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Induction motor control for high efficiency and power factor
Faculty
Engineering
Year:
2004
Type of Publication:
Theses
Pages:
94
Authors:
Adel EL Shahat Lotfy
BibID
10608037
Keywords :
Motors
Abstract:
Induction motors are the most widely used motors for appliances,industrial control, and automation. i.e. many electric loads are primarilyinduction motors. Hence they are often called the prime workhorse of theindustry motion. They are robust, reliable, and durable. Motors consumemore than 50 % of the total energy generated. For this reason it isimportant to optimize the efficiency of motor drive systems if significantenergy savings are to be obtained. The induction motor (IM), especiallythe squirrel - cage type, is widely used in electrical drives and isresponsible for most of the energy consumed by electric motors.The induction motor losses can be classified as follows:Stator copper losses.Rotor copper losses.Iron losses.. Stray losses.• Mechanical (friction + windage) losses.The main losses, are copper (stator + rotor) and iron losses. The focusof this research is to minimize these losses or maximizing the efficiency,that achieves a proper suitable deal of power factor improvement. Theconcept of energy saving has always been an attention grabber, especiallywhen the promised savings are high and the potential for a reduction inrunning costs appears high. It is experienced that, the induction motor atfractional loads, is an inherently inefficient device, because its efficiency falls at light loads. So the aim here is to improve the efficiency especially at light loads. Some words should be putted into our consideration that, Only energy that is being wasted could be saved.In this research, it is hopeful to give a point of view on efficiencyoptimization problem and so the power factor improvement. By usingsensorless speed control of I.M. Because controlled induction motordrives without mechanical speed sensors at the motor shaft have theattractions of low cost and high reliability. To replace the sensor, theinformation on the rotor speed is extracted from measured stator voltagesand currents at the motor terminals. The artificial neural networks areused here to achieve goals of this research.
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