Electric car path optimal seeking method considering range and charging station position
A technology for electric vehicles and charging stations, applied in navigation, measuring devices, surveying and navigation, etc., can solve problems such as difficulty in finding the optimal solution by algorithm, long calculation time, etc.
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Embodiment
[0045] In this embodiment, the electric vehicles are divided into four categories according to the current state of the electric vehicles.
[0046] Consider the attributes of potential charging stations in the route, including slow charging stations and fast charging stations, and distinguish them by the method of charging efficiency difference.
[0047] According to the classification of electric vehicles, the optimal path search methods for four types of electric vehicles are given respectively.
[0048] The best route search idea for electric vehicle auxiliary route is:
[0049] The electric vehicle auxiliary route refers to a feasible electric vehicle driving route scheme, on which the electric vehicle can ensure that the electric vehicle can be charged in time before the power is exhausted so as to reach the destination smoothly. Therefore, the main idea of the present invention is to first search for potential electric vehicle charging stations that can be charged, an...
Embodiment 2
[0124] It is basically the same as Embodiment 1, except that, in step 4, when the electric vehicle reaches the destination, the remaining power of the electric vehicle is:
[0125] BL A =BL F -D(SCS j , Des) / EM;
[0126] If the total driving distance is selected for sorting, calculate the driving route with the shortest total driving distance, select all the routes with the shortest difference from the total driving distance within the threshold, and use the route with the highest remaining power of the electric vehicle as the automatic selection route;
[0127] If the total travel time is selected for sorting, the route with the shortest total travel time is calculated, and all routes whose difference from the total travel distance time is within the threshold are selected, and the route with the highest remaining battery capacity of the electric vehicle is automatically selected.
Embodiment 3
[0129] It is basically the same as Embodiment 2, except that in step 4, if the user selects the most economical travel route in step 4, the preset weight value is added to the total travel distance and the total travel time respectively, and the total The driving distance is multiplied by the weight value and the total driving time is multiplied by the weight value and then added to obtain the total value for sorting, and the route with the highest total value is used as the automatically selected route.
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