An eco-friendly path guidance algorithm for electric vehicle

At present, the automobile industry’s interest in eco-friendly electric vehicles is increasing and those vehicles are replacing vehicles using traditional fossil fuels. This study considers how to drive an electric vehicle with maximum efficiency depending on the terrain. Since electric vehicles have poor climbing ability, they have a limitation in that battery efficiency and it decreases when driving on the road with a steep slope. As the speed decreases and the driving distance becomes shorter, it reveals weaknesses on steep roads. In order to overcome this risk, the optimal route was searched using spatial information data. The slope of each link is derived by analyzing 3D spatial information data including geographic and geospatial elements. Since the efficiency of electric vehicles varies depending on the slope, the degree of reduction in the speed of the electric vehicle according to the slope and length of the link is analyzed. The weight for each link is given and applied to the following function. In general, in the transportation field, the BPR function, which is one of the types of VDF, is used to optimize the route and classify the shortest path. However, the slope of the road is not reflected in the current function. By adding a slope-related variable to this, a new VDF system and network are built by constructing a new form of functional formula that includes the speed-reduction weights. By using a* algorithm, the shortest path algorithm, to the constructed network, the path to the destination to be reached is optimized and implemented. Finally, a real-time route guidance system can be built based on this, and route information can be provided to with electric vehicle driver. As a result of the assignment to the traffic route, it was confirmed that there is a significant difference compared to the shortest route assigned simply by distance. In addition, the effectiveness was verified through comparative analysis of the total travel time difference and energy efficiency of the two methods. By applying this algorithm, it was confirmed that the efficiency of use of the electric vehicle was improved. The energy efficiency when performing the route search considering the terrain is about 1.794 higher than when performing a simple route search. The proposed approach helps to achieve the goal of efficient transportation and ultimately promotes green transportation.