No abstract

No abstract

In the coming years, the number of electric vehicles (EVs) is going to increase, while the charging network might not be adequately expanded at the required time. It is very likely that there will be feedback effects within the power grid in form of capacity bottlenecks. This might result in reduced charging power for a higher number of electric vehicles in order to counteract fluctuations. In this paper, the authors describe a management system for electric vehicles that optimizes the allocation of charging processes on motorways. The designed system aims to optimize travel and charging times while reducing waiting times for electric vehicles in intercity transport. by considering respective charging capacities, it may be able to reduce feedback effects with the energy system. The management system uses data from the charging stations, electric vehicles and their planned route. This allows the system to forward relevant information regarding expected energy demand to the power grid. consequently, vehicles periodically communicate their position, battery level and their remaining way to destination to the management system, which returns charging advice for the optimal charging station. by using an optimization algorithm, the scarce resource of the charging stations is efficiently allocated to the vehicles. In order to examine its efficiency, a model of the management system with reduced features is transferred into a simulation. The simulation study follows an academic approach and takes different penetration rates of electric vehicles into account. A heuristic approach led to a solution with reasonable complexity, i.e. polynomial running time. In comparison, an analytical solution was outlined which describes the optimal case. This simulation study shows that the proposed system manages the waiting times efficiently by smartly assigning the vehicles to the corresponding charging stations.

The project MAVEN (see https://www.maven-ts.eu), funded by the European Com- mission, aims at developing a system for infrastructure-assisted platoon organization and green phase negotiation for automated connected vehicles (ACVs). Vehicle-to-Everything (V2X) communication protocols are hereby used for the insertion of vehicles into a traffic simulation of a real-world intersection. Until now, real world traffic could be inserted into a simulation through stationary detectors, for example magnet field sensors, induction loops, cameras, radar etc. The downside of this detection method is that only momentary information can be obtained and e.g. the behavior of the vehicles approaching an intersection can only be approximated. ACVs however continuously broadcast their positions and speeds via CAMs. Detecting vehicles though these messages leads to a more realistic representation of the vehicle’s driving behavior. The current paper describes how CAMs are used to place and move ACVs inside the simulation of a real-world intersection in Braunschweig with the traffic simulation SUMO (Simulation of Urban Mobility). Furthermore, it describes an approach to how these continuously detected vehicles could be further used as control units. Since the positions and speeds of ACVs are synchronized with the real-world behavior, they can be used to adjust the simulated upstream movements and positioning of conventional vehicles (CV) to match reality. Until all vehicles are equipped with V2X technology, this approach could enable more realistic simulated traffic flow behavior.