A route planning method for battery replacement of food delivery vehicles

Abstract

The present invention discloses a route planning method for battery replacement of a takeaway vehicle, which belongs to the technical field of route planning, and specifically comprises: obtaining target electric vehicle passing nodes in a target area and sorting them to obtain a node sequence; matching a target battery swap station for each passing node according to battery swap station information, generating a corresponding battery swap route and calculating the mileage; obtaining the battery status of the electric vehicle and calculating the remaining mileage L', and if the mileage Li of any battery swap route is less than or equal to L'*(1-α), then retaining the battery swap route; calculating the pending score of each battery swap station, obtaining the reference scores of other electric vehicles at battery swap station i and the amount of spare batteries M of battery swap station i, and correcting the pending score of the target electric vehicle corresponding to the target battery swap station i to obtain a preferred score; selecting the reserved battery swap route corresponding to the battery swap station with the highest preferred score, and pushing the reserved battery swap route to the target electric vehicle. The present invention improves the battery replacement efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of route planning, and in particular to a route planning method for replacing batteries of a takeaway vehicle. Background Art

[0002] Electric vehicles are an important tool for food delivery riders to carry out their delivery work, and the battery life of electric vehicles directly affects the delivery efficiency of food delivery riders.

[0003] At present, some food delivery platforms have set up fixed battery swap stations for riders. Riders need to monitor the battery power themselves and look for a battery swap station when they find that the battery power is low, or they can replace the battery at a fixed battery swap station. Although this model can guarantee the delivery needs of food delivery riders to a certain extent, due to the seasonal fluctuations in the order volume of the food delivery industry, especially during peak periods, the battery of the electric vehicles of food delivery riders is consumed at a faster rate, resulting in greater pressure on the battery swap station. In this case, the rider may face the difficulty of not being able to find a battery swap station where the battery can be replaced, and thus fail to complete the delivery task in time, affecting the on-time delivery of customer orders.

[0004] This happens because the matching mechanism between riders and battery swap stations is not fully optimized, and there is a lack of effective prediction and management of peak hours, which results in riders having limited choices of battery swap stations in terms of time and space during peak demand periods, thus affecting delivery efficiency. Therefore, an intelligent route planning method for battery swapping of food delivery vehicles is urgently needed to solve this problem. Summary of the invention

[0005] The purpose of the present invention is to provide a route planning method for battery replacement of a takeaway vehicle to solve the following technical problems:

[0006] This happens because the matching mechanism between riders and battery swap stations is not fully optimized, and there is a lack of effective prediction and management of peak hours, which results in riders having limited choices of battery swap stations in terms of time and space during peak demand periods, thus affecting delivery efficiency. Therefore, an intelligent route planning method for battery swapping of food delivery vehicles is urgently needed to solve this problem.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A method for route planning for battery replacement of a takeaway vehicle, characterized in that it comprises the following steps:

[0009] S1, obtain the order, location and expected driving route information of any target electric vehicle in the target area, determine the passing nodes according to the order and sort them according to the expected route, and obtain the passing node sequence Y1, Y2, ..., Yn;

[0010] S2, obtain the information of the battery swap station in the target area to determine that all the passing nodes correspond to the target battery swap station and mark them as H1, H2, ..., Hn, generate the battery swap route between the target electric vehicle and any target battery swap station and mark them as D1, D2, ..., Dn; obtain the current battery status information of the target electric vehicle to filter all the battery swap routes, obtain all the retained battery swap routes and mark them as D1, D2, ..., Dm; according to the calculation formula The pending score of any target battery swap station is calculated, where hi is the number of reserved battery swap routes corresponding to the i-th target battery swap station, and m is the total number of reserved battery swap routes;

[0011] S3, repeat S1 and S2, obtain the pending scores of other electric vehicles in the target area at battery swap station i as reference scores, obtain the backup battery capacity M of battery swap station i, correct the pending score of the target electric vehicle corresponding to the target battery swap station i according to the backup battery capacity M and the reference score, obtain the preferred score Q, select the battery swap route corresponding to the target battery swap station with the highest preferred score, and push the route to the target electric vehicle.

