Performance Evaluation of Maximum Power Point Algorithms for Annulling the Effect of Irradiance and Temperature for Standalone Electric Vehicle Charger

Abstract

The study presented in this paper deals with the evaluation of maximum power point tracking (MPPT) algorithms to nullify the effect of varying irradiance and temperature inputs given to the solar photovoltaic (PV) powered standalone electric vehicle (EV) chargers. Three different MPPT algorithms, namely perturb and observe (PO), particle swarm optimization (PSO), and cuckoo search (CA) algorithm, are designed and the settling time to reach steady-state by overcoming the effect of variable irradiance and temperature along with partial shading is analyzed. In this analysis, four different conditions are introduced: constant irradiation and constant temperature, which is an ideal case followed by change in irradiation with constant temperature, constant irradiance with temperature change, and finally, both varying irradiance and temperature. Among the algorithms, the CA algorithm tracks to the maximum power of 19.9kW, 12.8kW, 12.3kW, and 19.42kW respectively for all conditions. The analysis confirmed that the CA algorithm remains superior with 24%, 67%, 79%, and 40% of a maximum power compared to others by achieving the steady state at 0.2 seconds.