Online car-hailing charging management method and device, electronic equipment and medium

Abstract

The invention provides an online car-hailing charging management method and device, electronic equipment and a medium, and relates to the technical field of charging, and the method comprises the steps: predicting the operation value of a plurality of online car-hailing cars generated by an order in each future time period; predicting charging values generated by charging of the plurality of online hailed cars in each future time period; dividing the plurality of online hailed cars into a plurality of sets in each future time period according to the charging condition of each online hailed car; determining a benefit index corresponding to each set in each future time period according to the charging value in each future time period and the operation values of the plurality of online hailed cars; and according to the set corresponding to the benefit indexes meeting the first preset requirement in each future time period, managing the charging conditions of the plurality of online hailed cars in each future time period. According to the embodiment of the invention, the charging conditions of a plurality of online-hailed cars in a plurality of future time periods can be planned in advance for management, and compared with independent actions of a single online-hailed car, the operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of charging technology, and in particular to a charging management method, device, electronic equipment and medium for online car-hailing. Background Art

[0002] Electric vehicles are also one of the existing vehicle types for online ride-hailing vehicles. Unlike fuel-powered vehicles, electric vehicles take a long time to charge. Therefore, apart from operating outside to take orders, electric online ride-hailing vehicles spend most of their time undergoing offline maintenance. Charging, in particular, takes a long time, but the charging locations are fixed and the charging spaces are limited. If an electric online ride-hailing vehicle only goes to a charging location to charge according to its needs, and all the parking spaces at the charging location are occupied, the electric online ride-hailing vehicle will need to queue up to wait for charging. The time consumed for charging is longer than the time spent simply charging, resulting in relatively low operating efficiency of the electric online ride-hailing vehicle. Summary of the invention

[0003] The present invention provides a method, device, electronic device and medium for managing charging of online-hailing vehicles, which can coordinate and manage the charging conditions of multiple online-hailing vehicles in multiple future time periods in advance, thereby improving operational efficiency compared to independent action of a single online-hailing vehicle.

[0004] In a first aspect, an embodiment of the present invention provides a method for managing charging of an online car-hailing vehicle, including:

[0005] Based on the order information generated in the target area during multiple historical time periods, the operating value generated by the orders of multiple online ride-hailing vehicles in each future time period is predicted; and based on the charging information in the target area during multiple historical time periods, the charging value generated by the charging of multiple online ride-hailing vehicles in each future time period is predicted;

[0006] Establish multiple sets based on multiple online ride-hailing vehicles in each future time period; and determine the benefit index corresponding to each set in each future time period based on the charging value in each future time period and the operating value of multiple online ride-hailing vehicles; wherein the multiple online ride-hailing vehicles in each set are set with different or the same charging status, and the charging status of at least two online ride-hailing vehicles in different sets are different;

[0007] The charging status of multiple online-hailing vehicles in each future time period is managed according to the set of efficiency indicators corresponding to the first preset requirements in each future time period.

[0008] The above method can divide each future time period into multiple sets according to the charging status of each online-hailing vehicle, and determine the benefit index corresponding to each set based on the operating value and the charging value by predicting the operating value and the charging value in each future time period. According to the benefit index, a set is selected from the multiple sets in each future time period, and the charging status is managed according to the selected set. The present invention can coordinate and manage the charging status of multiple online-hailing vehicles in multiple future time periods in advance, which improves the operational efficiency compared to the independent action of a single online-hailing vehicle.

[0009] In one possible implementation, the set at each future time period satisfies the following requirements:

[0010] The number of online-hailing vehicles in the set that are in a charging state is less than the charging capacity of the target area;

[0011] The time interval between the times when the same online-hailing vehicle appears in charging status exceeds the preset interval.

[0012] The above method can avoid the situation where the number of online-hailing vehicles that need to be charged is less than the charging capacity, resulting in some online-hailing vehicles having to queue up to wait for charging. It can also avoid the situation where online-hailing vehicles are charged arbitrarily, resulting in relatively low operating value.

[0013] In a possible implementation method, based on the charging value and the operating value of multiple online ride-hailing vehicles in each future time period, the benefit indicators corresponding to each set in each future time period are determined, including:

[0014] For each set in each future time period, the charging value of the online-hailing vehicles in the set that are in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period; the operating value of the online-hailing vehicles in the set that are not in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period;

[0015] The sum of the individual benefit indicators corresponding to the online ride-hailing vehicles in each set in each future time period is used as the benefit indicator corresponding to each set in each future time period.

