Torque estimation for Direct Torque Controlled BLDC motor drive using Kalman Filter and Extended Kalman Filter are described in this paper. In conventional direct torque control method, the torque estimation is done based on the position information, which in turn requires position sensors for accurate estimation. In this paper, torque is directly estimated using Kalman filter and Extended Kalman Filter algorithms without the aid of any feedback information, and a comparison is made between the two. Both the algorithms are perceptive to follow the actual torque; the error between the actual and reference is used for the selection of appropriate voltage vector for inverter switching. The reflection of load changes in the control algorithm is also a part of the interest in this work. The potential of Extended Kalman Filter to follow exactly the changes in the load torque is utilized here and Extended Kalman Filter based sensorless drive is proposed for the torque estimation in Direct Torque Controlled BLDC motor. The performance parameters, viz. computational effort, torque ripple reduction are found to be superior with the Extended Kalman Filter algorithm, which is validated.

本文描述了使用卡尔曼滤波器和扩展卡尔曼滤波器的直接转矩控制 BLDC 电机驱动的转矩估计。在传统的直接扭矩控制方法中，扭矩估计是基于位置信息完成的，这又需要位置传感器来进行准确估计。本文采用卡尔曼滤波器和扩展卡尔曼滤波器算法直接估计转矩，不借助任何反馈信息，并对两者进行比较。这两种算法都能感知到跟随实际扭矩；实际值和参考值之间的误差用于选择合适的逆变器切换电压矢量。控制算法中负载变化的反映也是这项工作的兴趣的一部分。这里利用了扩展卡尔曼滤波器精确跟踪负载转矩变化的潜力，并提出了基于扩展卡尔曼滤波器的无传感器驱动，用于直接转矩控制 BLDC 电机的转矩估计。性能参数，即。计算工作量，发现使用扩展卡尔曼滤波器算法更好地降低扭矩纹波，该算法经过验证。