Design and performance evaluation of multilevel inverter for solar energy systems and electric vehicle charging with multi output active clamp forward converter

This paper addresses the challenges of achieving efficient and high-quality power conversion in solar energy systems and electric vehicle (EV) charging applications by introducing a Multi-Output Active Clamp Forward Converter (MOACFC). The proposed system is designed to generate symmetrical and asymmetrical DC voltage configurations for a Multilevel Inverter (MLI) topology. Traditional MLI topologies often require numerous switches and DC sources, leading to increased complexity and reduced efficiency. To overcome these limitations, the MOACFC delivers multiple output voltages from a single solar generation input, effectively reducing the number of switches and DC sources required. This study also highlights the application of a Recurrent Neural Network Incremental Conductance (RNN-INC)-based Maximum Power Point Tracking (MPPT) algorithm to optimize power extraction from photovoltaic (PV) arrays. The MLI system’s fundamental module can produce 9-level, 21-level, and 31-level outputs, with the Nearest Level Control Pulse Width Modulation (NLCPWM) and Level Shifted Pulse Width Modulation (LSPWM) techniques employed to minimize Total Harmonic Distortion (THD). The results demonstrate significant improvements in power quality, with THD levels reduced to 3.77% in voltage and 0.99% in current for EV charging applications – substantially better than conventional 2-level and 3-level inverters. The findings indicate that the proposed MOACFC-MLI system is a more efficient and reliable alternative, offering enhanced power quality and reduced electrical stress on EV battery systems.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-11-21
DOI
https://doi.org/10.2516/stet/2024084/pdf
Primary Topic
Genomics and Phylogenetic Studies
Type
article
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article

Design and performance evaluation of multilevel inverter for solar energy systems and electric vehicle charging with multi output active clamp forward converter

Springer Link (Chiba Institute of Technology)
Genomics and Phylogenetic Studies
article

Design and performance evaluation of multilevel inverter for solar energy systems and electric vehicle charging with multi output active clamp forward converter

article en

Abstract

This paper addresses the challenges of achieving efficient and high-quality power conversion in solar energy systems and electric vehicle (EV) charging applications by introducing a Multi-Output Active Clamp Forward Converter (MOACFC). The proposed system is designed to generate symmetrical and asymmetrical DC voltage configurations for a Multilevel Inverter (MLI) topology. Traditional MLI topologies often require numerous switches and DC sources, leading to increased complexity and reduced efficiency. To overcome these limitations, the MOACFC delivers multiple output voltages from a single solar generation input, effectively reducing the number of switches and DC sources required. This study also highlights the application of a Recurrent Neural Network Incremental Conductance (RNN-INC)-based Maximum Power Point Tracking (MPPT) algorithm to optimize power extraction from photovoltaic (PV) arrays. The MLI system’s fundamental module can produce 9-level, 21-level, and 31-level outputs, with the Nearest Level Control Pulse Width Modulation (NLCPWM) and Level Shifted Pulse Width Modulation (LSPWM) techniques employed to minimize Total Harmonic Distortion (THD). The results demonstrate significant improvements in power quality, with THD levels reduced to 3.77% in voltage and 0.99% in current for EV charging applications – substantially better than conventional 2-level and 3-level inverters. The findings indicate that the proposed MOACFC-MLI system is a more efficient and reliable alternative, offering enhanced power quality and reduced electrical stress on EV battery systems.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 68%
Genomics and Phylogenetic Studies
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