基于递推最小二乘法与模型参考自适应法的鼠笼式异步电机转子电阻在线辨识方法

发布时间：2018-11-10 13:58

【摘要】：为了能够实时准确地获取鼠笼式异步电机转子电阻,提出一种将递推最小二乘法(recursive least square method,RLS)与模型参考自适应法(model reference adaptive system,MRAS)相结合的转子电阻在线辨识方法。该方法首先推导基于dq0坐标系下标准最小二乘法形式的电机参数辨识模型,采用带遗忘因子的递推最小二乘算法辨识得出电机电感参数;然后将上述辨识得到的电感值作为基于瞬时无功功率的模型参考自适应系统中的电机常数,并采用基于波波夫超稳定性理论设计的PI自适应律,实现不同运行状态下的转子电阻在线辨识。以一台5.5 kW异步电机为例进行了仿真与实验研究,仿真结果表明,文中方法适用于转速波动明显且转子电阻变化较大的复杂运行工况,且具有计算量少、准确度高以及较好的动态跟踪辨识性能;进行不考虑温升与考虑温升的转子电阻在线辨识实验对比,验证了文中方法的正确性与有效性。
[Abstract]:In order to obtain the rotor resistance of squirrel-cage asynchronous motor in real time and accurately, an on-line rotor resistance identification method combining recursive least square method (recursive least square method,RLS) and model reference adaptive method (model reference adaptive system,MRAS) is proposed. In this method, the motor parameter identification model based on the standard least square method in dq0 coordinate system is derived, and the inductance parameters are obtained by using the recursive least square algorithm with forgetting factor. Then the inductance obtained above is regarded as the motor constant in the model reference adaptive system based on instantaneous reactive power, and the PI adaptive law based on Popov's hyperstability theory is adopted. The rotor resistance online identification is realized under different running conditions. The simulation and experiment of a 5.5 kW asynchronous motor are carried out. The simulation results show that the proposed method is suitable for complex operating conditions where the speed fluctuation is obvious and the rotor resistance changes greatly. High accuracy and better dynamic tracking identification performance; Experiments of rotor resistance identification without or without temperature rise are carried out to verify the correctness and effectiveness of the proposed method.
【作者单位】：新能源电力系统国家重点实验室(华北电力大学);
【基金】：国家自然科学基金项目(51307050) 中央高校基本科研业务费项目~~
【分类号】：TM343

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