Parameter Identification and Block Diagram Reduction of DC054B-6 Motor in Electric Control System Application

Abstract

This study presents a comprehensive mathematical modeling and simulation of two electric motors commonly used in industrial and educational applications: the PITTMAN TYPE DC054B-6 brushed DC motor and the FUJITA TYPE ML7112 single-phase AC motor. The objective is to derive accurate dynamic models that reflect the electrical and mechanical behavior of each motor, facilitating the analysis and design of control systems. The modeling process begins with the identification of motor parameters, including resistance, inductance, back EMF constant, torque constant, moment of inertia, and damping coefficient, sourced from datasheets and estimated through standard motor modeling techniques. The dynamic equations are formulated using Kirchhoff’s Voltage Law for electrical dynamics and Newton’s Second Law for mechanical motion. These equations are then transformed into the Laplace domain to derive transfer functions that relate input voltage to angular velocity. To validate the mathematical models, simulations are carried out in MATLAB/Simulink for both motors under open-loop and closed-loop configurations. A proportional controller is introduced in the feedback loop to improve performance and stability. The results show that the second-order DC motor model exhibits underdamped behavior in open-loop form but demonstrates significantly improved rise time and settling time in closed-loop control. Meanwhile, the AC motor, modeled as a simplified first-order system, responds more slowly but provides acceptable performance for applications with less dynamic requirements. The simulation results confirm the accuracy and reliability of the developed models for control system design. The models serve as a foundation for implementing more advanced control strategies such as PID or adaptive control. This work contributes to the development of digital simulation techniques and embedded control systems, especially in the context of marine electrical and automation engineering.