[0016] The above method can determine the benefit index of a single online-hailing vehicle through the operating value and charging value of each online-hailing vehicle in each future time period, and determine the total benefit index corresponding to each set based on the sum of the benefit indicators of a single online-hailing vehicle. In this way, the total benefit can be determined for the situation of each online-hailing vehicle, thereby improving the accuracy of the determination.

[0017] In a possible implementation, the charging status of multiple online-hailing vehicles in each future time period is managed according to a set of benefit indicators corresponding to the first preset requirement in each future time period, including:

[0018] Counting the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in the set corresponding to the benefit indicator that meets the first preset requirement in each future time period;

[0019] Generate charging scheduling data for each future time period according to the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in a set corresponding to the benefit indicator that meets the first preset requirement in each future time period;

[0020] Based on the charging scheduling data for each future time period, multiple online-hailing vehicles are scheduled in each future time period.

[0021] The above method can determine the charging scheduling data simply by the number of charged online-hailing vehicles and the number of uncharged online-hailing vehicles in each future time period, and thus schedule based on the charging scheduling data. The scheduling situation is considered based on the statistical scope, which can improve the overall operational efficiency compared to a single online-hailing vehicle.

[0022] In one possible implementation, before managing the charging conditions of multiple online-hailing vehicles in each future time period according to the set of benefit indicators corresponding to the first preset requirement that meet the first preset requirement in each future time period, the method further includes:

[0023] For each future time period, if the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is less than the number of transportation capacity demands in the future time period, the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is adjusted, or the number of online-hailing vehicles in the target set that are in a charging state in the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state in the target future time period are adjusted; wherein the target set is a set corresponding to the benefit indicators that meet the first preset requirements; and the target future time period is a time period adjacent to the future time period and before the future time period.

[0024] The above method can adjust the number of online-hailing vehicles in charging state and the number of online-hailing vehicles in non-charging state in the target set in the future time period based on the number of transportation capacity demands in the future time period, thereby alleviating the mismatch between transportation capacity and operating online-hailing vehicles, leading to an imbalance in supply and demand.

[0025] In a possible implementation, adjusting the number of online-hailing vehicles in the target set that are not in a charging state in the future time period includes:

[0026] According to the order of the remaining power of the online-hailing vehicles in the target set in the future time period, whether the online-hailing vehicles in the target set are in the charging state is adjusted multiple times in the future time period to obtain multiple candidate sets in the future time period;

[0027] Determining benefit indicators corresponding to multiple candidate sets in the future time period;

[0028] According to the candidate set corresponding to the benefit indicator that meets the second preset requirement, the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is adjusted.

[0029] The above method can readjust the number of online-hailing vehicles in the target set that are in a charging state according to the remaining power of the online-hailing vehicles in the target set in the future time period, thereby alleviating the mismatch between the transport capacity and the operating online-hailing vehicles, leading to an imbalance in supply and demand.

[0030] In one possible implementation, adjusting the number of online-hailing vehicles in the target set that are in a charging state within a target future time period and the number of online-hailing vehicles in the target set that are not in a charging state within the future time period includes:

[0031] Determine a ratio between a benefit index corresponding to the target set in the future time period and a benefit index corresponding to the target set in the target future time period;

[0032] According to the ratio, the number of online-hailing vehicles in the target set that are in a charging state within the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state within the target future time period are adjusted.

[0033] The above method can readjust the number of online-hailing vehicles in the two target sets that are in a charging state in two adjacent future time periods through the efficiency indicators corresponding to the target sets, so as to prepare in advance for the capacity demand in the future time period, thereby alleviating the mismatch between the capacity and the operating online-hailing vehicles, leading to an imbalance in supply and demand.

[0034] In a second aspect, an embodiment of the present invention provides a charging management device for an online car-hailing vehicle, comprising:

[0035] A prediction module is used to predict the operation value generated by orders of multiple online ride-hailing vehicles in each future time period based on order information generated in a target area in multiple historical time periods; and to predict the charging value generated by charging of multiple online ride-hailing vehicles in each future time period based on charging information in a target area in multiple historical time periods;

[0036] A determination module is used to establish multiple sets according to multiple online-hailing vehicles in each future time period; and determine the benefit index corresponding to each set in each future time period according to the charging value in each future time period and the operating value of multiple online-hailing vehicles; wherein the multiple online-hailing vehicles in each set are set with different or the same charging status, and the charging status of at least one online-hailing vehicle in different sets is different;

[0037] The management module is used to manage the charging status of multiple online-hailing vehicles in each future time period according to the set of benefit indicators corresponding to the first preset requirements that meet the requirements in each future time period.

