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出 处:《微电机》2013年第3期46-49,57,共5页Micromotors
基 金:辽宁省教育厅科学技术研究项目(200803525)
摘 要:基于感应电机损耗模型的效率优化控制策略易受参数变化的影响,混合动力车用感应电机参数时变性突出,常常使电机不能运行在效率最优点。针对这一问题,设计一个龙伯格-滑模观测器在线辨识感应电机模型参数,提出了基于参数在线估计的异步电动机效率优化控制策略。电机损耗模型参数的在线辨识,极大地提高效率优化方法对电机参数变化的鲁棒性。该方法结构简单、可靠,对驱动系统内部噪声和大测量信号扰动有很强的鲁棒性,并易于工程实现。仿真结果验证了所提方法的有效性。The optimized efficiency control derived from the expression of the minimum power losses is sensi- tive to parameter variations of induction motors. The induction motor could not be expected to operate at high efficiency due to motor parameters varying considerably and frequently in the hybrid electric vehicle. In view of the situation, a Luenberger-sliding mode observer was presented to estimate the parameters of induction motor in real time. A novel efficiency control strategy with adaptive parameter identification was investigated. The on-lineparameter identification of induction motor power losses model improved the algorithm robust to parameter variation greatly. The proposed method is simple, reliable, robust in the event of internal noise and large disturbances in measurements, and is easy to be implemented in practical applications. Simulation results show the effectiveness of the proposed identification algorithm.
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