低计算复杂度的永磁同步电机多步预测电流控制

传统的永磁同步电机模型预测电流控制策略仅在一个采样周期内寻优,难以避免陷入局部最优问题,而多步预测会增加预测次数,计算复杂度成倍增长.为此,提出一种低复杂度的永磁同步电机三步电流预测控制策略.首先,在延时补偿的基础上,两步预测结合三矢量电压控制和最优占空比电压控制,三步预测保持与两步预测相同的电压矢量,然后由代价函数选出控制电压矢量;最后,设计电感dq轴分量双闭环的鲁棒控制.仿真结果表明,相比其他控制策略,所提策略具有良好的动静态性能,寻优代码执行时间降低了约51%;在不影响输出电能质量的前提下,开关频率降低了约17%;并对电感失配造成的性能恶化具有抑制性.

Low computational complexity multi-step predictive current control of permanent magnet synchronous motor

The traditional model predictive current control strategy of permanent magnet synchronous motor (PMSM) is only optimized in one sampling period, so it is difficult to avoid falling into the local optimal problem. But multi-step prediction will increase the number of prediction times, and the computational complexity will multiply. Therefore, a threestep current predictive control strategy of PMSM based on low complexity is proposed. Firstly, on the basis of time delay compensation, two-step prediction is combined with three vector voltage control and optimal duty cycle voltage control, the three-step prediction keeps the same voltage vector as the two-step prediction, and then the control voltage vector is selected by the cost function; finally, the double closed-loop robust control of dq axis component of inductor is designed. The simulation results show that the proposed strategy has good dynamic and static performance, compared with other control strategies, reduces the code execution time by about 51%, reduces the switching frequency by about 17% without affecting the power quality, and has a certain inhibition on the inductance mismatch.