Simulink Implementation of Two-Level Inverter Using Space Vector PWM (SVPWM)

Simulink serves as a powerful simulation and modeling platform developed by MathWorks, extensively utilized across industries for designing and analyzing complex dynamic systems. A two-level inverter represents a fundamental power electronic converter that transforms DC input power into AC output with two distinct voltage levels. This configuration finds widespread application in motor drives, renewable energy systems (such as solar and wind power conversion), and electric vehicle charging infrastructure. Space Vector Pulse Width Modulation (SVPWM) constitutes an advanced switching technique that optimizes inverter performance by controlling power semiconductor devices (typically IGBTs or MOSFETs) to generate high-quality sinusoidal output waveforms with improved voltage utilization and reduced harmonic distortion. In Simulink implementation, the SVPWM algorithm involves several key computational stages: sector identification based on reference voltage vector components, dwelling time calculation using trigonometric transformations, and switching sequence generation with proper null vector distribution. The model typically incorporates Clarke/Park transformations to convert three-phase quantities into stationary (αβ) and rotating (dq) reference frames, enabling precise voltage vector synthesis. Engineers can simulate switching patterns using PWM Generator blocks configured with carrier-based comparison or custom S-function implementations for sector-based logic. Through Simulink simulation of a two-level SVPWM inverter, professionals can evaluate critical parameters including total harmonic distortion (THD), switching losses, dynamic response under load variations, and DC-link voltage utilization. The modeling approach facilitates waveform analysis through Scope blocks and performance quantification via MATLAB Function blocks integrating FFT analysis and efficiency calculations. This integrated workflow supports system optimization through modulation index adjustments, dead-time compensation implementation, and closed-loop control strategy validation for real-time deployment.