Implementation of a neural velocity estimator in a three phase induction motor
The three phase induction motor is the most used type of machine for electric drives. Low cost, construction simplicity and reliability are the motives that explains this statement. Nowadays, this motor is also highlighting for it's applicability in the automotive area, with the electric vehicle ascension which, besides being a economic alternative to fuel consumption compared to ordinary vehicle, are also a solution for the emission of polluting gases to the environment. From this scenario, the objective of this work is to perform the speed control of an induction motor without the use of a mechanical sensor attached to the rotor, avoiding some inconveniences such as a periodic maintenance and increased complexity and number of equipment are always part of the engine running. For the induction motor control was applied the control strategy known as Field Oriented Control and for the estimation of the motor rotor speed was used an artificial neural network, which observer electrical and mechanical system variables. The practical results were satisfatory, since the neural network worked as both observer and speed estimation and it was possible to perform the control os the motor with the estimated speed in the range of 100 to 170 rad/s.