[0038] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0039] processor;

[0040] A processor is used to execute the computer program or instructions in the memory so that the online car-hailing charging management method as described in any one of the first aspects is executed.

[0041] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor, the processor is enabled to execute the online car-hailing charging management method as described in any one of the first aspects.

[0042] In a fifth aspect, an embodiment of the present invention provides a computer program product, comprising: a computer program code, when the computer program code runs on a computer, the computer executes the online car-hailing charging management method as described in any one of the first aspects.

[0043] In addition, the technical effects brought about by any implementation method in the second to fifth aspects can refer to the technical effects brought about by different implementation methods in the first aspect, and will not be repeated here.

[0044] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of a target area provided by an embodiment of the present invention;

[0046] Figure 2 A flowchart of a charging management method for online car-hailing provided by an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of determining the scheduling of multiple online ride-hailing vehicles in each future time period provided by an embodiment of the present invention;

[0048] Figure 4A schematic diagram of the structure of a charging management device for online car-hailing provided by an embodiment of the present invention;

[0049] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all 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.

[0051] In the description of the embodiments of the present application, unless otherwise specified, in the description of the embodiments of the present application, "plurality" refers to two or more than two.

[0052] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0053] Glossary:

[0054] Robotaxi: refers to a taxi driven by autonomous driving technology. It does not require a human driver and relies on technologies such as sensors, artificial intelligence and high-precision maps to achieve automatic driving, navigation and decision-making.

[0055] Whether it is a manned electric vehicle or an unmanned electric vehicle, it needs to be charged during operation. However, if an electric vehicle goes to a charging place to charge according to its own needs, it is very likely that all the parking spaces at the charging place will be occupied. In this way, the electric vehicle needs to queue up and wait for charging, and then charge again. The time consumed for charging is longer than the time for simple charging, resulting in relatively low operating efficiency of the electric vehicle.

[0056] Based on this, an embodiment of the present invention provides a solution, which can predict the charging status of multiple online-hailing vehicles for future time periods. According to the predicted charging status of multiple online-hailing vehicles, the operation of online-hailing vehicles can be coordinated as a whole to improve the overall operational efficiency.

[0057] For example, the relevant information of online-hailing vehicles today and before today can be used to predict the charging status of online-hailing vehicles in multiple time periods tomorrow. In this way, when operating these online-hailing vehicles tomorrow, these online-hailing vehicles can be managed with reference to the above prediction information.

[0058] The present invention is described in detail below with reference to the accompanying drawings:

[0059] Combination Figure 1 As shown, the target area 10 includes charging places P1 and charging places P2, each of which is provided with multiple charging positions. Multiple online-hailing vehicles are operated in the target area 10. The operation conditions of the multiple online-hailing vehicles in historical time periods are utilized to predict the charging conditions at charging places P1 and charging places P2 in multiple future time periods, and the charging conditions of the multiple online-hailing vehicles are managed according to the predicted charging conditions.

[0060] Combination Figure 2 As shown, an embodiment of the present invention provides a charging management method for an online car-hailing vehicle, comprising:

[0061] S200: predicting the operating value of multiple online ride-hailing vehicles due to orders in each future time period based on order information generated in the target area during multiple historical time periods; and predicting the charging value of multiple online ride-hailing vehicles due to charging in each future time period based on charging information in the target area during multiple historical time periods;

[0062] The historical time period can be the time period before the current time, and the future time period can be the time period after the current time. For example, if the current time is 9:00 on October 1, 2024, the historical time period is the time period before 9:00 on October 1, 2024, and the future time period is the time period after 9:00 on October 1, 2024.

[0063] The operating value can be understood as the order cost. The predicted operating value generated by orders of multiple online ride-hailing vehicles in each future time period can be understood as: the total cost of multiple orders generated by multiple online ride-hailing vehicles in each future time period.

[0064] The charging value can be understood as the cost incurred by online ride-hailing vehicles due to charging. Predicting the charging value incurred by multiple online ride-hailing vehicles in each future time period can be understood as: predicting the charging costs of multiple online ride-hailing vehicles in each future time period.

[0065] In detail, for each future time period, the operating value generated by orders in the future time period is predicted based on the order information generated in the target area in the historical time period corresponding to the future time period; and the charging value generated by charging of multiple online ride-hailing vehicles in the future time period is predicted based on the charging information in the target area in the historical time period corresponding to the future time period.