[0012] As a further solution of the present invention: In S2, the process of determining the target battery swap station is as follows:

[0013] All battery swap stations with a backup battery level greater than zero are screened out from the battery swap station information and marked as pending battery swap stations. Any passing node is taken as the starting point, and the Dijkstra algorithm is used to obtain the shortest path from the starting point to all pending battery swap stations. The driving distances of all shortest paths are obtained and the battery swap station corresponding to the shortest path with the shortest driving distance is calibrated as the target battery swap station corresponding to the passing node.

[0014] As a further solution of the present invention: In S2, the specific generation process of the switching route is:

[0015] Select any transit node Ya and obtain the target battery swap station Ha corresponding to the transit node Ya, take the target battery swap station Ha as the adjacent next transit node of the transit node, obtain the planned transit sequence Y1, Y2, ..., Ya, Ha, and generate a battery swap route according to the planned transit sequence.

[0016] As a further solution of the present invention: the specific acquisition process of switching route screening is as follows:

[0017] The remaining power of the target electric vehicle is extracted from the battery status information, and the vehicle parameter data of the electric vehicle information is obtained; the remaining mileage L' of the target electric vehicle is calculated according to the remaining power and the vehicle parameter data, and the mileage of any power conversion route is calculated in turn and marked as L1, L2, ..., Ln. If there is any power conversion route with a mileage Li less than or equal to L'*(1-α), the power conversion route is retained, wherein α is a preset safety factor.

[0018] As a further solution of the present invention: in S3, the specific calculation process of the preferred score is:

[0019] ;

[0020] Among them, E is the total number of other electric vehicles in the target area, Csi is the reference score of the sth other electric vehicle corresponding to the battery swap station i, and ε is the preset unit coefficient.

[0021] As a further solution of the present invention: if there is no battery swap station i among the target battery swap stations corresponding to any other electric vehicle, the reference score of the electric vehicle at the battery swap station i is marked as 0.

[0022] As a further solution of the present invention: in S3, if there are two or more target battery swap stations whose preferred scores are all maximum values, the number of reserved battery swap routes corresponding to any target battery swap station is obtained, and the target battery swap station with the largest number of reserved battery swap routes is selected as the optimal target battery swap station.

[0023] As a further solution of the present invention: it also includes obtaining all reserved power switching routes corresponding to the optimal target power switching station and marking them as d1, d2, ..., dv, calculating the road condition score of any reserved power switching route according to the calculation formula W=μ*Ki*Gi, selecting the reserved power switching route with the smallest road condition score as the optimal route and pushing it to the target electric vehicle, wherein μ is a preset correction coefficient, Ki is the number of traffic lights corresponding to any reserved planned route, and Gi is the number of turns required for the reserved power switching route.

[0024] Beneficial effects of the present invention:

[0025] By obtaining the order information, positioning information and expected driving route of the target electric vehicle, all passing nodes can be accurately determined and effectively sorted according to these nodes. It is understandable that in real life, the platform will use intelligent algorithms to dispatch orders of one or more customers to riders. The riders need to pick up the goods from various merchants first and then deliver them one by one. Therefore, the address of each customer and merchant is a passing point of the initial planned route. By obtaining the information of all battery swap stations in the target area, and determining the target battery swap station corresponding to any passing node based on this information, a battery swap route between the target electric vehicle and any target battery swap station is generated. By obtaining the current battery status information of the target electric vehicle in real time and calculating the remaining mileage, the battery swap route that meets actual needs can be dynamically adjusted according to actual conditions, and by calculating the pending score of each battery swap station, it is understandable that battery swap routes that meet actual needs may exist. There are more than one, and the probability of each battery swap route being selected by the user is equal. In the actual process, there may be multiple optimal battery swap stations corresponding to the same node along the way. Therefore, the initial pending score of each battery swap station can be determined. It can be understood that the pending score is the probability that the battery swap station is selected by the rider. The larger the pending score, the higher the probability of being selected. However, there will be other riders swapping batteries in the area, and the amount of backup batteries at each battery swap station is limited. The pending score is corrected by considering the backup battery amount and the reference score of the battery swap station. By combining the backup battery amount and the usage of other electric vehicles, the battery swap station suitable for the current electric vehicle needs can be accurately selected, and the reserved battery swap route corresponding to the battery swap station can be sent to the target electric vehicle, thereby achieving a more reasonable allocation of battery swap station resources, avoiding some battery swap stations from being unable to provide services due to resource constraints, and improving battery replacement efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention will be further described below in conjunction with the accompanying drawings.

