Speed Harmonic Based Modeling and Estimation of Permanent Magnet Temperature for PMSM Drive Using Kalman Filter
Speed Harmonic Based Modeling and Estimation of Permanent Magnet Temperature for PMSM Drive Using Kalman Filter
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DOI：
10.1109/tii.2018.2849986
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发表时间：
2019-03
影响因子：
12.3
通讯作者：
G. Feng;Chunyan Lai;N. Kar
中科院分区：
文献类型：
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作者：
G. Feng;Chunyan Lai;N. Kar
本文研究了利用实测转速谐波对永磁同步电机的永磁温度进行建模和估计。首先，建立了一个线性温度模型，证明了转速谐波的大小随PMT的增加而线性减小。为了实现这一线性模型，注入满足一定条件的谐波电流产生速度谐波。为了提高PMT估计的性能，将PMT估计表示为基于导出的温度模型的状态空间模型，并利用卡尔曼滤波从测量的速度谐波中估计PMT。与现有方法相比，该方法具有估计简单、对电机电阻和电感变化具有鲁棒性等优点。在不同转速和负载条件下的实验室永磁同步电机驱动系统上进行了大量实验，对所提出的基于卡尔曼滤波的建模和估计方法进行了验证。
This paper investigates permanent magnet temperature (PMT) modeling and estimation for permanent magnet synchronous machines (PMSMs) by using the measured speed harmonic. First, a linear temperature model is derived to demonstrate that the magnitude of the speed harmonic decreases linearly with the increase of PMT. To achieve this linear model, the speed harmonic is induced by the injected harmonic currents satisfying certain conditions developed in this paper. To improve the estimation performance, PMT estimation is represented in a state–space model based on the derived temperature model, and the Kalman filter is applied to estimate the PMT from the measured speed harmonic. Compared with existing methods, the proposed approach has advantages in terms of simplicity in estimation and robustness to the variation of machine resistance and inductances. The proposed Kalman filter based modeling and estimation approach is evaluated with extensive experiments on a laboratory PMSM drive system under different speed and load conditions.