[0066] The historical time period corresponding to the future time period may be a historical time period before the future time period and having the same time period as the future time period.

[0067] For example, the current time is 9:00-10:00 on October 1, 2024, and the time periods before the current time can be 9:00-10:00 on September 30, 2024, 9:00-10:00 on September 29, 2024, and so on. The future time period is 9:00-10:00 on October 2, 2024, then the historical time periods corresponding to the future time period include 9:00-10:00 on October 1, 2024, 9:00-10:00 on September 30, 2024, 9:00-10:00 on September 29, 2024, and so on.

[0068] S201: Establish multiple sets according to multiple online-hailing vehicles in each future time period; and determine the benefit index corresponding to each set in each future time period according to the charging value in each future time period and the operating value of multiple online-hailing vehicles; wherein the multiple online-hailing vehicles in each set are set with different or the same charging status, and the charging status of at least one online-hailing vehicle in different sets is different;

[0069] Among them, for each future time period, the same batch of online-hailing vehicles are set to different charging status multiple times. Some online-hailing vehicles are set to be in a charging state, and some online-hailing vehicles are set to be in a non-charging state. The results of multiple settings are used to establish multiple sets.

[0070] For example, there are 3 online-hailing cars, the first online-hailing car, the second online-hailing car, and the third online-hailing car. One online-hailing car is set to be in a charging state, and the other two online-hailing cars are not in a charging state. This situation constitutes 9 sets. Two online-hailing cars are set to be in a charging state, and one online-hailing car is not in a charging state. This situation constitutes 3 sets. Three online-hailing cars are all set to be in a charging state, and three online-hailing cars are all set to not be in a charging state. This situation constitutes 2 sets, and one forms 14 sets.

[0071] S202: Manage the charging status of multiple online-hailing vehicles in each future time period according to the set of efficiency indicators corresponding to the first preset requirements in each future time period.

[0072] In this way, the embodiment of the present invention can predict the charging status of multiple online-hailing vehicles in a future time period based on the predicted operating value and charging value of multiple online-hailing vehicles, thereby enabling multiple online-hailing vehicles to be managed according to the predicted charging status, which improves operational efficiency compared to a single online-hailing vehicle acting independently.

[0073] In some embodiments, for each future time period, order information and charging information in the target area for multiple historical time periods corresponding to the future time period are first obtained.

[0074] Charging information, for example, includes vehicle data of online-hailing vehicles that are not in charging status in multiple historical time periods corresponding to the future time period, the number of online-hailing vehicles that are in charging status, the number of online-hailing vehicles waiting to be charged, the number of online-hailing vehicles that have completed charging, the vacant charging positions in the charging venue, the charging positions that are being charged in the charging venue, and the released charging positions; vehicle data includes SOC (State Of Charge, remaining power) data.

[0075] Order information, for example, the single-bike revenue of orders in multiple historical time periods corresponding to the future time period, etc.

[0076] Based on the above order information and charging information, the supply and demand relationship of the morning peak, the supply and demand relationship of the evening peak, the supply and demand relationship of the flat peak, the peak electricity price, the flat peak electricity price, the valley electricity price, the number of online-hailing vehicles waiting for charging, the number of online-hailing vehicles being charged, and the real-time battery SOC data of the online-hailing vehicles being charged, the idle charging positions, the charging positions being charged, the released charging positions, the single-vehicle revenue, the number of online-hailing vehicles in operation, the SOC data of online-hailing vehicles in operation, the number of online-hailing vehicles in operation that return to the charging station (return data), and the number of online-hailing vehicles with the difference between supply and demand (capacity gap data) are extracted for each historical time period corresponding to the future time period, as shown in the following table:

[0077]

[0078]

[0079] Set scores and weights for the data in the above table; determine the values ​​representing the information based on the scores and weights in the above table, predict the operation value based on the values ​​related to the order information; and predict the charging value based on the values ​​related to the charging information.

[0080] In some embodiments, the set within each future time period satisfies the following requirements:

[0081] The number of online ride-hailing vehicles in the collection that are in a charging state is less than the charging capacity of the target area;

[0082] The time interval between the times when the same online-hailing vehicle appears in charging status exceeds the preset interval.

[0083] Specifically, the number of online ride-hailing vehicles in the set that are in a charging state is less than the charging capacity of the target area is expressed as follows:

[0084]

[0085] Among them, L t is the charging capacity of the charging station in the target area, that is, the charging stations that are not charged by online ride-hailing vehicles, x i,tis a binary variable, indicating whether online car-hailing vehicle i will charge in the future time period t. i,t =1 means the online car-hailing vehicle is in the charging state, x i,t =0 means the online ride-hailing vehicle is not charging.

