摘要
针对混合动力汽车用感应电机模型参数时变性突出的问题,研究感应电机多模型参数在线辨识算法。依据龙伯格观测器和滑模控制理论,提出龙伯格-滑模观测器在线辨识感应电机模型参数的新方法。该方法将龙伯格-滑模观测器和自适应辨识算法结合起来对定子电流和转子磁链同时进行在线实时跟踪和自适应调节,利用定子电流估计变量的动态误差,在李亚普诺夫渐进稳定条件下实时辨识感应电机主要模型参数Rr和Rs。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。仿真结果验证所提方法的有效性。
The induction motor parameters vary with the operating conditions considerably in the Hybrid Electric Vehicle.In view of the situation,an on-line parameter identification method for induction motors was investigated.Based on the theory of Luenberger observer and sliding mode control,a novel Luenberger-sliding mode observer with adaptive identification was presented to estimate the parameters of induction motor in real time.A Luenberger-sliding mode observer and an adaptive identification method were used to simultaneously track and adapt the stator current and rotor flux.Estimated stator current dynamic output error was employed to identify rotor resistance,stator resistance with Lyapunov＇s stability criterion in real time.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.
出处
《电机与控制学报》
EI
CSCD
北大核心
2011年第8期93-100,共8页
Electric Machines and Control
基金
辽宁省教育厅科学技术研究项目(200803525)
关键词
混合动力汽车
感应电机
龙伯格“—”滑模观测器
动态输出误差技术
参数自适应
hybrid electric vehicle（HEV）
induction motors
Luenberger-sliding mode observer
dynamic output error technique
parameter adaptation
