Parameter identification of a DC motor: an experimental approach

The main goal of this paper is to estimate the parameters of a DC motor experimentally employing discrete measurements of an integrated dynamometer. The parameters under consideration are the motor armature-winding resistance and inductance, back e.m.f. constant, motor torque constant, moment of inertia, and the viscous friction. The dynamometer outputs are the discrete measurements of the armature current, angular velocity, armature voltage (system input), and the torque developed by the motor. In this paper parameter identification of a DC motor, employing the least-squares algorithm, is implemented without the use of a D/A converter and a power amplifier. In particular, the armature voltage is generated using a prime mover and a synchronous generator. The data acquisition system is composed of the existing dynamometer data acquisition coupled with special software resulting in collecting different measurements automatically at a desired fixed time interval. A Kalman filter is also implemented, as a state observer, to estimate the angular acceleration and the derivative of the armature current. In addition, to improve the overall identification performance, the DC parameters were first estimated by decoupling the AC parameters using a DC input signal. Subsequently, the estimated DC parameters are then used to identify the AC parameters. Experimental results are included to illustrate the efficiency of the proposed system