Mathematical Modeling of Mitsumi M36N-4E DC Motor and Fujita ML7122 AC Motor for Control System Optimization

Abstract

Mathematical modeling of electric motors often faces challenges in accuracy and complexity, especially when integrating dynamic parameters such as torque, speed, and resistance. This research aims to develop mathematical models for Mitsumi M36N-4E DC motor and Fujita ML7122 AC motor to predict performance and design more efficient control systems. Contributions (1) DC and AC motor modeling without manual feature extraction, (2) Robust training scheme against orientation variation, (3) Simple CNN architecture for fast computation, (4) Datasheet-based parameter validation. Laplace transform and transfer function are used to model the motor dynamics, with validation through MATLAB/Simulink simulation. The model accuracy reached 96.8% ±1.87% for DC motor and 70% efficiency for AC motor. The transient response of the DC motor shows an overshoot of 1.7-1.8× the steady-state value, while the AC motor has a slip of 5%. The model is effective for real-time control applications and can be implemented in embedded systems.