Model Based Route Guidance for Hybrid and Electric Vehicles
Model Based Route Guidance for Hybrid and Electric Vehicles
复制标题
基于模型的混合动力和电动汽车路线引导
DOI：
10.1109/itsc.2015.280
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
G. Inalhan
中科院分区：
文献类型：
--
作者：
C. Kurtulus;G. Inalhan
混合动力汽车和电动汽车在过去几年中获得了巨大的吸引力，这就需要进一步关注它们的独特特性。本文说明了一种基于模型的方法来引导路线，其中的车辆和动力系统的模型被用来计算弧成本的道路网络的经典导航成本函数（即时间，距离）和新的适应电动汽车，如能源使用，电池磨损。还应注意，用于路线引导的最短路径问题的标准解决方案，即Dijkstra算法，由于电气化车辆的独特方面而不能应用于该问题，并且另一算法，即Bellman-福特-摩尔算法，必须在最短路径问题的该应用的解决方案中使用。这是由于Dijkstra算法所需的非负边缘成本条件不适用于具有再生制动能力的电动车辆。此外，还有人认为，只有在路线引导和电源管理协调工作的情况下，才能实现电动汽车的最有效运行，从而充分利用电气化带来的额外自由度。最后，这种新的方法进行路线引导的比较，经典的方法，它表明，加权复合成本函数，考虑到经典的，新引入的参数生成的路线是有效的，也取得了很好的平衡的旅行时间。
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.