基于磁链衰减数据的同步电机参数的最大似然估计

Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting Pub Date : 1992-10-04 DOI:10.1109/IAS.1992.244295

A. Tumageanian, A. Keyhani, S. Moon, T. Leksan, L. Xu

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引用次数: 17

摘要

提出了一种从静止试验测量中估计5kva凸极电机参数的时域系统辨识方法。测试包括施加在机器的d轴和q轴上的直流磁通衰减信号。根据对该信号的记录响应，确定了导纳传递函数模型和静止频率响应(SSFR)等效电路模型。采用最大似然算法估计模型参数值，采用赤池准则选择最优拟合模型。通过在线小干扰试验仿真，研究了静止模型在动态环境下的性能。结果与实测数据进行了比较。

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Maximum likelihood estimation of synchronous machine parameters from flux decay data

A time-domain system identification procedure for estimating the parameters of a 5-kVA salient pole machine from standstill test measurements is proposed. The test consists of a DC flux decay signal applied to the d-axis and q-axis of the machine. From the recorded responses to this signal, the admittance transfer function models and the standstill frequency response (SSFR) equivalent circuit models are identified. The maximum-likelihood algorithm is used to estimate the model parameter values, and the Akaike criterion is used to select the best-fit model. The performance of the standstill models in the dynamic environment is studied through simulation of an online small-disturbance test. The results are compared with measured data.<>

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Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting

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