[0086] The preset interval is the time in the future. The time interval of the same online car-hailing vehicle in the charging state exceeding the preset interval is expressed in the following way:

[0087]

[0088] The above formula indicates that the same online car-hailing vehicle can only be charged in one future time period among multiple future time periods.

[0089] In some embodiments, according to the charging value in each future time period and the operating value of multiple online ride-hailing vehicles, the benefit index corresponding to each set in each future time period is determined, including:

[0090] For each set in each future time period, the charging value of the online-hailing vehicles in the set that are in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period; the operating value of the online-hailing vehicles in the set that are not in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period;

[0091] The sum of the individual benefit indicators corresponding to the online ride-hailing vehicles in each set in each future time period is used as the benefit indicator corresponding to each set in each future time period.

[0092] Specifically, the benefit index corresponding to each set in each future time period is calculated by the following formula:

[0093]

[0094] Among them, there are N online ride-hailing vehicles, R i,t is the operating value of the online car-hailing service in the future time period t, C t The charging value for future time periods.

[0095] The single benefit indicator corresponding to a single online car-hailing service: R i,t (1-x i,t )-C t x i,t ;

[0096] For each set in each future time period, when a ride-hailing vehicle x i,t When not in charging state, x i,t =0, then the single benefit index corresponding to the online car-hailing service is Ri,t ; When a ride-hailing car i,t When in charging state, x i,t =1, then the single benefit indicator corresponding to the online car-hailing service is -C t The sum of the individual benefit indicators corresponding to each online car-hailing vehicle in this set is taken as the benefit indicator corresponding to the set.

[0097] In some embodiments, in combination Figure 3 As shown, according to the set of benefit indicators corresponding to the first preset requirement in each future time period, the charging status of multiple online-hailing vehicles in each future time period is managed, including:

[0098] S300: Counting the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in a set corresponding to the benefit indicator that meets the first preset requirement in each future time period;

[0099] S301: Generate charging scheduling data for each future time period according to the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in a set corresponding to the benefit indicator that meets the first preset requirement in each future time period;

[0100] S302: Scheduling multiple online-hailing vehicles in each future time period based on the charging scheduling data for each future time period.

[0101] Among them, the benefit indicator that meets the first preset requirement is the maximum benefit indicator.

[0102] For example, the historical time period can be today and the time period before today, and the multiple future time periods can be 24 time periods of 1 hour tomorrow. The charging schedule data of each future time period is shown in the following table:

[0103]

[0104]

[0105] The above table shows the future time periods set in 1-hour time periods in a day. The charging scheduling data in the above table include the optimal benefit indicators for multiple future time periods, the number of online-hailing vehicles in charging status under the optimal benefit indicators, the number of online-hailing vehicles not in charging status under the optimal benefit indicators, and the number of transport capacity demands.

[0106] The amount of transport capacity demand in each future time period may be predicted based on the amount of transport capacity demand in multiple historical time periods corresponding to each future time period, weather and other external factors.

[0107] In some embodiments, before managing the charging conditions of multiple online-hailing vehicles in each future time period according to the set of benefit indicators corresponding to the first preset requirement in each future time period, the method further includes:

[0108] For each future time period, if the number of online-hailing vehicles that are not in a charging state in the target set in the future time period is less than the number of transportation capacity demands in the future time period, the number of online-hailing vehicles that are not in a charging state in the target set in the future time period is adjusted, or the number of online-hailing vehicles that are in a charging state in the target set in the target future time period and the number of online-hailing vehicles that are not in a charging state in the target set in the future time period are adjusted; wherein, the target set is a set corresponding to the efficiency indicator that meets the first preset requirement; the target future time period is a time period adjacent to the future time period and before the future time period.

[0109] When performing the above operations, the required capacity quantity can be referred to the above table.

[0110] Among them, adjusting the number of online-hailing vehicles that are not in a charging state in the target set in the future time period includes:

[0111] According to the order of the remaining power of the online-hailing vehicles in the target set in the future time period from large to small, multiple adjustments are made to whether the online-hailing vehicles in the target set in the future time period are in the charging state, and multiple candidate sets in the future time period are obtained;

[0112] Determine the benefit indicators corresponding to multiple candidate sets in the future time period;

[0113] According to the candidate set corresponding to the efficiency indicator that meets the second preset requirement, the number of online-hailing vehicles that are not in charging status in the target set in the future time period is adjusted.

