摘要
用扩展的卡尔曼滤波算法(EKF)对表贴式交流永磁无刷同步电动机进行动态参数估计,根据电机控制系统中传感器检测到的电机定子电流、电压和转子的位置、转速等信号,推算电机定子绕组的电阻和转子的主磁通值,经过对电机模型和卡尔曼算法的分析,给出了电机控制系统的全阶卡尔曼滤波模型和经过简化处理后的降阶估计模型,用降阶的简化模型对系统进行估计后,得到了定子电阻和转子主磁通的结果,并分析了定子电阻和转子磁通估计值和实际值之间的误差,以及估计值随电机转速和负载大小变化的曲线.电机用脉宽调制(PWM)的电压源逆变器供电,用TMS320F2812系列数字信号处理器(DSP)作为控制芯片,用矢量控制的策略对电机进行转速控制.
The linearized and reduced order Extended Kalman Filter （EKF） arithmetic is employed in parameter identification including estimate estimation of the stator winding resister and rotor flux linkage in surface-mounted permanent magnet brushless AC motor, according to stator voltages, currents, rotor position and speed measured from the motor. Having analyzed the model of the motor and arithmetic of Kalman Filter, we establish a full order and a reduced order of Kalman Filter model, and also obtain the estimated value through the model. The error between real value and estimated value is analyzed in the paper and the curves of the resistance and flux-linkage, which vary with speed, and the loads are also analyzed in the paper. In the motor control system, PWM inverter is used as power supply of the motor, and a new generation of micro DSP TMS320F281 is employed as a controller. At the end of the paper, the estimated results of stator resistor and rotor flux linkage are presented.
出处
《南京师范大学学报（工程技术版）》
CAS
2008年第1期7-12,共6页
Journal of Nanjing Normal University(Engineering and Technology Edition)
关键词
扩展的卡尔曼算法
交流永磁电机
参数辨识
降阶模型
extended kalman filter arithmetic, permanent AC motor, parameter identifier, reduced order model
