The aim of this study was to design three-phase induction motors with aluminum and copper cage, in the range 0.75 ÷22 kW, to fulfill the 1E3 efficiency level according to typical performance and standard constrai...The aim of this study was to design three-phase induction motors with aluminum and copper cage, in the range 0.75 ÷22 kW, to fulfill the 1E3 efficiency level according to typical performance and standard constraints. The proposed study has concerned TEFC （ totally Enclosed Fan-Cooled ）, 400 V, 50 Hz, SI duty three phase squirrel-cage induction motors only. The motors＇ designs, with AI and Cu cage, have been optimized in order to reach the minimum efficiency level IE3 at lowest active material costs and satisfy the physical and performance constraints of the designs, which are the motor specifications. A suitable optimization procedure has been used which allowed to find the ＂best design＂ by chancing the geometric dimensions of the stator, rotor shape, the stator winding and the stack length. In order to guarantee the goodness and feasibility of the optimized designs, several constrains have been imposed.展开更多
In this paper, it presents a project of a fuzzy controller and a neural estimator to control a coordinate table powered by three-phase induction motor, aiming to implement an intelligent milling system. The position/s...In this paper, it presents a project of a fuzzy controller and a neural estimator to control a coordinate table powered by three-phase induction motor, aiming to implement an intelligent milling system. The position/speed control is performed using vector techniques of three-phase induction machines. The estimation of the motor electromagnetic torque is used for setting the feedrate of the table. The speed control is developed using TS （Takagi-Sugeno） fuzzy logic model and electromagnetic torque estimation using neural network type LMS （least mean square） algorithm. The induction motor is powered by a frequency inverter driven by a DSP （digital signal processor）. Control strategies are implemented in DSP. Simulation results are presented for evaluating the performance of the system.展开更多
文摘The aim of this study was to design three-phase induction motors with aluminum and copper cage, in the range 0.75 ÷22 kW, to fulfill the 1E3 efficiency level according to typical performance and standard constraints. The proposed study has concerned TEFC （ totally Enclosed Fan-Cooled ）, 400 V, 50 Hz, SI duty three phase squirrel-cage induction motors only. The motors＇ designs, with AI and Cu cage, have been optimized in order to reach the minimum efficiency level IE3 at lowest active material costs and satisfy the physical and performance constraints of the designs, which are the motor specifications. A suitable optimization procedure has been used which allowed to find the ＂best design＂ by chancing the geometric dimensions of the stator, rotor shape, the stator winding and the stack length. In order to guarantee the goodness and feasibility of the optimized designs, several constrains have been imposed.
文摘In this paper, it presents a project of a fuzzy controller and a neural estimator to control a coordinate table powered by three-phase induction motor, aiming to implement an intelligent milling system. The position/speed control is performed using vector techniques of three-phase induction machines. The estimation of the motor electromagnetic torque is used for setting the feedrate of the table. The speed control is developed using TS （Takagi-Sugeno） fuzzy logic model and electromagnetic torque estimation using neural network type LMS （least mean square） algorithm. The induction motor is powered by a frequency inverter driven by a DSP （digital signal processor）. Control strategies are implemented in DSP. Simulation results are presented for evaluating the performance of the system.
