Portable charging box rental return recommendation method, system, medium and program product

Abstract

A portable charging box rental and return recommendation method, system, medium and program product, in which the method matches a number of corresponding alternative adapted rental and return outlets in a charging map according to the charging parameters of a vehicle to be charged; determines the remaining power, current location, destination location, locations of several outlets, and weight information; determines several alternative routes respectively; determines several optional alternative routes; determines the rental price of the optional adapted portable charging box and several returnable outlets; receives the return location input by a user terminal, and generates several rental and return plans; uses a weighted average algorithm to calculate the rental and return scores corresponding to each of the several rental and return plans; sorts the several rental and return plans according to the rental and return scores to obtain a rental and return recommendation sorting table, and sends the rental and return recommendation sorting table to the user terminal. The time for recommending the rental and return of portable charging boxes is reduced, and the efficiency of user rental and return is improved.

Description

Technical Field

[0001] The present application belongs to the field of electronic digital data processing, and in particular, relates to a portable charging box rental and return recommendation method, system, medium and program product. Background Art

[0002] With the increasing global awareness of environmental protection and the transformation of energy structure, electric vehicles (EVs) are gradually gaining favor among consumers as a clean and efficient means of transportation. However, the endurance of electric vehicles and the construction of charging facilities have always been key factors restricting their popularity. In order to solve this problem, portable energy storage charging boxes came into being and became a major innovation in the field of electric vehicle charging. However, the weight of portable energy storage charging boxes will have a certain impact on the endurance of electric vehicles, so portable energy storage charging boxes are rented like power banks, which allows car owners to recharge more conveniently.

[0003] In the related art, a user terminal obtains basic information of each vehicle-mounted mobile power rental terminal through a cloud server; the user selects a designated location through the user terminal and sends a rental instruction or a return instruction based on the designated location; the vehicle-mounted mobile power rental terminal is delivered to the designated location by vehicle transportation; the cloud server sends a rental instruction or a return instruction to the control unit of the vehicle-mounted mobile power rental terminal; the control unit sends a corresponding control instruction to the mobile power drive module, and the mobile power drive module takes the mobile power out of or takes it in the charging cabinet.

[0004] However, the renter knows too little about the specific parameter information of the portable energy storage charging box that needs to be rented, and needs to spend more time to select a portable energy storage charging box that can recharge the vehicle to be charged. After the screening is completed, it may be necessary to select a portable energy storage charging box with the lowest charging cost. When returning, due to the different charging specifications of each outlet, the portable energy storage charging box that currently needs to be returned needs to be sent to a designated location, and the user needs to screen the return outlet. In summary, the recommended method for renting and returning portable charging boxes still has the problems of being too time-consuming and difficult to screen, which reduces the efficiency of user rental and return. Summary of the invention

[0005] The present application provides a portable charging box rental and return recommendation method, system, medium and program product, which are used to reduce the time for portable charging box rental and return recommendations and improve the efficiency of user rental and return.

[0006] In a first aspect, the present application provides a portable charging box rental and return recommendation method, in which, when it is determined that a network point query request sent by a user terminal is received, a number of corresponding alternative adaptive rental and return network points are matched in a charging map according to the charging parameters of the vehicle to be charged, and the alternative adaptive rental and return network points contain at least one adaptive portable charging box whose real-time status is idle;

[0007] Determine the remaining power of the vehicle to be charged, the current location, the destination location, the locations of several alternative suitable rental and return outlets, and the weight information of the suitable portable charging box with a real-time idle status;

[0008] Determine several alternative routes corresponding to several alternative adapted rental and return outlets respectively according to the current location, the destination location and the locations of several outlets;

[0009] Determine a number of optional alternative routes according to the number of alternative routes, the remaining power and the weight information, the optional alternative routes being routes that the vehicle to be charged can travel completely, and the number of optional alternative routes corresponding to a number of optional adapted rental return outlets;

[0010] Determine the rental price of each optional portable charging box with an idle real-time status among a number of optional rental and return outlets and a number of returnable outlets corresponding to the optional portable charging box;

[0011] Receive the return location input by the user terminal, and generate several rental return plans based on the optional alternative routes, rental prices, returnable outlets and return locations, the rental return plans including rental outlets, rental-adapted portable charging boxes, rental routes, total rental amounts, return outlets and return routes;

[0012] Use a weighted average algorithm to calculate the rental return score corresponding to each of the rental return plans;

[0013] The multiple rental return plans are sorted according to the rental return scores to obtain a rental return recommendation sorting table, and the rental return recommendation sorting table is sent to the user terminal.

