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Research on speed sensorless operation of PMSM based on improved MRAS

机译：基于改进型MRAS的永磁同步电机无速度传感器运行研究

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The traditional model reference adaptive system (MRAS) has the problem of error accumulation and DC bias in the pure integration of flux observation. In order to solve this problem, this paper presents an improved model reference adaptive speed identification method. A high pass filter is added to the voltage model to eliminate the pure integral effect, and a high pass filter is added to the current model to balance the phase and amplitude errors. Thus, the influence of DC bias can be eliminated. On the other hand, when the flux is observed, the feedback quantity is added, and the error value is obtained by comparing the stator flux values obtained by the voltage model and the current model respectively. Then, the error value is corrected by the PI regulator, it can improve the accuracy of the observer. In the MATLAB/SIMULINK environment, the model reference adaptive algorithm is simulated. The results show that the model reference adaptive algorithm can realize the accurate estimation of the rotor speed and position without load start and load start, and realize the sensorless operation of the permanent magnet synchronous motor.
机译：传统的模型参考自适应系统（MRAS）在通量观测的纯积分中存在误差累积和DC偏置的问题。为了解决这个问题，本文提出了一种改进的模型参考自适应速度识别方法。高通滤波器被添加到电压模型以消除纯积分效应，高通滤波器被添加到电流模型以平衡相位和幅度误差。因此，可以消除直流偏置的影响。另一方面，当观察到磁通量时，添加反馈量，并且通过比较分别由电压模型和电流模型获得的定子磁通值来获得误差值。然后，通过PI调节器校正误差值，可以提高观察者的准确性。在MATLAB / SIMULINK环境中，对模型参考自适应算法进行了仿真。结果表明，模型参考自适应算法可以在没有负载启动和负载启动的情况下实现转子速度和位置的准确估计，并实现了永磁同步电动机的无传感器运行。

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