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Adaptive internal model-based suppression of torque ripple in brushless DC motor drives

机译:基于自适应内部模型的无刷直流电动机驱动器转矩脉动抑制

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Permanent-magnet synchronous motors (PMSMs) are widely used as high-performance variable-speed drives. Ripple in the electric torque of such motors is often a source of vibration and tracking errors, especially at low speeds. We study the torque characteristics of PMSMs and propose a method to minimize the torque ripple. First, we establish a detailed model for the motor and present a Fourier analysis of the torque ripple, caused by the non-sinusoidal back electro-motive force (BEMF) and the cogging torque, where the main conclusion is that the frequencies present in the torque disturbance are integer multiples of six times the electric frequency. The resulting model is highly nonlinear. We propose an adaptive controller based on the internal model principle, where the resonant frequencies of the controller and the associated gains change according to the motor speed. This is achieved by replacing the time variable by the motor angle, which simplifies the nonlinear model. Our approach is passivity based and will work also for complex mechanical loads and several resonant frequencies. Simulation and experimental results are given to verify the new controller. We compare the performance of our adaptive algorithm with the well-known one from [Canudas de Wit, C., & Praly, L. (2000 Park, S. J., Park, H. W., Lee, M. H., & Harashima, F. (2000). A new approach for minimum torque ripple maximum efficiency control of BLDC motor. IEEE Transaction on Industrial Electronics , 47, 109–114. doi: 10.1109/41.824132[Crossref], [Web of Science ®]?[Google Scholar]). Adaptive eccentricity compensation. IEEE Trans. Control Syst. Technol. 8, 757–766]. We find that it performs similarly in simple configurations, and it works also when the motor is part of a more complex system, for example, when the motor is connected to a load via a very flexible shaft.
机译:永磁同步电动机(PMSM)被广泛用作高性能变速驱动器。这样的电动机的电转矩的波动通常是振动和跟踪误差的来源,尤其是在低速时。我们研究了永磁同步电动机的转矩特性,并提出了一种最小化转矩波动的方法。首先,我们建立电动机的详细模型,并对由非正弦反向电动势(BEMF)和齿槽转矩引起的转矩脉动进行傅立叶分析,主要结论是存在于电动机中的频率转矩扰动是电频率的六倍的整数倍。结果模型是高度非线性的。我们基于内部模型原理提出了一种自适应控制器,其中控制器的谐振频率和相关的增益会根据电动机速度而变化。这是通过将时间变量替换为电动机角度来实现的,从而简化了非线性模型。我们的方法基于无源性,并且还将适用于复杂的机械负载和多个谐振频率。通过仿真和实验结果验证了该新型控制器的有效性。我们将自适应算法的性能与[Canudas de Wit,C.和Praly,L.(2000 Park,SJ,Park,HW,Lee,MH,&Harashima,F.(2000))中的著名算法进行比较。 。BLDC电动机的最小转矩脉动最大效率控制的新方法工业电子学学报,47,109–114。doi:10.1109 / 41.824132 [Crossref],[Web of Science®]?[Google Scholar] )。自适应偏心补偿。 IEEE Trans。控制系统技术。 8,757–766]。我们发现它在简单的配置中具有相似的性能,并且当电动机是更复杂的系统的一部分时(例如,当电动机通过非常柔软的轴连接到负载时)也可以工作。

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