Design and Analysis of ANN MPPT System in Switching Capacitor-Based MLI for Electric Vehicles

The abstract outlines a research endeavor focused on enhancing Multilevel Inverters (MLIs) for electric vehicles (EVs) and solar photovoltaic (PV) applications. Specifically, it introduces a 53-level MLI design tailored for EVs, leveraging a Switched Capacitor (SC) technique. In this design, the number of SC cells dictates the MLI’s level count, offering simplicity in implementation. With fewer active switches, driving circuits are reduced, leading to cost, size, and device count reductions in the MLI. Additionally, the research incorporates a Maximum Power Point Tracking system based on Artificial Neural Networks (ANN) (MPPT) a Single Input Multiple Output (SIMO) converter and a mechanism. Together, these components increase the DC link voltage with the aid of solar panels, providing a constant DC output voltage and reducing the Total Harmonic Distortion, or THD, in the MLI’s output voltage. The approach of the study entails building a MATLAB simulation model, which is expected to evaluate the performance of the suggested system and confirm that it is effective in accomplishing the stated goals. This research aims to contribute to the advancement of MLI technology for EVs and solar PV systems, emphasizing efficiency, simplicity, and performance optimization.