Optimizing charging battery efficiency in partially shaded PV systems with enhanced particle swarm optimization using dual-core DSP microcontroller in EV applications

Abstract

This paper presents the development of an intelligent battery charging system for electric vehicle (EV) charging stations, incorporating a Photovoltaic (PV) system with a buck converter to improve power transfer efficiency in partial shade scenarios. The intrinsic unpredictability of solar irradiation causes changes in photovoltaic output power, requiring an intelligent optimization strategy. The study utilizes an Enhanced Particle Swarm Optimization (E-PSO) algorithm, a stochastic search method, to optimize power extraction and enhance overall system performance. The DSP F28379D microcontroller is employed for real-time execution, producing high-frequency pulse-width modulation (PWM) signals for accurate regulation of the buck converter. Experimental validation confirms the enhanced performance of the proposed E-PSO algorithm, with a response time of 0.04 s and an efficacy of 99.90%, markedly decreasing charging duration and improving power output relative to traditional MPPT techniques. These findings highlight the effectiveness and feasibility of the proposed method for efficient and adaptive electric vehicle battery charging in variable operating conditions.