[0114] Specifically, when the number of online-hailing vehicles that are not in a charging state in the target set in the future time period is greater than the number of transportation capacity requirements in the future time period, no adjustment is required. When the number of online-hailing vehicles that are not in a charging state in the target set in the future time period is less than the number of transportation capacity requirements in the future time period, the difference between the number of online-hailing vehicles that are not in a charging state and the number of transportation capacity requirements is set to be no greater than the adjustment number. For example, when the difference is 2, the adjustment number is set to be greater than 2; when the difference is 4, the adjustment number is set to be greater than 4.

[0115] For example, when the difference is 1 and the adjustment quantity is 2, then the two online-hailing vehicles with the largest and second largest remaining power that can be adjusted are the ones that are currently charging. Similarly, when the difference is 1 and the adjustment quantity is 3, then the three online-hailing vehicles with the largest, second largest, and third largest remaining power that can be adjusted are the ones that are currently charging.

[0116] When the difference is 1 and the adjustment quantity is 2, the number of candidate sets is 2, namely, the online-hailing car with the largest remaining power that is currently charging is transferred to the set of online-hailing cars that are not currently charging, and the online-hailing car with the second largest remaining power that is currently charging is transferred to the set of online-hailing cars that are not currently charging.

[0117] When the difference is 1 and the number of adjustments is 3, the number of candidate sets is 3, namely, the online-hailing car with the largest remaining power that is currently charging is transferred to the set of online-hailing cars that are not currently charging, the online-hailing car with the second largest remaining power that is currently charging is transferred to the set of online-hailing cars that are not currently charging, and the online-hailing car with the third largest remaining power that is currently charging is transferred to the set of online-hailing cars that are not currently charging.

[0118] Based on the above candidate sets and the above formula for calculating the benefit index, the benefit index corresponding to each candidate set is determined. The candidate set corresponding to the maximum adjusted benefit index is selected as the final adjustment plan.

[0119] Among them, adjusting the number of online-hailing vehicles in the target set that are in a charging state in the target future time period and the number of online-hailing vehicles that are not in a charging state in the target set in the future time period includes:

[0120] Determine the ratio between the benefit index corresponding to the target set in the future time period and the benefit index corresponding to the target set in the target future time period;

[0121] According to the ratio, the number of online-hailing vehicles in the target set that are in a charging state in the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state in the target future time period are adjusted.

[0122] For example, when the future time period is from 5 o'clock to 6 o'clock, the target future time period is from 4 o'clock to 5 o'clock.

[0123] The number of online-hailing vehicles in the target set that are in a charging state in the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state in the target future time period are adjusted to be equal to the ratio.

[0124] The online-hailing vehicles that are not in a charging state within the target future time period are adjusted to the online-hailing vehicles that are in a charging state within the target future time period; the number of the adjusted online-hailing vehicles is added to the number of the online-hailing vehicles that are not in a charging state within the future time period.

[0125] like Figure 4 As shown, the present invention also provides a charging management device for an online car-hailing vehicle, comprising:

[0126] Prediction module 400, for predicting the operation value generated by orders of multiple online ride-hailing vehicles in each future time period based on order information generated in a target area in multiple historical time periods; and for predicting the charging value generated by charging of multiple online ride-hailing vehicles in each future time period based on charging information in a target area in multiple historical time periods;

[0127] The determination module 401 is used to establish multiple sets according to multiple online-hailing vehicles in each future time period; and determine the benefit index corresponding to each set in each future time period according to the charging value in each future time period and the operating value of multiple online-hailing vehicles; wherein the multiple online-hailing vehicles in each set are set with different or the same charging status, and the charging status of at least one online-hailing vehicle in different sets is different;

[0128] The management module 402 is used to manage the charging status of multiple online-hailing vehicles in each future time period according to the set of efficiency indicators corresponding to the first preset requirements in each future time period.

[0129] Optionally, the collection in each future time period meets the following requirements:

[0130] The number of online-hailing vehicles in the set that are in a charging state is less than the charging capacity of the target area;

[0131] The time interval between the times when the same online-hailing vehicle appears in charging status exceeds the preset interval.

[0132] Optionally, the determination module 401 is specifically configured to:

[0133] For each set in each future time period, the charging value of the online-hailing vehicles in the set that are in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period; the operating value of the online-hailing vehicles in the set that are not in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period;

[0134] The sum of the individual benefit indicators corresponding to the online ride-hailing vehicles in each set in each future time period is used as the benefit indicator corresponding to each set in each future time period.

