Model Based Route Guidance for Hybrid and Electric Vehicles

Hybrid and electric vehicles have been gaining significant traction in the past few years, and this necessitates that further attention should be given to their unique characteristics. This paper illustrates a model based approach to route guidance, where a model of the vehicle and the powertrain is utilized to calculate arc costs of a road network in terms of classical navigation cost functions (i.e. time, distance) and new ones adapted to electrified vehicles, such as energy use, and battery wear. It is also noted that the standard solution for the shortest path problem used for route guidance, i.e. Dijkstra's algorithm, cannot be applied to this problem due to the unique aspects of electrified vehicles, and another algorithm, namely Bellman-Ford-Moore, has to be utilized in the solution of this application of the shortest path problem. This is due to the fact that the condition of non-negative edge costs required by Dijkstra's algorithm does not hold for electrified vehicles which have regenerative braking capability. Moreover, it is also argued that most efficient operation of an electrified vehicle can only be achieved if route guidance and power management work in harmony, so that the best use of additional degrees of freedom enabled by electrification can be fully exploited. Finally, a comparison of this new method for route guidance to classical methods is carried out, and it is demonstrated that a weighted composite cost function that takes into account both classical, and newly introduced parameters generate a route that is efficient, and that also strikes a good balance in terms of travel time.