Direct Torque Control with Space Vector Modulation (DTC-SVM) of ...
Direct Torque Control with Space Vector Modulation (DTC-SVM) of ...
Direct Torque Control with Space Vector Modulation (DTC-SVM) of ...
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Sensorless Speed <strong>Direct</strong> <strong>Torque</strong> <strong>Control</strong> <strong>with</strong> <strong>Space</strong> <strong>Vector</strong> <strong>Modulation</strong> (<strong>DTC</strong>-<strong>SVM</strong>)<br />
Where lim is the limited value. Please note that lim should be set at reference stator<br />
flux amplitude<br />
lim =Ψ<br />
s _ ref<br />
equal Ψ<br />
PM<br />
.<br />
From Eq. 6.18 it can be observed that when one <strong>of</strong> the stator flux linkage components<br />
Ψ<br />
sα<br />
or Ψ<br />
sβ<br />
exceeds the limit, it causes in distortion <strong>of</strong> the output waveform.<br />
6.4 Electromagnetic torque estimation<br />
The PMSM motor output torque is calculated based on the equations (2.51), (2.52),<br />
(2.55), (2.58) presented in Chapter 2, which for stator oriented coordinate system can be<br />
written as follows:<br />
3<br />
M<br />
e<br />
= pb( Ψs αIsβ −Ψ<br />
sβIsα<br />
)<br />
(6.19)<br />
2<br />
It can be seen that calculated torque is dependent on the current measurement accuracy<br />
and stator flux estimation method. In practice current measurement is performed <strong>with</strong><br />
high accuracy ( ≤ 1% <strong>with</strong> 150kHz frequency bandwidth) using, for example, LEM<br />
sensors.<br />
6.5 Rotor speed estimation methods<br />
6.5.1 Overview<br />
High performance operation <strong>of</strong> motion sensorless PMSM drives depends mainly on<br />
accurate knowledge <strong>of</strong> rotor PM flux magnitude, position and speed. The rotor position<br />
estimation methods can be classified into two major groups:<br />
• motor model based,<br />
• rotor saliency based techniques.<br />
The rotor saliency based approach is suitable only for the Interior PMSM (see Fig. 1.2 c<br />
and d). Motor model based approach detect the back EMF vector, which includes<br />
information about position and speed, using either open loop models/estimators<br />
[81,85,86] or closed loop estimators/observers [70, 73,74,96,97,100]. Also adaptive<br />
observers [72,92,98,83] and Extended Kalman Filters (EKF) [67,73] have been<br />
proposed for motor position and speed estimation. These methods, however, are<br />
computationally intensive and require careful design and proper initialization.<br />
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