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Energy Saving ?


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#1 jamco23

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Posted 17 October 2006 - 07:00 PM

Some drive manufacturer's are quoting energy savings by using Flux optimisation on VSD's and quoting 10 15 % energy saving by using this function and hence save money can this be true. Also installing newer drives be 20 - 30 % more efficent ?

Anyone done any studies in this area ?


#2 marke

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Posted 17 October 2006 - 09:49 PM

Hello jamco23

10 - 15% of what? I am not a fan of these percentage savings that get quoted unless they are well qualified.
If you use flux optimisation, you will reduce the iron loss in the motor. This will equate to some savings, but the amount can be quite small relative to the rated power of the motor. The bottom line is just how much iron loss is there in your particular motor. Small motors have a higher iron loss per KW motor rating than large motors.
It is common for large motors to have a full load efficiency in the order of 95%, which leaves 5% losses made up of iron loss, copper loss and windage losses. Typically, the iron loss will be in the order of 30 - 50% of the total losses at full load, so that gives you an indication of the potential saving, a portion of a couple of percent of the motor rating when the motor is operating at light load.

Newer drives can certainly be more efficient than some of the older drives.

Best regards,

#3 jOmega

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Posted 20 October 2006 - 07:11 PM

"In many applications Induction Motor drives work below the nominal torque most of the time. In these circumstances the IM efficiency can be improved lowering the flux. For a given torque, this decreases iron looses and increases copper losses. With appropriate algorithms an optimum point for the flux can be achieved in order to minimize IM total power losses. Using an IM model, a neural network (NN) based approach is used to improve efficiency in a vector control of the induction motor drive. A complex loss model of the motor, including magnetic and thermal deviations of its parameters, is used to estimate losses. Based on this model, the neural network is trained to estimate the optimum rotor flux. Inputs to the NN are torque, speed and rotor resistance of the IM and the output is the rotor flux."







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