Considerations of Stator Resistance Online-tuning Method for MRAS-based Speed Sensorless Induction Motor Drive

C. Lu, Yi Liu, Xianghua Bao, Yu Zhang, Jianping Ying
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引用次数: 3

Abstract

Model reference adaptive system (MRAS) based estimator has become the dominant speed estimation approach for sensorless induction motor drives. However, stator resistance thermo variation always deteriorates speed estimation stability and accuracy at low speeds, especially in the generating-mode operation, which is a common challenge to MRAS-based speed estimators. To improve the drive's robustness, generally the stator resistance should be estimated simultaneously at low speeds. In this paper, the two estimators, conventionally regarded as a complex fourth-order MIMO system, are decoupled to be two simple second-order SISO systems based on the two-time-scale approach. Simple but general design principles rather than complicated numerical solutions are presented to stabilize the estimators. A novel error function with dynamic convergence is proposed to estimate stator resistance in acceleration, deceleration and impact-load situations. Stability of the proposed estimators is verified by extensive experiments. Analysis method of this paper can be extended to other MRAS schemes.
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基于mras的无速度传感器异步电机驱动定子电阻在线整定方法的思考
基于模型参考自适应系统(MRAS)的估计器已成为无传感器异步电机驱动速度估计的主流方法。然而,定子电阻热变化总是会降低低速下,特别是在发电模式运行时,速度估计的稳定性和准确性,这是基于mras的速度估计所面临的共同挑战。为提高驱动器的稳健性,一般应在低速时同时对定子电阻进行估计。本文基于双时间尺度方法,将两个通常被视为复杂四阶MIMO系统的估计器解耦为两个简单的二阶SISO系统。给出了简单但通用的设计原则,而不是复杂的数值解来稳定估计器。提出了一种新的动态收敛误差函数,用于估计加、减速和冲击载荷情况下的定子电阻。通过大量的实验验证了所提估计器的稳定性。本文的分析方法可以推广到其他MRAS方案。
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