Brushless DC Motor Speed-Current Dual Closed-Loop Simulation

This project implements a comprehensive brushless DC motor (BLDC) simulation with dual closed-loop control for speed and current regulation. The simulation architecture employs custom-developed models for both the three-phase inverter and motor dynamics, achieving high numerical accuracy through discrete-time modeling with appropriate sampling rates. The phase current output demonstrates ideal square waveform characteristics, validated through Fourier analysis of the simulated results.

Brushless DC motors represent a key technology in modern electromechanical systems, widely deployed in electric vehicles, UAV propulsion, and industrial robotics. Their operation leverages electronic commutation via Hall-effect sensors or sensorless algorithms, replacing traditional mechanical brushes with semiconductor switching. This design ensures superior efficiency (typically 85-95%), extended operational lifespan, and minimal maintenance requirements compared to brushed counterparts.

The simulation implements a cascaded control structure where the outer speed loop generates current references for the inner current regulation loop. The inverter module utilizes space vector PWM (SVPWM) techniques to synthesize three-phase voltages with programmable amplitude and frequency. The motor model incorporates mathematical representations of electromagnetic torque production, back-EMF generation with trapezoidal waveform profiles, and dynamic equations governing mechanical rotation. Key parameters including rotor inertia, winding inductance, and permanent magnet flux linkage are configurable through model parameterization.

This simulation framework enables detailed analysis of transient responses during acceleration/deceleration scenarios, torque ripple minimization strategies, and stability assessment under varying load conditions. The modular design facilitates integration with hardware-in-the-loop (HIL) testing environments for controller validation and performance optimization across diverse application requirements.