Design and analysis of trans Z-source inverter for electric vehicle applications using neural network-clustering

Abstract

The presented paper analyzes the detailed design of a trans Z-source inverter (ZSI) with an input from solar photovoltaic (SPV) system. Increase in SPV uses requires highly efficient SPV enabled inverters under varying weather parameters are in high demand in modern smart grid applications. The SPV-trans ZSI has high conversion efficiency because of the single-stage voltage boost conversion capability. In contradiction, the conventional voltage source inverter (VSI) requires an additional step-up transformer to boost the output voltage of inverter. This reduces the efficiency by increasing the volume of set up and also increase the cost of the system. In the proposed SPV system it provides a better output against VSI. The increase in inverter output voltage is because of shoot through time period present in ZSI. It also reduces the voltage stress and harmonics content as compared to VSI. The proposed model has been validated through MATLAB simulation.