[0027] Figure 1 It is a schematic flow chart of a route planning method for replacing batteries of a takeaway vehicle according to the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figure 1 As shown, the present invention is a route planning method for replacing batteries of a takeaway vehicle, comprising the following steps:

[0030] S1, obtaining order information, positioning information and expected driving route of any target electric vehicle in the target area, determining all passing nodes according to the order information, and sorting all passing nodes according to the expected planned route to obtain a passing node sequence Y1, Y2, ..., Yn;

[0031] S2, obtaining information of all battery swap stations in the target area, determining the target battery swap station corresponding to any passing node according to the battery swap station information, obtaining the target battery swap stations corresponding to all passing nodes and marking them as H1, H2, ..., Hn, generating a battery swap route between the target electric vehicle and any target battery swap station and marking them as D1, D2, ..., Dn, calculating the mileage of any battery swap route in turn and marking them as L1, L2, ..., Ln;

[0032] Obtain the current battery status information of the target electric vehicle and calculate the remaining mileage L' of the target electric vehicle. If the mileage Li of any battery swapping route is less than or equal to L'*(1-α), then the battery swapping route is retained, and all retained battery swapping routes are obtained and marked as D1, D2, ..., Dm; obtain the target battery swapping station i corresponding to any retained battery swapping route and calculate it according to the calculation formula The pending score of the battery swap station is calculated, and the pending scores of all battery swap stations are obtained, where α is the preset safety factor, hi is the number of reserved battery swap routes corresponding to the i-th battery swap station, and m is the total number of reserved battery swap routes;

[0033] S3, repeat S1 and S2, obtain the pending scores of other electric vehicles in the target area at the corresponding battery swap station i and mark them as reference scores, obtain the backup battery capacity M of the target battery swap station i, and correct the pending score of the target electric vehicle corresponding to the target battery swap station i according to the backup battery capacity M and the reference score to obtain the preferred score Q, and then obtain the preferred score of the target electric vehicle corresponding to all target battery swap stations, select the reserved battery swap route corresponding to the target battery swap station with the largest preferred score, and push the reserved battery swap route to the target electric vehicle.

[0034] By obtaining the order information, positioning information and expected driving route of the target electric vehicle, all passing nodes can be accurately determined and effectively sorted according to these nodes. It is understandable that in real life, the platform will use intelligent algorithms to dispatch orders of one or more customers to riders. The riders need to pick up the goods from various merchants first and then deliver them one by one. Therefore, the address of each customer and merchant is a passing point of the initial planned route. By obtaining the information of all battery swap stations in the target area, and determining the target battery swap station corresponding to any passing node based on this information, a battery swap route between the target electric vehicle and any target battery swap station is generated. By obtaining the current battery status information of the target electric vehicle in real time and calculating the remaining mileage, the battery swap route that meets actual needs can be dynamically adjusted according to actual conditions, and by calculating the pending score of each battery swap station, it is understandable that battery swap routes that meet actual needs may exist. There are more than one, and the probability of each battery swap route being selected by the user is equal. In the actual process, there may be multiple optimal battery swap stations corresponding to the same node along the way. Therefore, the initial pending score of each battery swap station can be determined. It can be understood that the pending score is the probability that the battery swap station is selected by the rider. The larger the pending score, the higher the probability of being selected. However, there will be other riders swapping batteries in the area, and the amount of backup batteries at each battery swap station is limited. The pending score is corrected by considering the backup battery amount and the reference score of the battery swap station. By combining the backup battery amount and the usage of other electric vehicles, the battery swap station suitable for the current electric vehicle needs can be accurately selected, and the reserved battery swap route corresponding to the battery swap station can be sent to the target electric vehicle, thereby achieving a more reasonable allocation of battery swap station resources, avoiding some battery swap stations from being unable to provide services due to resource constraints, and improving battery replacement efficiency.

