Maximum Power Point Tracking Improvement in Electric Vehicles Using HPSOGSA Algorithm

Electric Vehicles (EVs) are gradually becoming the essential part of our daily life. Due to fast depletion of the fossil fuels like petroleum and diesel and also increasing concentration of pollutants in the atmosphere, EV is widely serving as an alternate of these fossil fuels. Many electric vehicles, solar powered cars or hybrid vehicles obtain the input from a solar PV panel. To store the energy, some energy storage device is vital that can store the surplus energy during production, and then transfer this excess energy during deficit. To serve this purpose, battery is considered as a major element for an electrical vehicle. But these batteries can damage due to overcharging by a solar panel. So, to safeguard the battery from any sort of damage because of overcharging, some sort of intelligent or smart battery management system is necessary. In the present research work, a smart battery management system based on fuzzy logic is proposed. This system is supported by the solar PV panels that can provide the faster charging to the electrical vehicles, protecting the battery life from the overcharging, and enhancing the life of battery by utilizing the optimum power from the battery. To achieve this improvement of maximum power point tracking (MPPT) is necessary in solar PV panels. Present research work includes an HPSOGSA algorithm that is a hybrid system of two most proficient (PSO & GSA) algorithms for improving MPPT in solar PV systems. Various parameters such as rise time, settle time, peak time, overshoot, under shoot, irradiance, battery voltage (Vbat), and state of charge (SOC), are used for comparing the results of two particular controllers (PID & FOPID) for the suggested HPSOGSA system.