[0014] By adopting the above technical solution, according to the charging parameters of the vehicle to be charged provided by the user, a number of alternative adapted rental and return outlets containing idle adapted portable charging boxes are matched in the charging map. By analyzing the remaining power of the vehicle to be charged, the current location, the destination location and the location information of the alternative outlets, multiple alternative routes passing through these alternative outlets can be determined. Furthermore, combined with the remaining power of the vehicle and the weight information of the portable charging box, the optional alternative routes that the vehicle can fully travel can be screened out, and the corresponding optional adapted rental and return outlets can be determined. Then, considering the user's return needs, the method receives the return location entered by the user, and comprehensively considers factors such as the optional alternative routes, the rental price of the charging box, and the returnable outlets, and generates multiple rental and return plans for the user to choose. Finally, the score of each plan is calculated by the weighted average algorithm, and a recommended ranking table is generated according to the score sorting, which is convenient for users to make the best decision. According to the vehicle charging parameters and real-time network information, it intelligently matches suitable alternative rental outlets to improve the rental efficiency. It comprehensively considers factors such as vehicle power, driving route, and charging box weight to screen out feasible alternative routes and outlets to ensure that users can complete their trips smoothly. It also takes into account the user's return needs, provides a variety of rental return plans, improves user experience, and uses weighted average score sorting to scientifically and rationally recommend the best plan to users.

[0015] In conjunction with some embodiments of the first aspect, in some embodiments, determining a plurality of selectable alternative routes according to a plurality of alternative routes, remaining power, and weight information specifically includes:

[0016] Calculate the route lengths of several alternative routes respectively;

[0017] Determine the average power consumption of the amount of electricity to be charged and the current total vehicle mass;

[0018] The average power consumption is divided by the current total vehicle mass and multiplied by the weight information to obtain the increased power consumption;

[0019] The sum of the average power consumption and the increased power consumption is determined as the final power consumption;

[0020] Divide the remaining power by the final power consumption to get the final drivable distance;

[0021] Among the several alternative routes, the routes whose route length is less than the final drivable distance length are deleted to obtain several optional alternative routes.

[0022] By adopting the above technical solution, first, by calculating the length of each alternative route, the mileage can be preliminarily evaluated. Secondly, by comprehensively considering the average power consumption of the amount of electricity to be charged and the total mass of the vehicle, and quantifying the impact of the weight of the charging box on the power consumption as increased power consumption, the actual power consumption level of the vehicle can be estimated more accurately. Then, the remaining power of the vehicle is divided by the final power consumption taking into account the impact of the weight of the charging box, and the final drivable mileage of the vehicle can be obtained. Finally, the alternative routes are compared and screened with the final drivable mileage, and infeasible routes with too long mileage are excluded to obtain several optional alternative routes. The lengths of the alternative routes are calculated separately to provide a basis for subsequent screening, and the impact of the weight of the charging box on power consumption is introduced to make the power consumption estimation closer to the actual situation. The maximum drivable mileage of the vehicle is scientifically calculated through the ratio of the remaining power to the final power consumption to avoid the risk of the vehicle running out of power halfway. The alternative routes are compared with the final drivable mileage to efficiently screen out infeasible routes and ensure the feasibility of the recommended solution.

[0023] In conjunction with some embodiments of the first aspect, in some embodiments, a number of rental return plans are generated based on the optional alternative routes, rental prices, returnable outlets, and return locations, specifically including:

[0024] Determine the rental of the portable charging box and the rental period, and determine the rental outlets based on the rental of the portable charging box;

[0025] Determine the total rental amount based on the rental period;

[0026] Determine the rental route based on the rental outlets;

[0027] Determine a number of returnable outlets corresponding to the rental of the portable charging box;

[0028] Determine a rental return plan based on the return location, destination location and a returnable outlet.

