Solar EV Charging with Zeta Topology

Abstract

Electric vehicles are rapidly emerging as a sustainable transportation solution; however, conventional grid-based charging systems increase electricity demand and contribute to carbon emissions. Solar photovoltaic energy offers a clean and renewable alternative for EV charging. The output of photovoltaic systems is highly dependent on solar irradiance and temperature, which leads to fluctuations in voltage and power generation. In order to improve energy extraction efficiency, a solar photovoltaic charging system using a ZETA DC–DC converter integrated with a Maximum Power Point Tracking algorithm is presented. The ZETA converter operates in both buck and boost modes while maintaining a non-inverted output voltage suitable for battery charging. A PIC microcontroller implements the MPPT control algorithm and monitors battery parameters such as state of charge, state of health, and charging duration. Real-time system parameters are displayed through an LCD and transmitted to the ThingSpeak cloud platform using an ESP8266 Wi-Fi module for remote monitoring. The proposed system is modeled and simulated using MATLAB/Simulink to evaluate voltage regulation, output ripple, and charging performance. Simulation results demonstrate efficient power extraction, improved voltage stability, and enhanced charging performance under varying solar conditions. The system promotes environmentally friendly transportation while reducing dependence on conventional grid power.

Introduction

The text presents a solar-powered charging system designed to improve renewable energy efficiency, especially for applications like electric vehicles. Solar photovoltaic (PV) panels generate electricity, but their output fluctuates ???? environmental factors such as sunlight, temperature, and shading, reducing efficiency.

To solve this, the system uses Maximum Power Point Tracking (MPPT)—specifically the Perturb and Observe (P&O) method—to ensure the solar panel always operates at its optimal power point. A ZETA DC–DC converter is used to regulate voltage efficiently, offering both step-up and step-down capabilities while maintaining stable, non-inverted output and continuous current flow.

The proposed system integrates a PIC microcontroller to implement the MPPT algorithm and control the converter via PWM signals. It also includes battery monitoring features such as State of Charge (SOC) and State of Health (SOH). An IoT-based monitoring system using the ESP8266 module enables real-time data transmission (voltage, current, battery status) to a cloud platform for remote access and analysis.

The system architecture combines PV generation, power conversion, battery storage, embedded control, and cloud connectivity. Simulation using MATLAB/Simulink demonstrates effective voltage regulation, improved power extraction, and stable battery charging under varying conditions.

Overall, the system provides an efficient, intelligent, and scalable solution for solar energy management, enhancing energy utilization, battery performance, and remote monitoring capabilities.

Conclusion

A solar power based maximum power point tracking system using a ZETA converter provides an efficient solution for renewable energy based battery charging applications. The integration of the ZETA converter enables both step-up and step-down voltage conversion while maintaining a non-inverted output voltage suitable for stable battery charging. Implementation of the MPPT algorithm through a PIC microcontroller ensures that the photovoltaic system continuously operates at its maximum power point under varying environmental conditions. The incorporation of IoT technology using an ESP8266 Wi-Fi module enables real-time monitoring and visualization of system parameters through the ThingSpeak cloud platform. Simulation and hardware implementation demonstrate that the proposed system improves energy extraction efficiency, enhances battery performance, and enables intelligent monitoring of renewable energy systems. The combination of photovoltaic energy conversion, efficient power regulation, and cloud-based supervision makes the system suitable for modern smart renewable energy applications and sustainable energy management systems.

References

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Copyright

Copyright © 2026 Anandhu E, Asim Ali , Jeslyn Sara Sam, Niranjan Rajeev, Prof. Jessy Thomas , Dr. Sija Gopinathan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.