Predict Energy Charging Points to Electric Vehicles in a Smart City Using a Novel Metaheuristic

Abstract

The purpose of this research is to understand from a Multivariable optimization associated with the path of a group of vehicles integrated in an Ecological Community and determine the optimal route involve speed, storage and travel resources including time of charge for determining the cost benefit have partnered with a travel plan associated with the charge point in a Smart City, which has as principal basis the orography restriction related with the energy consume, although this problem has been studied on several occasions by the literature failed to establish by supporting ubiquitous computing for interacting with the various values associated with the achievement of the group of vehicles and their cost-benefit of each member of the community and comparing their individual trips for the group and determine the quantity of energy which requires each one. There are several factors that can influence in the achievement of a group trip, for our research we propose to use Bat Algorithm on, which has proven to be efficient for the convergence of several issues (artificial bats) when they have such restrictions and obstacles should use this energy to avoid in our case, a gain resource as food which in our case is represented as the use of food optimally for the duration of a long trip with the uncertainty of not knowing when you have a resupply of energy considering a Considering a useful life of between 8 and 10 hours depending of the use and load in weight of the electric vehicle.