[0029] By adopting the above technical solution, first of all, by determining the rental portable charging box and the rental duration, the rental outlets and the total rental amount can be determined. Secondly, a detailed rental route can be planned according to the rental outlets. Thirdly, combined with the attributes of the charging box itself, several returnable outlets that match it can be determined. Finally, a series of complete rental return plans can be generated by comprehensively considering the return location, the established destination, and each returnable outlet provided by the user. By selecting the adapted charging box and determining the rental duration, the rental outlets and fees can be clarified, providing key decision-making information for users, planning detailed routes according to the rental outlets, allowing users to clearly understand the driving route, matching the returnable outlets corresponding to the adapted charging box, and providing users with a variety of options for return, taking into account the user's return needs, integrating information such as the destination and return location, and generating a complete rental-use-return-return full-process plan to meet user needs.

[0030] In conjunction with some embodiments of the first aspect, in some embodiments, a weighted average algorithm is used to calculate the rental return score corresponding to each of the rental return schemes, specifically including:

[0031] Obtain the rental records of the user terminal within the preset time;

[0032] Determine the weight ratios of the rental path, the total rental amount, and the return path in the rental return plan based on the rental records;

[0033] The rental return score corresponding to the rental return plan is obtained by adding the values ​​obtained by multiplying the value of the rental path by the corresponding weight ratio, the total rental amount by the corresponding weight ratio, and the value of the rental return path by the corresponding weight ratio.

[0034] By adopting the above technical solution, the user's recent rental records can be obtained to analyze the user's preference habits. Secondly, the importance of each key factor (such as rental path, total rental amount, return path, etc.) in the user's decision is determined based on historical data, and quantified as the corresponding weight ratio. Finally, the weighted average algorithm is used to multiply the key factor values ​​of each solution by the weight ratio and then sum them to obtain the comprehensive score of each solution. Based on the user's own historical behavior data, analyze user preferences and provide personalized recommendation references. The importance of key factors is quantified by weight ratio, highlighting the focus of user attention, providing targeted evaluation, and using the weighted average algorithm. A number of factors are comprehensively considered in a scientific and reasonable manner to make the scoring results more comprehensive and balanced, and each solution is uniformly converted into a comparable score, which is convenient for users to intuitively compare and quickly make choices.

[0035] In conjunction with some embodiments of the first aspect, in some embodiments, after sorting the plurality of rental return schemes according to the rental return scores to obtain a rental return recommendation ranking table, and sending the rental return recommendation ranking table to the user terminal, the method further includes:

[0036] Generate filter controls corresponding to the rental path, total rental amount, return path, and rental return score;

[0037] Added filter controls to the rental return recommendation sorting table;

[0038] In response to the user clicking the current filter control, the sorting order in the rental return recommendation sorting table is modified to sort according to the size of the sorting data corresponding to the current filter control, and the sorting data is the rental path, total rental amount, return path or rental return score.

[0039] By adopting the above technical solution, the system generates corresponding filter controls based on key information (such as rental path, total rental amount, return path, comprehensive score, etc.) and adds them to the recommended sorting table. When a user clicks on a filter control, the system can dynamically adjust the sorting order of the sorting table and re-sort it according to the data size corresponding to the selected control. By setting the filter control, key information of different dimensions can be intuitively presented to the user, which is convenient for the user to quickly understand and compare. The user can flexibly choose the sorting scheme according to their own needs and preferences, realize personalized and customized recommendation sorting, and enhance the user's dominance and satisfaction. The interactive filtering operation replaces the cumbersome parameter setting, simplifies the user's selection process, provides a smooth and convenient operation experience, dynamically adjusts the display of the sorting results, realizes real-time update of information, and helps users obtain the latest and most relevant recommendations in a timely manner.

[0040] In conjunction with some embodiments of the first aspect, in some embodiments, after sorting the plurality of rental return schemes according to the rental return scores to obtain a rental return recommendation ranking table, and sending the rental return recommendation ranking table to the user terminal, the method further includes:

[0041] In response to the user terminal selecting an operation of a rental return plan, determining a rental-adaptive portable charging box and a rental outlet in the rental return plan;

[0042] Determine the arrival time based on the current location, rental outlet, and driving speed of the vehicle to be charged;

[0043] The time period from the current time point to the arrival time point is added to the reservation list for renting an adapted portable charging box.

