基于转子时间常数在线辨识的车用异步电机转速估计

Speed estimation of asynchronous motor for vehicle based on rotor time constant on-line identification

针对转子时间常数变化导致转速估计精度降低的问题,文中提出了一种基于转子时间常数在线辨识的车用异步电机扩展卡尔曼滤波(EKF)转速估计方法。该方法利用静止坐标系下电机动态模型和测量得到的电压、电流及估算转速来实时辨识异步电机转子时间常数。仿真结果表明,本文提出的方法能够在较宽调速范围内准确辨识出电机的转子时间常数,而且计算简单可靠,易于实现在线实时辨识,同时不受定子电阻变化的影响,低速下依然能够对转子时间常数准确辨识,具有较高的鲁棒性。与传统EKF转速估计方法相比,文中提出的方法考虑到了转子时间常数变化对转速估计和磁链定向的影响,因而具有更高的转速估计精度,进而验证了该方法的有效性和可行性。研究结果可为异步电机转子时间常数辨识提供了一种新方法。

In view of the problem that the variation of asynchronous motor rotor time constant reduces the accuracy of the speed estimation,a new method of speed estimation for vehicle asynchronous motor with extended Kalman filter(EKF)based on rotor time constant on-line identification is proposed.The method utilizes the motor dynamic model in the stationary reference frame and the measured motor voltage,current and estimated speed to identify the rotor time constant of the asynchronous motorin real time.The simulation result shows that the proposed method can accurately identify the rotor time constant in a wide speed range while the computation is simple and reliable.It is easy to implement real-time on-line identification and is not affected by the variation of the stator resistance socan be accurately identified at low speed then has high robustness.Compared with the traditional EKF speed estimation method,the method takes into account the influence of rotor time constant variation on the speed estimation and flux orientation then has higher estimation accuracy.The research result provides a new method for asynchronous motor rotor time constant identification.