The Key Laboratory of Electronic Power and Power Transformation, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, PR China.
The Key Laboratory of Electronic Power and Power Transformation, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, PR China.
ISA Trans. 2023 Jun;137:615-628. doi: 10.1016/j.isatra.2023.01.024. Epub 2023 Jan 19.
In order to improve the accuracy of the speed and angle estimation of the permanent magnet synchronous motor (PMSM) in the sensorless mode, this paper firstly proposes a multi-sliding mode scheme based on model reference adaptive system (MRAS) with proportional integral (PI) control. The current disturbance of the sensorless method is suppressed by the multi-sliding mode based on MRAS method, thus reducing the disturbance of the current to the PI and indirectly improving the current anti-interference of the PI. Meanwhile, the quantitative analysis of the current disturbance by the MRAS based on multi-sliding mode scheme is presented in detail. Then, the suppression capability of different sliding-mode schemes is discussed. Finally, various experiments are designed to verify the feasibility of the scheme and the correctness of the theory.
为了提高无传感器模式下永磁同步电机（PMSM）速度和角度估计的精度，本文首先提出了一种基于模型参考自适应系统（MRAS）与比例积分（PI）控制的多滑模方案。无传感器方法中的电流干扰通过基于 MRAS 方法的多滑模来抑制，从而减小电流对 PI 的干扰，并间接提高 PI 的电流抗干扰能力。同时，详细给出了基于多滑模方案的 MRAS 对电流干扰的定量分析。然后，讨论了不同滑模方案的抑制能力。最后，设计了各种实验来验证方案的可行性和理论的正确性。
