Constrained MPPT based control of a photovoltaic DC to DC conversion system using a non inverting buck boost converter

Abstract This paper presents a Constrained Maximum Power Point Tracking Algorithm (CMPPTA) integrated with a Non Inverting Buck Boost Converter (NIBBC) for photovoltaic (PV) energy conversion. Unlike conventional Perturb and Observe (P&O) methods, CMPPTA uses a constrained duty-cycle update law with adaptive bounded perturbation, saturation enforcement, and a local hold region near the maximum power point (MPP). The duty cycle is limited to $$D_{\\min }=0.1$$ and $$D_{\\max }=0.9$$ , with practical operation mainly within 50–60%. The controller is implemented on an ARM Cortex-M4 STM32F407VGT6 microcontroller and validated through MATLAB/Simulink simulation and laboratory hardware testing. The simulation uses a 200 W equivalent PV array, while the prototype uses a single 40 W PV module. Under 300–1000 W/m $$^2$$ simulation, CMPPTA achieves 96.63% peak DC conversion efficiency. Under 270–1000 W/m $$^2$$ laboratory testing, hardware efficiency reaches 84.48%. CMPPTA reduces cumulative tracking error by 18.7% relative to IC and 24.1% relative to P&O. The present validation is limited to MPPT execution and DC–DC converter operation; outdoor testing, partial shading, temperature variation, storage integration, and inverter-level validation remain future work. Accordingly, the reported results validate the proposed controller at the MPPT and DC–DC converter levels only, and should not be interpreted as full-system validation of storage, inverter, grid-interface, or application-side load operation.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-09-15
DOI
https://doi.org/10.1038/s41598-026-71613-z
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Constrained MPPT based control of a photovoltaic DC to DC conversion system using a non inverting buck boost converter

Ruby Beniwal, Shruti Kalra, Narendra Singh Beniwal, K. Nisha et al.
Scientific Reports
Photovoltaic System Optimization Techniques
article

Constrained MPPT based control of a photovoltaic DC to DC conversion system using a non inverting buck boost converter

Ruby Beniwal, Shruti Kalra, Narendra Singh Beniwal, K. Nisha, Maninder Singh, Vinay Singh
article en

Abstract

Abstract This paper presents a Constrained Maximum Power Point Tracking Algorithm (CMPPTA) integrated with a Non Inverting Buck Boost Converter (NIBBC) for photovoltaic (PV) energy conversion. Unlike conventional Perturb and Observe (P&O) methods, CMPPTA uses a constrained duty-cycle update law with adaptive bounded perturbation, saturation enforcement, and a local hold region near the maximum power point (MPP). The duty cycle is limited to $$D_{\min }=0.1$$ and $$D_{\max }=0.9$$ , with practical operation mainly within 50–60%. The controller is implemented on an ARM Cortex-M4 STM32F407VGT6 microcontroller and validated through MATLAB/Simulink simulation and laboratory hardware testing. The simulation uses a 200 W equivalent PV array, while the prototype uses a single 40 W PV module. Under 300–1000 W/m $$^2$$ simulation, CMPPTA achieves 96.63% peak DC conversion efficiency. Under 270–1000 W/m $$^2$$ laboratory testing, hardware efficiency reaches 84.48%. CMPPTA reduces cumulative tracking error by 18.7% relative to IC and 24.1% relative to P&O. The present validation is limited to MPPT execution and DC–DC converter operation; outdoor testing, partial shading, temperature variation, storage integration, and inverter-level validation remain future work. Accordingly, the reported results validate the proposed controller at the MPPT and DC–DC converter levels only, and should not be interpreted as full-system validation of storage, inverter, grid-interface, or application-side load operation.

Scientific Reports
Jaypee Institute of Information Technology (IN), Bundelkhand University (IN), Symbiosis International University (IN)
Affordable and clean energy
Openalex Percentile: Top 30%
Photovoltaic System Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.