A linear optimization approach for electric vehicles charging

Recently, electric vehicles (EVs) are qualified to be one of the indispensable solutions for green transport and environmental challenges. As the number of EVs sold steadily increases in the automobile market, charging infrastructures should be further developed and sophisticated. Reducing charging times of EVs is one of the major challenges for public charging stations. This challenge can be met by increasing the rate of power transferred to the EVs. However, there are other methods proposed in the literature for reducing charging times while ensuring maximum charging rates. In this paper, we propose an optimization algorithm in order to assign optimally and adequately a fleet of EVs to charging stations. This approach provides a solution to both minimize the energy consumption by EVs while reaching adequate charging stations. Each EV assignment takes into account the constraints of vehicles, charging stations and the traffic situation on the roads. With the proposed solution we keep the in-vehicle battery state of charge (SOC) to its highest level (maximum level) when reaching its destination. Consequently, this charging approach allows to reduce charging times and therefore reduce the time spent within charging stations.

[1]  Tao Wang,et al.  Energy-aware Vehicle Routing in Networks with Charging Nodes , 2014, 1401.6478.

[2]  Pascal Lorenz,et al.  Wireless communication technologies for ITS applications [Topics in Automotive Networking] , 2010, IEEE Communications Magazine.

[3]  Kevin Tanguy Modélisation et optimisation de la recharge bidirectionnelle de véhicules électriques : application à la régulation électrique d'un complexe immobilier , 2013 .

[4]  Stuart E. Dreyfus,et al.  An Appraisal of Some Shortest-Path Algorithms , 1969, Oper. Res..

[5]  Dirk Uwe Sauer,et al.  Optimizing vehicle-to-grid charging strategies using genetic algorithms under the consideration of battery aging , 2011, 2011 IEEE Vehicle Power and Propulsion Conference.

[6]  J. Gaber,et al.  Towards an optimal assignment and scheduling for charging electric vehicles , 2013, 2013 International Renewable and Sustainable Energy Conference (IRSEC).

[7]  M. Becherif,et al.  Design and sizing of a stand-alone recharging point for battery electrical vehicles using photovoltaic energy , 2011, 2011 IEEE Vehicle Power and Propulsion Conference.

[8]  Guillaume Leduc,et al.  Plug-in Hybrid and Battery-Electric Vehicles: State of the research and development and comparative analysis of energy and cost efficiency , 2009 .

[9]  Q. Meng,et al.  Analysis of Traffic Speed-Density Regression Models-A Case Study of Two Roadway Traffic Flows in China , 2013 .

[10]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[11]  Ahmed Nait-Sidi-Moh,et al.  TransportML platform for collaborative location-based services , 2012, Service Oriented Computing and Applications.

[12]  Richard Bellman,et al.  ON A ROUTING PROBLEM , 1958 .

[13]  Nicanor Quijano,et al.  Optimal Routing and Scheduling of Charge for Electric Vehicles: Case Study , 2013, ArXiv.

[14]  Alexis Kwasinski,et al.  A rapid charging station with an ultracapacitor energy storage system for plug-in electrical vehicles , 2010, 2010 International Conference on Electrical Machines and Systems.

[15]  Christopher L. Decker,et al.  Electric Vehicle Charging and Routing Management via Multi-Infrastructure Data Fusion , 2012 .

[16]  Stanton W. Hadley,et al.  Impact of Plug-in Hybrid Vehicles on the Electric Grid , 2006 .

[17]  Ahmed Nait-Sidi-Moh,et al.  Geopositioning and Mobility: Nait-Sidi-Moh/Geopositioning and Mobility , 2013 .

[18]  Ling Guan,et al.  Optimal Scheduling for Charging and Discharging of Electric Vehicles , 2012, IEEE Transactions on Smart Grid.