关键词: 空调外风机, 永磁同步电机, 双矢量模型预测控制, 稳态性能, 动态响应

Abstract: The drive performance of the outdoor fan directly affects the overall energy-saving capability and operational stability of the system, although conventional finite control set model predictive control (FCS-MPC) offers fast dynamic response, it applies only a single voltage vector within each sampling period, which easily leads to large steady-state current ripples and torque pulsations. As a result, it is difficult to meet the requirements of high-efficiency and low-noise operation for outdoor fan drives. To address this issue, a double-vector model predictive control strategy for household air conditioner outdoor fan drives was proposed. In each sampling period, the optimal and suboptimal voltage vectors are jointly introduced, and their action durations are reasonably allocated according to the torque error relationship, thereby achieving deadbeat torque control. In this way, prediction errors are effectively compensated and steady-state performance is significantly improved. Experimental results demonstrate that, under identical operating conditions, the proposed double-vector model predictive control can significantly reduce steady-state current ripples and torque pulsations while maintaining a dynamic response speed comparable to that of the conventional method. Under steady-state conditions, the total harmonic distortion (THD) of the phase current is reduced from 23.07% to 7.63%, and the steady-state speed fluctuation amplitude is decreased from approximately ±5 r/min to ±1 r/min, with a clear improvement in the sinusoidal quality of the current waveform. The result verify the effectiveness of the proposed method in enhancing steady-state current quality, reducing noise potential, and improving system operating efficiency, indicating its strong potential for practical application in household air conditioner outdoor fan drive systems.

Key words: Outdoor fan of air conditioner, Permanent magnet synchronous motor, Double-vector model predictive control, Steady-state performance, Dynamic response