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Parameter Identification Based Online Noninvasive Estimation of Rotor Temperature in Induction Motors
IEEE Transactions on Industry Applications ( IF 4.2 ) Pub Date : 2020-11-23 , DOI: 10.1109/tia.2020.3039940
Haisen Zhao , Hassan H. Eldeeb , Jinyu Wang , Jinping Kang , Yang Zhan , Guorui Xu , Osama A. Mohammed

This article proposes a rotor temperature estimation method for in-service induction machine (IM) based on parameter identification, which combines the advantage of recursive least squares (RLS) and model reference adaptive system (MRAS). The RLS with forgetting factor is firstly adopted to identify the parameters of motor inductances. Then, the online identification of rotor resistance can be realized via the MRAS based on the instantaneous reactive power (IRP) and the proportional integral (PI) regulation adaptive law designed by the Popov hyper-stable theory. Thereby, the rotor temperature is computed by the resistance-temperature relationship of metals. To achieve a fast convergence of the parameter identification, rotor slot harmonics are extracted from the stator current and used to determine the rotor speed in real time. Furthermore, to obtain a more accurate initial value of the stator and rotor leakage inductances and resistances, the first 5-15 cycles of the IM starting process are used to mimic the locked-rotor test condition. A merit of the proposed method is that it requires significantly less time to estimate the rotor resistance than the traditional methods. With a novel test bench, experimental validation is performed on a 22-kW IM. In the test, the rotor temperature is measured in three different ways: 1) wireless sensors inserted in the rotating rotor core and rotor end rings, 2) infrared sensor for rotor end ring temperature, and 3) PT100 installed in stator end winding. With this test bench, the real rotor temperature was revealed, and the effectiveness of the presented method is also verified.

中文翻译:


基于参数辨识的感应电机转子温度在线无创估算



本文提出一种基于参数辨识的在役感应电机(IM)转子温度估计方法,该方法结合了递归最小二乘法(RLS)和模型参考自适应系统(MRAS)的优点。首次采用带遗忘因子的RLS来辨识电机电感参数。然后,通过基于瞬时无功功率(IRP)和波波夫超稳定理论设计的比例积分(PI)调节自适应律的MRAS,可以实现转子电阻的在线辨识。由此,通过金属的电阻-温度关系计算转子温度。为了实现参数识别的快速收敛,从定子电流中提取转子槽谐波并用于实时确定转子速度。此外,为了获得更准确的定子和转子漏感和电阻的初始值,IM启动过程的前5-15个周期用于模拟堵转测试条件。该方法的一个优点是,与传统方法相比,估计转子电阻所需的时间要少得多。通过新颖的测试台,在 22 kW IM 上进行实验验证。在测试中,转子温度通过三种不同的方式测量:1)插入旋转转子铁芯和转子端环的无线传感器,2)用于转子端环温度的红外传感器,3)安装在定子端绕组中的PT100。通过该试验台,揭示了转子的真实温度,验证了该方法的有效性。
更新日期:2020-11-23
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