Experimental Implementation of a Stand-Alone Photovoltaic Smart Traffic Light System with MPPT and Battery Charge Management

Renewable energy sources have been widely utilized in many applications worldwide in recent years, particularly to support sustainable and energy-efficient systems. One of the most vital applications of these sources is the photovoltaic (PV) traffic light system (TF-LS), which represents a sustainable alternative to conventional grid-powered traffic infrastructure. This paper presents the design and experimental implementation of a stand-alone PV TF-LS, consisting of a PV power system and an integrated TF-LS that operate autonomously while ensuring reliable and efficient energy utilization. The proposed control of the PV power system accomplishes two main functions: maximum power point tracking (MPPT) of the PV module and battery charging management. The MPPT system is implemented using a perturb and observe (P&O)-based PI algorithm with reduced step size and is experimentally validated using a dSPACE 1104 real-time control platform. In addition, this paper proposes and experimentally implements a novel intelligent control strategy for the TF-Ls that relies on vehicle counting and real-time comparison of traffic densities at road intersections instead of the traditional fixed-time scheduling approach, using LabVIEW software and an Arduino microcontroller. Experimental results demonstrate the effectiveness of the proposed control techniques for MPPT, battery charging, and traffic signal operation. Moreover, the proposed TF-LS control demonstrates fast and efficient operation under real-time traffic conditions, providing a simple and practical solution for mitigating traffic congestion.

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Publication Details

Journal
Sustainability
Published
2026-02-13
DOI
https://doi.org/10.3390/su18041959
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
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article

Experimental Implementation of a Stand-Alone Photovoltaic Smart Traffic Light System with MPPT and Battery Charge Management

Abd El-Fattah A. Omran, Yousef Ha, Faten Hosny Fahmy, Abd El-Shafy A. Nafeh
Sustainability
Vehicle emissions and performance
article

Experimental Implementation of a Stand-Alone Photovoltaic Smart Traffic Light System with MPPT and Battery Charge Management

Abd El-Fattah A. Omran, Yousef Ha, Faten Hosny Fahmy, Abd El-Shafy A. Nafeh
article en

Abstract

Renewable energy sources have been widely utilized in many applications worldwide in recent years, particularly to support sustainable and energy-efficient systems. One of the most vital applications of these sources is the photovoltaic (PV) traffic light system (TF-LS), which represents a sustainable alternative to conventional grid-powered traffic infrastructure. This paper presents the design and experimental implementation of a stand-alone PV TF-LS, consisting of a PV power system and an integrated TF-LS that operate autonomously while ensuring reliable and efficient energy utilization. The proposed control of the PV power system accomplishes two main functions: maximum power point tracking (MPPT) of the PV module and battery charging management. The MPPT system is implemented using a perturb and observe (P&O)-based PI algorithm with reduced step size and is experimentally validated using a dSPACE 1104 real-time control platform. In addition, this paper proposes and experimentally implements a novel intelligent control strategy for the TF-Ls that relies on vehicle counting and real-time comparison of traffic densities at road intersections instead of the traditional fixed-time scheduling approach, using LabVIEW software and an Arduino microcontroller. Experimental results demonstrate the effectiveness of the proposed control techniques for MPPT, battery charging, and traffic signal operation. Moreover, the proposed TF-LS control demonstrates fast and efficient operation under real-time traffic conditions, providing a simple and practical solution for mitigating traffic congestion.

SustainabilityVol. 18(4)
Cairo University (EG), Electronics Research Institute (EG)
Industry, innovation and infrastructure
Openalex Percentile: Top 57%
Vehicle emissions and performance
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