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机构地区:[1]天津大学电气与自动化工程学院,天津300072
出 处:《电机与控制学报》2018年第3期42-49,共8页Electric Machines and Control
基 金:国家高技术研究发展计划(863计划)(2011AA11A259)
摘 要:针对电机转子的鼠笼结构会导致总漏感随电流频率的不同而发生变化给激磁电感和转子电阻的测量带来偏差的问题,提出了一种离线辨识电机参数的算法。采用直流实验结合最小二乘法辨识定子电阻,采用低频交流实验辨识激磁电感和转子电阻,且激磁电感和转子电阻的辨识无需电机总漏感参数,从而消除了转子漏感参数变化给辨识带来的影响。另外,辨识算法辨识逆变器的非线性压降模型并对逆变器压降进行补偿以提高算法精度,激磁电感的辨识在不同激磁水平下进行以得到电机的激磁曲线。在TMS320F28035实验平台上实现辨识算法,验证了算法的辨识精度。In order to analyze the problem that the leakage inductance varies with current frequency because of the deep bar effect in squirrel-caged rotor that leads to the measured deviation of magnetizing inductance and rotor resistance,an offline parameter estimation algorithm for induction motors was proposed. Stator resistance was measured through DC test with the least square method while magnetizing inductance and rotor resistance were measured through low-frequency AC test. The proposed method eliminates the influence result from leakage inductance variation by identifying the magnetizing inductance and rotor resistance without the requirement of leakage inductance. Furthermore,the proposed algorithm identifies the nonlinear voltage drop on inverter and compensates for the voltage drop on inverter automatically to ensure the estimation precision. The magnetizing curve of induction motor is also obtained by estimating the magnetizing inductance under different levels of magnetizing. The effectiveness of the proposed estimation algorithm is validated on the platform of TMS320 F28035.
关 键 词:异步电机 鼠笼结构 逆变器非线性压降模型 激磁曲线
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