Implementation of Advanced SVPWM Control Algorithms for Switch State Management in a Multilevel Cascaded Inverter within an Electric Traction Chain

Abstract

This paper presents the development of advanced Space Vector Pulse Width Modulation (SVPWM) algorithms based on newly formulated mathematical models, aimed at controlling the switching states of multilevel cascaded inverters. The proposed control scheme introduces a generalized layer-based decomposition methodology with any number of levels n. By leveraging this hierarchical framework, the method achieves a substantial reduction in Total Harmonic Distortion (THD), lowering it from approximately 50% to below 10%, and ensuring the generation of high-quality, near-sinusoidal output waveforms. These algorithms are integrated into an electric traction system powered by photovoltaic energy sources. The actuator used in this chain is an induction motor controlled in a vector manner. The layered structure allows the systematic identification of all possible vectors per layer, the determination of redundant vectors, and the classification of distinct and equivalent switching states across the entire modulation space. A dedicated coding system assigns a unique identifier to each vector, allowing efficient tracking of corresponding redundant vectors on the layers. This redundancy management framework improves modulation flexibility and allows a transition between equivalent states. Moreover, the process of decomposition of a global reference voltage into its multilevel components is addressed by the analytical determination of amplitudes and transition angles. This contributes to a computationally efficient, modular modulation structure that significantly reduces implementation complexity and enables real-time application. The proposed algorithms have been validated by complete simulations in the MATLAB/Simulink environment. The results demonstrate superior performance in terms of output waveform quality, harmonic suppression, and switching loss reduction, highlighting the appropriateness of the approach for high-efficiency traction systems based on renewable energies.