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A Wavelet Filtering Scheme for Noise and Vibration Reduction in High-frequency Signal Injection-Based Sensorless Control of PMSM at Low Speed

机译:基于高频信号注入的PMSM低速无传感器控制的降噪和小波滤波方案

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摘要

This paper presents a technique for noise and vibration reduction in low-speed sensorless control algorithm of surface mounted permanent magnet synchronous machines (SM-PMSM). The signal processing involved in high-frequency-based sensorless control algorithms has a significant effect on the vibration and noise accompanying such algorithms. Therefore, a wavelet filtering approach is proposed. This wavelet filter is capable of extracting the position information even at low values of injection voltage amplitude where conventional filters fail to extract the information. This leads to a reduction in the machine''s noise and vibration. Furthermore, an optimization using hardware-in-the-loop method based on genetic algorithms was implemented in real time to obtain the optimum value of the injected voltages amplitude and frequency causing the least possible vibration with acceptable position estimation accuracy. Consequently, a significant reduction in vibration and noise was achieved. The proposed techniques were implemented on a 2-hp SM-PMSM motor both experimentally and through simulations. Comparisons between numerical and test results confirm the validity of the proposed techniques.
机译:本文提出了一种用于表面安装永磁同步电机(SM-PMSM)的低速无传感器控制算法中的降噪和减振技术。基于高频的无传感器控制算法中涉及的信号处理会对伴随此类算法的振动和噪声产生重大影响。因此,提出了一种小波滤波方法。该小波滤波器即使在常规滤波器不能提取信息的低注入电压幅度值的情况下也能够提取位置信息。这样可以减少机器的噪音和振动。此外,基于遗传算法的硬件在环方法的实时优化得以实现,从而以可接受的位置估计精度获得了使振动最小的注入电压幅度和频率的最佳值。因此,大大降低了振动和噪音。通过实验和仿真,在2 hp SM-PMSM电动机上实施了建议的技术。数值和测试结果之间的比较证实了所提出技术的有效性。

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