[0044] By adopting the above technical solution, when the user selects a rental return plan on the terminal, the system determines the rental-adaptive charging box and rental outlet in the plan. At the same time, based on the user's current location, the location of the rental outlet, and the vehicle's driving speed, the time point when the user arrives at the rental outlet can be estimated. Then, the system adds the time period from the current time to the estimated arrival time to the reservation list of the selected charging box, and reserves the charging equipment for the user in advance. By estimating the user's arrival time in advance and incorporating it into the reservation period, the availability of the charging equipment when the user arrives can be maximized, reducing the user's waiting time. The setting of the reservation list helps rental outlets to allocate equipment resources more reasonably, improve equipment utilization and operational efficiency, and seamlessly connect the entire process from user selection of the plan to actual vehicle pickup.

[0045] In combination with some embodiments of the first aspect, in some embodiments, when it is determined that a network point query request sent by a user terminal is received, a number of corresponding candidate adapted rental return network points are matched in a charging map according to charging parameters of the vehicle to be charged, specifically including:

[0046] In the case of determining that a network point query request sent by the user terminal is received, matching a number of corresponding adapted rental and return network points in the charging map according to the charging parameters of the vehicle to be charged, wherein the adapted rental and return network points include at least one adapted portable charging box;

[0047] Delete the outlets that do not contain an adaptable portable charging box with a real-time idle status from the multiple adaptable rental and return outlets to obtain multiple alternative adaptable rental and return outlets.

[0048] By adopting the above technical solution, the system matches all eligible adapted rental and return outlets in the charging map according to the vehicle charging parameters submitted by the user. These outlets all contain at least one adapted charging box that is compatible with the vehicle. Then, based on the above matching results, the system further determines the real-time status of the charging box of each adapted outlet, eliminates outlets without available equipment, and finally obtains a set of alternative outlets that meet the real-time rental needs. Make full use of vehicle parameters and charging map data to achieve accurate matching, ensure that the equipment of the alternative outlets is compatible with the vehicle model, and improve the adaptability of the rental. On the basis of preliminary matching, real-time status screening is introduced, and the range of alternative outlets is dynamically updated to ensure that the recommended results are consistent with the actual available resources, and improve the successful rental rate of users after arriving at the outlets. The two-step screening effectively balances the comprehensiveness and real-time nature of the matching, while ensuring compatibility, minimizing invalid recommendations, thereby improving the accuracy of the entire recommendation service and user experience.

[0049] In a second aspect, an embodiment of the present application provides a portable charging box rental and return recommendation system, which portable charging box rental and return recommendation system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0050] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a system, causes the system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0051] In a fourth aspect, an embodiment of the present application provides a computer program product, characterized in that when the computer program product runs on a system, the system executes the method described in any possible implementation manner in the first aspect.

[0052] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0053] 1. The present application provides a portable charging box rental and return recommendation method. According to the charging parameters of the vehicle to be charged provided by the user, a number of alternative adapted rental and return outlets containing idle adapted portable charging boxes are matched in the charging map. By analyzing the remaining power of the vehicle to be charged, the current location, the destination location and the location information of the alternative outlets, multiple alternative routes passing through these alternative outlets can be determined. Furthermore, combined with the remaining power of the vehicle and the weight information of the portable charging box, the optional alternative routes that the vehicle can fully travel can be screened out, and the corresponding optional adapted rental and return outlets can be determined. Then, considering the user's return needs, the method receives the return location entered by the user, and comprehensively considers factors such as the optional alternative routes, the rental price of the charging box, and the returnable outlets, and generates multiple rental and return plans for the user to choose. Finally, the score of each plan is calculated by the weighted average algorithm, and a recommended ranking table is generated according to the score sorting, so that the user can make the best decision. According to the vehicle charging parameters and real-time network information, it intelligently matches suitable alternative rental outlets to improve the rental efficiency. It comprehensively considers factors such as vehicle power, driving route, and charging box weight to screen out feasible alternative routes and outlets to ensure that users can complete their trips smoothly. It also takes into account the user's return needs, provides a variety of rental return plans, improves user experience, and uses weighted average score sorting to scientifically and rationally recommend the best plan to users.

