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中文摘要：
提出一种基于自适应线性元件（Adaline）神经网络辨识表面式永磁同步电机定子绕组电阻、电感和转子磁链的方法。所提出的辨识方法不需要知道电机的任何设计参数信息,只需在线采样定子电流、电压和转速值即可。该方法首先在电机静止状态时估算出定子绕组电阻值,并利用该电阻值在电机启动时辨识出转子磁链和定子电感值,而所辨识出来的转子磁链值将被进一步用来在线估算定子绕组电阻的变化。实验显示该方法能够有效辨识定子电阻、电感和转子磁链。此外,当电机带负载运行时,该方法依然能够有效地在线跟踪电机定子绕组电阻变化。
英文摘要：
An Adaline neural network （NN） based estimation strategy is proposed for estimating the winding resistance,inductance and rotor flux linkage of surface-mounted permanent magnet synchronous machines （SPMSM）.The proposed method does not need any machine design parameter information for estimation and only needs to sample the stator currents,voltages and rotor speed.In the proposed estimation,the stator winding resistance value is firstly estimated at PMSM standstill and the estimated winding resistance value is then used for estimating the rotor flux linkage and inductance when the PMSM is started.Further,the estimated rotor flux linkage value is used for online estimating the variation of stator winding resistance.The validity of proposed method is verified by experiments which show that it is effective in estimating the winding resistance,inductance and rotor flux linkage.In addition,it is also effective in online tracking the stator winding resistance variation when the PMSM is with load.
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