发表机构
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种基于时间回归的无模型无传感器控制方法，通过堆叠电压积分和电流增量构建回归，消除电感项并重构转子磁链，无需指定电机参数即可估计转子位置，实验验证了其有效性。
AI 中文摘要
针对表贴式永磁同步电机（SPMSM）无传感器控制对电机参数普遍敏感的问题，本文提出一种基于时间回归的无模型无传感器控制（TFC）方法。首先，将连续短时间间隔内的电压积分和电流增量堆叠起来，构建一个有限窗口回归，其中未知的定子电感表现为一个公共标量系数。其次，由堆叠的电流增量构造的投影算子消除了电感项，并开发了最小二乘公式来重构转子磁链矢量。同时，对投影回归和电流-磁链几何的分析建立了一个二维方向矢量，其分量共享一个包含定子电阻和磁链的公共幅值。该幅值在位置提取过程中被抵消。通过将电阻参考值设置为零，所提方法无需指定定子电阻、电感或磁链即可估计位置。最后，实验结果验证了所提TFC方法的有效性。
英文摘要
To address the widespread sensitivity of surface-mounted permanent magnet synchronous motor (SPMSM) sensorless control to motor parameters, this paper proposes a temporal regression-based model-free sensorless control (TFC) method. First, voltage integrals and current increments over consecutive short intervals are stacked to construct a finite window regression, in which the unknown stator inductance appears as a common scalar coefficient. Second, a projection operator constructed from the stacked current increments eliminates the inductance term, and a least-squares formulation is developed to reconstruct the rotor flux vector. Meanwhile, the analysis of the projected regression and current-flux geometry establishes a two-dimensional direction vector whose components share a common amplitude containing the stator resistance and flux linkage. This amplitude cancels during position extraction. By setting the resistance reference to zero, the proposed method estimates the position without specifying the stator resistance, inductance, or flux linkage. Finally, experimental results verify the effectiveness of the proposed TFC method.
