【目的】扩展卡尔曼滤波器(EKF)在无传感器无刷直流电机驱动系统中应用广泛，可基于非线性电机模型递归估计转子位置与转速。然而，EKF固有的线性化特性导致逼近精度有限，使得估计器对参数不确定性、模型失配及噪声统计偏差极为敏感。这些局限性会导致估计的电角度和转速随时间漂移，进而引发换相误差，显著降低电机运行性能。【方法】为解决此问题，本文提出一种基于相反电动势与相电流基波相位同步的换相误差校正方法。首先，采用可变中心频率基波提取滤波器提取相电流与相反电动势的基波分量。其次，基于两相坐标系中的矢量关系构建换相误差表征量。当该表征量大于零时表示换向滞后，小于零时表示换向超前。然后，通过比例积分控制器对误差表征量进行闭环调节，使其收敛至零，实现换向时序的自适应校正。最后，通过仿真和试验对所提换相误差校正方法进行验证。【结果】仿真与试验结果具有良好的一致性，所提方法对控制回路中各类非理想因素引起的换相误差具有较强的鲁棒性，有效校正了换相误差，显著改善了电流波形对称性，使换相过程更加平滑稳定。在滞后换相和超前换相状态下，相电流峰峰值分别降低了75%和67%，且转子位置误差保持在0.2 rad以内。【结论】本文所提基于EKF观测器和相电流与相反电动势基波相位同步的换相误差校正方法可以有效校正换相误差，显著减少功率损耗，提高系统效率与运行稳定性。

[Objective] The extended kalman filter (EKF) is widely used in sensorless brushless DC motor drive systems and can recursively estimate rotor position and speed based on the nonlinear motor model. However, the inherent linearization characteristic of the EKF results in limited approximation accuracy, making the estimator extremely sensitive to parameter uncertainties, model mismatches, and deviations in noise statistics. These limitations can cause the estimated electrical angle and speed to drift over time, leading to commutation errors and significantly reducing motor operating performance. [Methods] To address this issue, this paper proposed a commutation error correction method based on the phase synchronization between the fundamental components of phase back electromotive force and phase current. Firstly, a variable center frequency fundamental extraction filter was employed to extract the fundamental components of both phase current and phase back electromotive force. Secondly, using the vector relationships in the two-phase coordinate system, a commutation error indicator was constructed. When this commutation error indicator was greater than zero, it indicated lagging commutation, when less than zero, it indicated leading commutation. Finally, the commutation error indicator was closed-loop regulated through a proportional integral controller, driving it toward zero and thereby achieving adaptive correction of the commutation timing. [Results] The simulation and experimental results showed good consistency. The proposed method exhibited strong robustness against phase errors induced by various non-ideal factors within the control loop, effectively correcting commutation errors, significantly improving the symmetry of the current waveforms, rendering the commutation process smoother and more stable. Under both lagging and leading commutation conditions, the peak-to-peak values of phase current were reduced by 75% and 67% respectively, and the rotor position error remained within 0.2 rad. [Conclusion] The proposed commutation error correction method based on EKF and phase synchronization of fundamental components between phase current and phase back electromotive force effectively corrects commutation errors, significantly reduces power loss, and enhances both system efficiency and operational stability.

国家自然科学基金(32371868)