An Optimized PV-Based Multi-Port Plug-In EV Charger Using Improved Particle Swarm Optimization Algorithm

In order to significantly improve the factor power and State of Charge, we proposed a design of Particle Swarm Optimization (PSO) with Maximum Power Point Tracking (MPPT) and control the Pulse Width Modulation (PWM) by PI controller that improves performance and reduces losses than other two existing works such as PV grid system designed with PI controller and P&O with MPPT and Fuzzy control-based PV grid system for EV charging. Here, the proposed PSO technique is improved by adding frequency scaling. The photovoltaic (PV) controlling, maximum power tracking and pulse generation are improving the result by adopting Improved Particle Swarm Optimization (IPSO). Multi-port charging station utilizes battery. After, getting the voltage link DC, the grid utilization is fed with the inverter logic. Here, the multi-port charger with PV and convertor boost DC-DC is directly interfaced with the electric vehicles (EV) charging port; additionally, the battery stores the energy. Depends on the utility grid, the energy is utilized. Thus, the proposed method attains the result of efficient multi-port utility, improved percentage of State of Charge (SoC), and better switching circuit with PFC and larger load utility. Overall, the proposed work is done in the 2018a version that adaptation with MATLAB/Simulink.