【目的】为了解决永磁同步电机(PMSM)模型预测电流控制(MPCC)参数依赖性强的问题,本文提出了一种基于临近电流变化的预测模型,消除了电阻和转子磁链参数,提高了PMSM MPCC的参数鲁棒性。【方法】基于PMSM传统电流预测模型与临近电流变化,首先计算施加与上一时刻相同电压矢量Vn的预测电流值。然后,以此为基准值,计算得出施加其他电压矢量的预测值,从而建立基于临近电流变化的预测模型。最后,通过仿真和试验,对比了基于传统电流预测模型、增量式电流预测模型和临近电流变化预测模型的PMSM MPCC性能。【结果】仿真和试验结果表明,本文所提临近电流变化预测模型无需定子电阻和转子磁链参数,其控制性能与传统及增量式电流预测模型相当,且三者最优电压矢量选择一致。该模型仅依赖定子d、q轴电感,显著降低了参数依赖性,系统运行稳定。【结论】本文所提模型为PMSM MPCC提供了更简化的解决方案。

[Objective] To address the strong parameter dependence of permanent magnet synchronous motor (PMSM) model predictive current control (MPCC), this paper proposes a near-current-variation-based prediction model, which eliminates the resistance and rotor flux parameters, thereby improving the parameter robustness of PMSM MPCC. [Methods] Based on the traditional current prediction model of PMSM and near-current-variation, the predicted current value for applying the same voltage vector Vn as the previous moment was first calculated. Then, using this as a reference value, the predicted values for applying other voltage vectors were derived, thereby establishing a near-current-variation-based prediction model. Finally, through simulations and experiments, the performance of PMSM MPCC based on the traditional current prediction model, incremental current prediction model, and near-current-variation prediction model was compared. [Results] The simulation and experimental results demonstrated that the proposed near-current-variation prediction model did not require stator resistance or rotor flux linkage parameters, and its control performance was comparable to that of both the traditional and incremental current prediction models. Moreover, the optimal voltage vector selections of the three models were consistent. The proposed model relied solely on the stator d, q-axis inductance, significantly reducing parameter dependency while maintaining stable system operation. [Conclusion] The proposed model provides a more simplified solution for PMSM MPCC.

青海职业技术大学青海省高原汽车电动化与智能化技术重点实验室开放基金资助(QZDSZ03-202502)