Energy Management of a Solar Electric Vehicle Equipped with Two-Energy Storages via Optimized Fuzzy Controller by Genetic Algorithm

Abstract

The optimum energy management is the main challenge of powered Electric Vehicles (EVs) with multiple energy storage systems. The solar powered EVs is enabled with multiple energy sources and storages, and so, achieving the optimum energy management schedule is a complicated optimization problem. This paper develops an optimized fuzzy controller using genetic algorithm (GA) for energy management of solar powered EV equipped with Photovoltaic cells as well as two power banks including battery and super-capacitor. Design of fuzzy controllers relies too much on the expert experience and non-optimal design may lead to sub-optimal performance. To overcome this complexity, genetic algorithm (GA) is employed to optimally determine Fuzzy rules and membership functions. The proposed approach is modeled in ADVISOR software. Standard driving cycle is used to simulate the proposed approach. Simulation results demonstrate the decrease on consumed power by the proposed optimal GA-Fuzzy controller in comparison with the standard fuzzy controller.