[0054] 2. The present application provides a method for recommending the rental and return of a portable charging box. First, by calculating the length of each alternative route, the mileage can be preliminarily evaluated. Secondly, by comprehensively considering the average power consumption of the amount of electricity to be charged and the total mass of the vehicle, and quantifying the impact of the weight of the charging box on the power consumption as increased power consumption, the actual power consumption level of the vehicle can be estimated more accurately. Then, the remaining power of the vehicle is divided by the final power consumption that takes into account the impact of the weight of the charging box, and the final drivable mileage of the vehicle can be obtained. Finally, the alternative routes are compared and screened with the final drivable mileage, and infeasible routes with too long mileage are excluded to obtain several optional alternative routes. The lengths of the alternative routes are calculated separately to provide a basis for subsequent screening, and the impact of the weight of the charging box on power consumption is introduced to make the power consumption estimation closer to the actual situation. The maximum drivable mileage of the vehicle is scientifically calculated through the ratio of the remaining power to the final power consumption to avoid the risk of the vehicle running out of power halfway. The alternative routes are compared with the final drivable mileage to efficiently screen out infeasible routes and ensure the feasibility of the recommended solution.

[0055] 3. The present application provides a method for recommending the rental and return of a portable charging box. First, by determining the compatible portable charging box and the rental duration, the rental outlets and the total rental amount can be determined. Secondly, a detailed rental route can be planned based on the rental outlets. Thirdly, in combination with the attributes of the charging box itself, several returnable outlets that match it can be determined. Finally, a series of complete rental return plans can be generated by comprehensively considering the return location, the established destination, and each returnable outlet provided by the user. By selecting an adaptive charging box and determining the rental duration, the rental outlets and fees can be clarified, providing key decision-making information for users, and planning detailed routes based on the rental outlets so that users can clearly understand the driving route, match the returnable outlets corresponding to the adaptive charging box, and provide users with a variety of options for return, taking into account the user's return needs, integrating information such as the destination and return location, and generating a complete rental-use-return-return full-process plan to meet user needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flowchart of a recommended method for renting and returning a portable charging box in an embodiment of the present application.

[0057] Figure 2 This is another flowchart of a recommended method for renting and returning a portable charging box in an embodiment of the present application.

[0058] Figure 3 It is a schematic diagram of the physical device structure of a portable charging box rental and return recommendation system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0060] 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 the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0061] An application scenario of an embodiment of the present application is described below:

[0062] In a busy commercial district, an electric car owner was about to drive to an important business meeting in the suburbs. Before leaving, he found that his car was running low on power and might not be able to reach the meeting place. At this moment, the owner remembered the portable energy storage charging box rental service. He opened the rental app on his phone, hoping to quickly find a suitable charging box to solve the urgent problem. However, when he began to browse the charging boxes of various models and specifications, the owner found that he knew very little about these parameters and had no idea where to start. He didn't know which charging box would be compatible with his car model, nor did he know which one he could rent to fully charge his car at the fastest speed.

[0063] The owner anxiously looked through the detailed parameters of various charging boxes, trying to find the best choice. However, the numerous technical indicators and model specifications dazzled him and made it difficult to make a decision. He was worried that the charging box he chose might not be compatible with the model, or the charging efficiency might be low, thus affecting the vehicle's range performance.

[0064] After an anxious wait, the owner finally found a charging box that seemed suitable. But when he prepared to rent it, he found that the rental price of this model was much higher than other models. In order to save money, the owner had to start searching for other models of charging boxes again, hoping to find a more cost-effective option.

[0065] After several struggles, the owner finally selected a charging box and completed the rental process. He drove to a nearby rental outlet to pick up the charging box. However, when he put the charging box in the trunk, he found that the vehicle's range was significantly reduced. It turned out that the weight of the portable charging box affected the energy consumption performance of the electric vehicle.

[0066] The owner finally arrived at the meeting place and breathed a sigh of relief. But when he was ready to leave, he faced a new problem: since the charging specifications of various rental outlets were different, he needed to carefully identify which outlets were compatible with the charging box in his hand, which would undoubtedly take a lot of time and energy.