[0035] In a preferred case of this embodiment, in S2, the process of determining the target battery swap station is:

[0036] All battery swap stations with a backup battery level greater than zero are screened out from the battery swap station information and marked as pending battery swap stations. Any passing node is taken as the starting point, and the Dijkstra algorithm is used to obtain the shortest path from the starting point to all pending battery swap stations. The driving distances of all shortest paths are obtained and the battery swap station corresponding to the shortest path with the shortest driving distance is calibrated as the target battery swap station corresponding to the passing node.

[0037] In another preferred situation of this embodiment, in S2, the specific process of generating the switching route is as follows:

[0038] Select any transit node Ya and obtain the target battery swap station Ha corresponding to the transit node Ya, take the target battery swap station Ha as the adjacent next transit node of the transit node, obtain the planned transit sequence Y1, Y2, ..., Ya, Ha, and generate a battery swap route according to the planned transit sequence.

[0039] In another preferred embodiment of the present invention, in S2, the specific process of obtaining the remaining mileage is as follows:

[0040] The remaining power of the target electric vehicle is extracted from the battery status information, and vehicle parameter data of the electric vehicle information is obtained; and the remaining mileage of the target electric vehicle is calculated based on the remaining power and the vehicle parameter data.

[0041] In another preferred situation of this embodiment, in S3, the specific calculation process of the preferred score is:

[0042] ;

[0043] Among them, E is the total number of other electric vehicles in the target area, Csi is the reference score of the sth other electric vehicle corresponding to the battery swap station i, and ε is the preset unit coefficient.

[0044] In another preferred situation of this embodiment, if there is no battery swap station i among the target battery swap stations corresponding to any other electric vehicle, the reference score of the electric vehicle at the battery swap station i is marked as 0.

[0045] In another preferred situation of the present embodiment, in S3, if there are two or more target battery swap stations whose preferred scores are all maximum values, the number of reserved battery swap routes corresponding to any target battery swap station is obtained, and the target battery swap station with the largest number of reserved battery swap routes is selected as the optimal target battery swap station.

[0046] In another preferred situation of the present embodiment, it also includes obtaining all reserved power switching routes corresponding to the optimal target power switching station and marking them as d1, d2, ..., dv, calculating the road condition score of any reserved power switching route according to the calculation formula W=μ*Ki*Gi, selecting the reserved power switching route with the smallest road condition score as the optimal route and pushing it to the target electric vehicle, wherein μ is a preset correction coefficient, Ki is the number of traffic lights corresponding to any reserved planned route, and Gi is the number of turns required for the reserved power switching route.