[0135] Optionally, the management module 402 is specifically configured to:

[0136] Counting the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in the set corresponding to the benefit indicator that meets the first preset requirement in each future time period;

[0137] Generate charging scheduling data for each future time period according to the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in a set corresponding to the benefit indicator that meets the first preset requirement in each future time period;

[0138] Based on the charging scheduling data for each future time period, multiple online-hailing vehicles are scheduled in each future time period.

[0139] Optionally, the management module 402 is further configured to:

[0140] For each future time period, if the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is less than the number of transportation capacity demands in the future time period, the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is adjusted, or the number of online-hailing vehicles in the target set that are in a charging state in the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state in the target future time period are adjusted; wherein the target set is a set corresponding to the benefit indicators that meet the first preset requirements; and the target future time period is a time period adjacent to the future time period and before the future time period.

[0141] Optionally, the management module 402 is further configured to:

[0142] According to the order of the remaining power of the online-hailing vehicles in the target set in the future time period, whether the online-hailing vehicles in the target set are in the charging state is adjusted multiple times in the future time period to obtain multiple candidate sets in the future time period;

[0143] Determining benefit indicators corresponding to multiple candidate sets in the future time period;

[0144] According to the candidate set corresponding to the benefit indicator that meets the second preset requirement, the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is adjusted.

[0145] Optionally, the management module 402 is further configured to:

[0146] Determine a ratio between a benefit index corresponding to the target set in the future time period and a benefit index corresponding to the target set in the target future time period;

[0147] According to the ratio, the number of online-hailing vehicles in the target set that are in a charging state within the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state within the target future time period are adjusted.

[0148] In addition, combined Figure 1-Figure 4The online car-hailing charging management method and device described in the embodiments of the present invention can be implemented by an electronic device.

[0149] Electronic devices, including: processors;

[0150] a memory for storing instructions executable by the processor;

[0151] Wherein, the processor is configured to execute the instructions to implement the online car-hailing charging management method as described in any one of the above-mentioned methods.

[0152] Based on the above introduction, an exemplary Figure 5 electronic equipment structure.

[0153] The electronic device may include a processor 501 and a memory 502 storing computer program instructions.

[0154] Specifically, the processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.

[0155] The memory 502 may include a large capacity memory for data or instructions. For example, but not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 502 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 502 may be inside or outside the data processing device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory. In a specific embodiment, the memory 502 includes a read-only memory (ROM). In appropriate cases, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM) or a flash memory or a combination of two or more of these.

[0156] The processor 501 implements any one of the methods for executing tasks in the above embodiments by reading and executing computer program instructions stored in the memory 502 .

[0157] In one example, the electronic device may further include a communication interface 503 and a bus 504. Figure 5As shown, the processor 501, the memory 502, and the communication interface 503 are connected via a bus 504 and communicate with each other.

[0158] The communication interface 503 is mainly used to implement the communication between the modules, devices, units and / or equipment in the embodiment of the present invention.

[0159] Bus 504 includes hardware, software or both, and the parts of electronic equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 504 may include one or more buses. Although the embodiment of the present invention describes and shows a specific bus, the present invention considers any suitable bus or interconnection.

[0160] The electronic device can execute the online car-hailing charging management method in the embodiment of the present invention based on the received task, thereby realizing the combination Figure 1-Figure 4 Described is a charging management method and device for an online car-hailing vehicle.

[0161] In addition, in combination with the electronic device in the above embodiments, an embodiment of the present invention may provide a storage medium. When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the online car-hailing charging management method as described in any one of the above items.

[0162] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0163] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0164] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0165] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0166] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A charging management method for online car-hailing, characterized in that: include: Based on the order information generated in the target area in multiple historical time periods, predict the operating value of multiple online ride-hailing vehicles due to orders in each future time period; and predicting the charging value generated by charging of multiple online ride-hailing vehicles in each future time period based on charging information in a target area in multiple historical time periods; Establish multiple sets based on multiple online ride-hailing vehicles in each future time period; And according to the charging value in each future time period and the operating value of multiple online-hailing vehicles, determine the benefit index corresponding to each set in each future time period; wherein the multiple online-hailing vehicles in each set are set with different or the same charging status, and the charging status of at least one online-hailing vehicle in different sets is different; The charging status of multiple online-hailing vehicles in each future time period is managed according to the set of efficiency indicators corresponding to the first preset requirements in each future time period.

