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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 />

132

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