A method for identification of parameters of a non-linear dynamic system, such as an induction motor with saturation effect taken into account, is presented in this paper. Adaptive identifier with structure similar to model of the system performs identification. This identifier can be regarded as a special neural network, therefore its adaptation is based on the gradient descent method and Back-Propagation well known in the neural networks theory. Parameters of electromagnetic subsystems were derived from the values of synaptic weights of the estimator after its adaptation. Testing was performed with simulations taking into account noise in measured quantities. Deviations of identified parameters in case of electrical parameters of the system were up to 1% of real values. Parameters of non-linear magnetizing curve were identified with deviations up to 6% of real values. Identifier was able to follow sudden changes of rotor resistance, load torque and moment of inertia.
The first part of this article introduces formulas for dimension of motor-size in the case in which an electrical machine replaces the combustion engine. There were shortly described various types of electrical drives that can be applied to drive electrical cars: DC machine, brushless DC machine and induction motor. There are derived differential equations both of electric and mechanic part of the system. As a result of simulation that was performed using MATLAB/SIMULINK there are compared two alternative time-responses of acceleration: with an automatic controlled gearbox and with a manual operation. There were simulated motor-current, battery-current, angular speed of the motor and speed of the car during acceleration. and Obsahuje seznam literatury