Efficient Energy-Optimal Routing for Electric Vehicles

Traditionally routing has focused on finding shortest paths in networks with positive, static edge costs representing the distance between two nodes. Energy-optimal routing for electric vehicles creates novel algorithmic challenges, as simply understanding edge costs as energy values and applying standard algorithms does not work. First, edge costs can be negative due to recuperation, excluding Dijkstra-like algorithms. Second, edge costs may depend on parameters such as vehicle weight only known at query time, ruling out existing preprocessing techniques. Third, considering battery capacity limitations implies that the cost of a path is no longer just the sum of its edge costs. This paper shows how these challenges can be met within the framework of A* search. We show how the specific domain gives rise to a consistent heuristic function yielding an O(n2) routing algorithm. Moreover, we show how battery constraints can be treated by dynamically adapting edge costs and hence can be handled in the same way as parameters given at query time, without increasing run-time complexity. Experimental results with real road networks and vehicle data demonstrate the advantages of our solution

Exploring particle swarm optimization to build a dynamic charging electric vehicle routing algorithm

Electric vehicle (EV) limited range is a serious concern for its wide scale commercialization. Dynamic battery charging is being developed as a promising technology for increasing the range, vehicles are charged through inductive points placed in the net. The choice of a proper navigation route becomes essential, and algorithms must be identified for a run time identification of the better path. In this paper, we propose and explore the application of the particle swarm optimization (PSO) algorithm to solve the problem of energy efficient routing problem for inductive dynamic charging EVs. The paper presents the results obtained in a simple simulation of a road network with 11 dynamic charging inductive lanes