Smart navigation system for electric vehicles charging

Abstract

In the present time, there is still a lack of popularity in the use of electric vehicles, because of the actual disadvantages that they have. For this work presents the process of research and development of a web based application with the main purpose of helping Electric Vehicle owners decide the Charging Station that, by selecting it to go and charge their vehicles, represents the lowest cost in time or money (depending on their priorities) when they need to go to charge their electric vehicles and to give them less time or energy consuming route to follow in order to arrive to the charging station selected. This, to reduce the concern of the users about if the can or not arrive to a charging station.

To do this, the application has been developed with several features to help the users. First, the application has the feature of being accessed from multiple type of devices. Second, the application has the feature of detecting the users locations using Global Positioning System. Third, the application has the ability to find the charging stations and their coordinates that are near to the users. Fourth, the application has the ability to formulate the route with the lowest time or energy cost between the users locations and the charging stations. Fifth, after creating all the routes, the application shows the users the parameters of every route and charging station. Sixth, the application has the ability to let the users decide the priority to select the charging station. Seventh, the application let the users decide the battery percentage that they want their vehicles to have after charging them.

This application was created using mostly Javascript language, Expressjs as the framework and for the user interface jQuery. Moreover, MongoDB and PosgreSQL were used as databases. Furthermore, some web services like Amazon Web Services were used for server hosting, OpenStreetMap for obtaining GeoSpatial data, Open Charging Map for obtaining charging stations coordinates and data and Fuel Economy for obtaining vehicles data were used to complement the application. For the route formulation, Dijkstra's algorithm and pgRouting was used.

Results indicated that the application can successfully recommend routes and charging stations to the users with a reduction of 90 of time needed against the less time consuming cheapest option when time is the priority and a reduction of 27 times the money needed for the fastest option when price is the priority. Meaning that the navigation system can successfully reduce the time or costs to adjust to the users necessities.