Review on Ant Colony Optimization and Partial Swarm Optimization Based Harmonic Elimination Method in Multilevel Inverters for EV Applications

In this study, we use ant colony optimisation (ACO) to determine the output of an optimisation approach for precise harmonic rejection in a cascaded multilevel inverter (MLI). The most crucial idea in these harmonics elimination plans is to eliminate normal level harmonics by equating non-symmetric variables and to proceed with a normal solution, where larger levels of various components are satisfied, to a position inside a specific area paper. To this end, one side of the paper examines the impact of optimal DC sources, while the other side examines contrast optimisation techniques. By using this technique, the CBO, a recently developed universe-influenced algorithm, is subjected to the genetic based algorithm (GA), the harmonic search algorithm (HS), the artificially developed bee colony algorithm (ABC), the partial swarm optimisation algorithm (PSO), the imperialized competitive algorithm (ICA), the ant colony optimisation method (ACO), and others. The experiment is set up is constructed and developed for a 9-level H-bridge inverter using analysed DC input something is obtained. For good distinguish in these methods an impact of optimum DC method is taken under consideration using 3-, 7-, and 15-levels inverters.