2. The online car-hailing charging management method according to claim 1, characterized in that: The set at each future time period satisfies the following requirements: The number of online-hailing vehicles in the set that are in a charging state is less than the charging capacity of the target area; The time interval between the times when the same online-hailing vehicle appears in charging status exceeds the preset interval.

3. The online car-hailing charging management method according to claim 1, characterized in that: According to the charging value and the operating value of multiple online ride-hailing vehicles in each future time period, the benefit indicators corresponding to each set in each future time period are determined, including: For each set in each future time period, the charging value of the online-hailing vehicles in the set that are in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period; the operating value of the online-hailing vehicles in the set that are not in a charging state in the future time period is used as a single benefit indicator corresponding to the online-hailing vehicles in the set that are in a charging state in the future time period; The sum of the individual benefit indicators corresponding to the online ride-hailing vehicles in each set in each future time period is used as the benefit indicator corresponding to each set in each future time period.

4. The online car-hailing charging management method according to claim 1, characterized in that: According to the set of benefit indicators corresponding to the first preset requirement in each future time period, the charging status of multiple online-hailing vehicles in each future time period is managed, including: Counting the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in the set corresponding to the benefit indicator that meets the first preset requirement in each future time period; Generate charging scheduling data for each future time period according to the number of online-hailing vehicles that are not in a charging state and the number of online-hailing vehicles that are in a charging state in a set corresponding to the benefit indicator that meets the first preset requirement in each future time period; Based on the charging scheduling data for each future time period, multiple online-hailing vehicles are scheduled in each future time period.

5. The charging management method for online car-hailing according to any one of claims 1 to 4, characterized in that: Before managing the charging conditions of multiple online-hailing vehicles in each future time period according to the set of benefit indicators corresponding to the first preset requirement that meet the first preset requirement in each future time period, the method further includes: For each future time period, if the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is less than the number of transportation capacity demands in the future time period, the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is adjusted, or the number of online-hailing vehicles in the target set that are in a charging state in the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state in the target future time period are adjusted; wherein the target set is a set corresponding to the benefit indicators that meet the first preset requirements; and the target future time period is a time period adjacent to the future time period and before the future time period.

6. The online car-hailing charging management method according to claim 5, characterized in that: Adjusting the number of online-hailing vehicles in the target set that are not in a charging state in the future time period includes: According to the order of the remaining power of the online-hailing vehicles in the target set in the future time period, whether the online-hailing vehicles in the target set are in the charging state is adjusted multiple times in the future time period to obtain multiple candidate sets in the future time period; Determining benefit indicators corresponding to multiple candidate sets in the future time period; According to the candidate set corresponding to the benefit indicator that meets the second preset requirement, the number of online-hailing vehicles in the target set that are not in a charging state in the future time period is adjusted.

7. The online car-hailing charging management method according to claim 5, characterized in that: Adjusting the number of online-hailing vehicles in the target set that are in a charging state within a target future time period and the number of online-hailing vehicles in the target set that are not in a charging state within the target future time period includes: Determine a ratio between a benefit index corresponding to the target set in the future time period and a benefit index corresponding to the target set in the target future time period; According to the ratio, the number of online-hailing vehicles in the target set that are in a charging state within the target future time period and the number of online-hailing vehicles in the target set that are not in a charging state within the target future time period are adjusted.

8. A charging management device for online car-hailing, characterized in that: include: A prediction module is used to predict the operational value of multiple online ride-hailing vehicles generated by orders in each future time period based on order information generated in the target area in multiple historical time periods; and predicting the charging value generated by charging of multiple online ride-hailing vehicles in each future time period based on charging information in a target area in multiple historical time periods; A determination module, used for establishing multiple sets based on multiple online ride-hailing vehicles in each future time period; And according to the charging value in each future time period and the operating value of multiple online-hailing vehicles, the benefit index corresponding to each set in each future time period is determined; wherein, multiple online-hailing vehicles in each set are set with different or the same charging status, and the charging status of at least one online-hailing vehicle in different sets is different; The management module is used to manage the charging status of multiple online-hailing vehicles in each future time period according to the set of benefit indicators corresponding to the first preset requirements that meet the requirements in each future time period.

9. An electronic device, characterized in that: include: Memory, used to store computer programs or instructions; A processor is used to execute the computer program or instructions in the memory so that the online car-hailing charging management method as described in any one of claims 1-7 is executed.

10. A computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by the processor, the processor is enabled to execute the online car-hailing charging management method as described in any one of claims 1-7.

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