Hybrid approach for optimizing energy of smart electric vehicle and finding the optimal charging station

Abstract

In the near future, the electric vehicle (EV) will be the most used in the word. Thus, the energy management of its battery and finding the optimal charging station when the battery will be in low-level are the most attractive subject specialty in the last decade. Thus, if a driver uses an electric vehicle, he wants to find an optimal method that can optimize the energy battery of its electric vehicle. Also, he wants to know where can find the optimal charging station according to its location on the road, charging time and the energy amount demanded, when the energy level of the battery will be very low. In this paper, we propose a new concept of the smart electric vehicle (SEV) that can manage, control and optimize the energy of its battery, in condition to satisfy the drivers’ and passengers’ comfort and then, it can rapidly find the charging station when the energy level of the battery will be very low according to the distance, the amount of energy demanded and the charging time. Thus, we use hybrid approach that based on the multi-agent system and the genetic algorithm (MAS-GA).