Speed Adjustable System Of Wound-Rotor Induction Motor With IGBT Chopper Controlled Resistance In Rotor Circuit

Wound-rotor induction motors are used in a large amount of cranes in our country, and are controlled in discrete steps and open loop. These equipments are not suitable in some areas nowadays. So their reforming has become quite urgent. In some cases, rotor resistance chopper control scheme is economic and efficient. The thyristor- chopper control scheme has already been investigated thoroughly. This paper probes into the rotor resistance IGBT chopper control system for the induction motor to follow the development of modern power electronics. The IGBT-controlled chopper circuit can be greatly simplified as the smoothing inductor and commutation circuit of the thyristor-controlled chopper circuit are no more required. In this paper a novel chopper circuit consisting only four elements: one IGBT, one diode, one resistor and one electrolytic capacitor is presented. Experiments and simulation have shown that the circuit can not only adjust the resistance in the rotor circuit efficiently, but also absorb the spikes across IGBT when the switch is turned off, and the turn-off track of IGBT can be improved a lot. The equivalent circuit of the motor with this circuit has been analyzed in detail, and the nonlinear mapping between the equivalent resistance and the duty cycle is deduced. The value of the resistor and capacitor can be determined according to the design method given in the paper so that the specified speed ratio can beachieved and the power spikes across IGBT when it is turned-off can be weakened or avoided. In our system, the stator voltage control is also applied as a secondary strategy, so that the motor can also run at low speeds with light load. The practical calculation method of the stator voltage has also been introduced.In order to simulate the above system with old version of PSPICE, we have investigated the identification of model parameters of IGBT composite model in this software, and BP neural network has been applied. With the help of neural network, the steady-state behavior related parameters of IGBT can be acquired quite easily.During the training of the BP network in this application, we have observed that there exist a large amount of local minimal points. We have developed an unproved adaptive variable step gradient (IAVSG) algorithm, so that the net can jump out of the local minimums more efficiently, and the convergence speed can be greatly increased.