Enhanced EV Battery Monitoring Using IoT with Improved SEPIC - ZETA Converter and Modified Lion Optimization for Photovoltaic Systems

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R. Ramani, A. Nalini

Abstract

The rising popularity of electric vehicles (EVs) and the increasing emphasis on sustainable transportation have highlighted the importance of advanced monitoring systems. These systems play a crucial role in providing real-time information about battery parameters to ensure optimal performance and longevity. Moreover, the integration of renewable energy sources, specifically photovoltaic (PV) systems, with EV charging infrastructure presents an exciting prospect to enhance energy efficiency and minimize environmental harm. As a consequence the proposed work develops an Internet of Things (IoT) based PV fed EV charging system. The system incorporates an improved SEPIC-Zeta converter together with Modified Lion Optimization algorithm (LOA) assisted Proportional Integral (PI) controller for optimizing PV system for charging EV battery. IoT connectivity monitors parameter such as PV voltage, PV current, and State of Charge (SOC) of battery. Real-time monitoring of these parameters is achieved by leveraging sensors. The collected data is transmitted through IoT networks to a central monitoring system, enabling operators to track the performance of PV system and EV battery. This facilitates optimized energy generation, efficient battery charging and discharging, and overall system reliability. IoT-enabled monitoring system provides remote accessibility, data analytics, and the generation of alerts and notifications for timely actions. Experimental validation demonstrates that, the proposed concept enhances the monitoring capabilities, improves energy efficiency, and ensures reliable operation of EV charging infrastructure.

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