This paper deals with a dynamic estimator for fully automated parameters indentification of permanent magnet three-phase synchronous motors. High performance application of permanent magnet synchronous motors (PMSM) is increasing. PMSM models with accurate parameters are significant not only for precise control system designs but also in traction applications. Acquisition of these parameters during motor operations is a challenging task due to the inherent nonlinearity of motor dynamics. This paper proposes parameters estimator technique for PMSMs. The technique uses a decoupling procedure optimized by a minimum variance error to estimate the inductance and resistance of the motor. Moreover, a dynamic estimator is shown. The estimator uses the measurements of input voltage, current and mechanical angular velocity of the motor, the estimated winding inductance, and resistance to identify the amplitude of the linkage flux. The presented technique is generally applicable and could be used also for the estimation of mechanical load and for other types of electrical motors, as well as for other dynamic systems with nonlinear model structure. Through simulations of a synchronous motor used in automotive applications, this paper verifies the effectiveness of the proposed method in identification of PMSM model parameters and discusses the limits of the found theoretical and the simulation results.