[0047] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A route planning method for replacing batteries in a takeaway vehicle, characterized in that: The following steps are involved: S1, obtain the order, location and expected driving route information of any target electric vehicle in the target area, determine the passing nodes according to the order and sort them according to the expected route, and obtain the passing node sequence Y1, Y2, ..., Yn; S2, obtain the information of the battery swap station in the target area to determine that all the passing nodes correspond to the target battery swap station and mark them as H1, H2, ..., Hn, generate the battery swap route between the target electric vehicle and any target battery swap station and mark them as D1, D2, ..., Dn; obtain the current battery status information of the target electric vehicle to filter all the battery swap routes, obtain all the retained battery swap routes and mark them as D1, D2, ..., Dm; according to the calculation formula The pending score of any target battery swap station is calculated, where hi is the number of reserved battery swap routes corresponding to the i-th target battery swap station, and m is the total number of reserved battery swap routes; S3, repeat S1 and S2, obtain the pending scores of other electric vehicles in the target area at battery swap station i as reference scores, obtain the backup battery capacity M of battery swap station i, correct the pending score of the target electric vehicle corresponding to the target battery swap station i according to the backup battery capacity M and the reference score, obtain the preferred score Q, select the battery swap route corresponding to the target battery swap station with the highest preferred score, and push the route to the target electric vehicle.

2. A route planning method for replacing battery of a takeaway vehicle according to claim 1, characterized in that: In S2, the process of determining the target battery swap station is as follows: All battery swap stations with a backup battery level greater than zero are screened out from the battery swap station information and marked as pending battery swap stations. Any passing node is taken as the starting point, and the Dijkstra algorithm is used to obtain the shortest path from the starting point to all pending battery swap stations. The driving distances of all shortest paths are obtained and the battery swap station corresponding to the shortest path with the shortest driving distance is calibrated as the target battery swap station corresponding to the passing node.

3. A route planning method for replacing battery of a takeaway vehicle according to claim 1, characterized in that: In S2, the specific process of generating the switching route is as follows: Select any transit node Ya and obtain the target battery swap station Ha corresponding to the transit node Ya, take the target battery swap station Ha as the adjacent next transit node of the transit node, obtain the planned transit sequence Y1, Y2, ..., Ya, Ha, and generate a battery swap route according to the planned transit sequence.

4. A method for route planning for battery replacement of a takeaway vehicle according to claim 1, characterized in that: In S2, the specific acquisition process of switching route screening is as follows: The remaining power of the target electric vehicle is extracted from the battery status information, and the vehicle parameter data of the electric vehicle information is obtained; the remaining mileage L' of the target electric vehicle is calculated according to the remaining power and the vehicle parameter data, and the mileage of any power conversion route is calculated in turn and marked as L1, L2, ..., Ln. If there is any power conversion route with a mileage Li less than or equal to L'*(1-α), the power conversion route is retained, wherein α is a preset safety factor.

5. A route planning method for replacing battery of a takeaway vehicle according to claim 1, characterized in that: In S3, the specific calculation process of the preferred score is: ； Among them, E is the total number of other electric vehicles in the target area, Csi is the reference score of the sth other electric vehicle corresponding to the battery swap station i, and ε is the preset unit coefficient.

6. A method for route planning for battery replacement of a takeaway vehicle according to claim 5, characterized in that: It also includes marking the reference score of the electric vehicle at the battery swap station i as 0 if there is no battery swap station i among the target battery swap stations corresponding to any other electric vehicle.

7. A route planning method for replacing battery of a takeaway vehicle according to claim 1, characterized in that: In S3, if there are two or more target battery swap stations whose preferred scores are all maximum values, the number of reserved battery swap routes corresponding to any target battery swap station is obtained, and the target battery swap station with the largest number of reserved battery swap routes is selected as the optimal target battery swap station.

8. A method for route planning for battery replacement of a takeaway vehicle according to claim 7, characterized in that: It also includes obtaining all reserved power-swap routes corresponding to the optimal target power-swap station and marking them as d1, d2, ..., dv, calculating the road condition score of any reserved power-swap route according to the calculation formula W=μ*Ki*Gi, selecting the reserved power-swap route with the smallest road condition score as the optimal route and pushing it to the target electric vehicle, where μ is a preset correction coefficient, Ki is the number of traffic lights corresponding to any reserved planned route, and Gi is the number of turns required for the reserved power-swap route.

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