降低转矩脉动6.89%,降低磁链脉动13.33%,同时共模电压也得到有效抑制。相较固定生成方式,动态选择虚拟电压矢量生成方式可降低开关频率25.89%。虽然该方法可有效提升系统性能,但增加遍历次数,极大增大计算量。为提高算法实时性,提出一种通过判断理想电压矢量所在区域来确定最优电压矢量简化确定方法,无需遍历计算,减小运算负担。基于STM32H743IIT6单片机实时性试验表明:相较于7个基本电压矢量,采用19个电压矢量算法执行时间增大273.40%,最优电压矢量简化确定方法执行时间减小88.09%。

To address the problem of high common-mode voltage in deadbeat predictive control for permanent magnet synchronous motor (PMSM), this paper proposed the use of opposite-phases basic voltage vectors within one control cycle to generate a virtual zero voltage vector, which suppressed the common-mode voltage. A dynamic selection method for generating virtual voltage vectors was adopted to decrease switching frequency. To further improve the performances of deadbeat predictive control, 12 virtual non-zero voltage vectors were introduced to expand candidate voltage vector set. Simulation results showed that, compared to using 7 basic candidate voltage vectors, the deadbeat predictive control based on 19 candidate voltage vectors reduced torque ripple by 6.89%, decreased flux linkage ripple by 13.33% and effectively suppressed common-mode voltage. The dynamic selection method for virtual voltage vector generation reduced the switching frequency by 25.89% compared to the fixed generation method. Although this method significantly improved system performance, it increased the number of iterations, leading to a substantial increase in computation burden. To enhance the real-time performance of the algorithm, a simplified method was proposed, which determined the optimal voltage vector by identifying the region where the ideal voltage vector resided, eliminating the need for exhaustive calculations and reducing the computation burden. Real-time experiments based on the STM32H743IIT6 microcontroller showed that compared with using 7 voltage vectors, deadbeat predictive control using 19 voltage vectors increased execution time by 273.40%, while the optimal voltage vector simplified determination method reduced execution time by 88.09%.

长安大学2024年研究生科研创新实践项目(300103724044)