5 Introduction of operation and running SV800/SV800A User Manual
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5.3 Induction motors parameters self-learning
The mathematical model of the motor needs to be built when the induction motor is under
vector control mode. The relevant parameters of the motor in the mathematical model can be
automatically obtained by motor parameters self-learning .Thus it must perform motor
parameters self-learning or input the motor parameters manually when vector control mode
selected in the frequency inverter.
5.3.1 Induction motor parameters self-learning method and procedure
The self-learning of induction motor mainly includes full-mode self-learning and direct-current
mode self-learning. Full-mode self-learning algorithm detects all electrical constants required
for driving the motor. The direct-current mode self-learning algorithm just detects the primary
side resistance of the motor and the frequency inverter nonlinear parameters, etc.
We tested all the frequency inverter well before send the frequency inverter to the customers. As
the characteristic of the driven motor cannot be predicted after leaving the factory, the user
needs to perform motor parameters self-learning after the frequency inverter is connected with
the motor in the first time. The self-learning procedure as shown in Fig.5-9; When the motor
types changes (including, but is not limited to power, voltage, current, rotational speed,
frequency) during the use of the frequency inverter, the self-learning needs to be performed
again as shown in Fig.5-9; If the carrier frequency changes during the controlling the debugging
process, the static mode self-learning needs to be performed at least and the procedure as shown
in
Fig.5-9.