[0067] The car owner's experience is not an isolated case. As electric vehicles become increasingly popular, although the portable energy storage charging box rental service provides car owners with more charging options, there are still many inconveniences in actual use. Complex model specifications, opaque compatibility information, high rental fees, and the difficulty of screening return outlets all affect the user's rental experience. In order to solve the above technical problems, the present application provides a portable charging box rental and return recommendation method, which is used to reduce the time for portable charging box rental and return recommendations and improve the efficiency of user rental and return.

[0068] Combine the following Figure 1 , a recommended method for renting and returning a portable charging box in an embodiment of the present application is described:

[0069] See also Figure 1 , which is a flow chart of a recommended method for renting and returning a portable charging box in an embodiment of the present application.

[0070] S101, when it is determined that a network point query request sent by a user terminal is received, matching a number of corresponding candidate adapted rental return network points in a charging map according to charging parameters of the vehicle to be charged;

[0071] When the system determines that a network point query request sent by a user terminal is received, the system matches a number of corresponding alternative adaptive rental and return network points in the charging map according to the charging parameters of the vehicle to be charged. Specifically: when the system determines that a network point query request sent by a user terminal is received, the system matches a number of corresponding adaptive rental and return network points in the charging map according to the charging parameters of the vehicle to be charged, and the adaptive rental and return network points include at least one adaptive portable charging box;

[0072] Delete the outlets that do not contain an adaptable portable charging box with a real-time idle status from the multiple adaptable rental and return outlets to obtain multiple alternative adaptable rental and return outlets.

[0073] In this step, the system first determines whether it has received a network query request from the user terminal. Once the request is confirmed, the system will match the charging parameters of the vehicle to be charged in the preset charging map and filter out the rental and return network points that are compatible with the vehicle. These network points are equipped with at least one portable charging box that is compatible with the vehicle to be charged.

[0074] Next, the system further optimizes the screening results and eliminates those outlets that have matching charging boxes but are not currently available. In this way, the final list of candidate outlets can meet the user's real-time rental needs.

[0075] For example, a user drives an electric car model A, whose charging interface type is Type-2. When the system receives the user's network query request, it will search for all rental outlets equipped with Type-2 charging boxes in the charging map. Suppose three outlets numbered 001, 002, and 003 are found. However, after real-time status verification, it is found that the Type-2 charging box of outlet 002 is currently being rented by other users, so the system removes it from the candidate list. In the end, outlets 001 and 003 will be pushed to the user terminal as the final alternative outlets.

[0076] S102, determining the remaining power of the vehicle to be charged, the current location, the destination location, the locations of several alternative suitable rental and return outlets corresponding to the several network points, and the weight information of the suitable portable charging box with a real-time idle status;

[0077] The main purpose of this step is to comprehensively collect key information that affects the rental decision and prepare for subsequent path planning and solution generation.

[0078] First, the system will obtain the remaining power of the vehicle to be charged, which is the primary basis for judging whether the vehicle needs to rent a charging box. Usually, the remaining power can be read through the vehicle's battery management system (BMS). Assume that the current power of the vehicle is 30%.

[0079] Secondly, the system will obtain the current location of the vehicle and the destination location set by the user. Through GPS positioning or the vehicle navigation system, the current geographic coordinates of the vehicle can be accurately located, such as (39.54, 116.28). The destination coordinates entered by the user, such as (40.32, 115.67), indicate the end point of this trip.

[0080] Next, the system will extract the location information of several candidate rental and return outlets selected in the previous step. The coordinate data of these outlets are usually stored in the system's POI (Point of Interest) database.

[0081] Finally, the system also obtains the weight information of the available charging boxes in each candidate outlet. The weight data of the charging box is usually maintained in the device management system, and the weight of different models of charging boxes is different. For example, the charging box of model A weighs 20kg, model B weighs 25kg, and model C weighs 30kg.

[0082] S103, determining a number of alternative routes corresponding to a number of alternative adapted rental and return outlets according to the current location, the destination location and the locations of a number of outlets;

[0083] In this step, the system will plan multiple possible travel routes based on the vehicle's current location, the user's destination location, and the geographic coordinates of the alternative rental outlets. The core of this step is the path planning algorithm, which provides users with the best travel path by comprehensively considering factors such as distance, time, and road conditions.

[0084] Specifically, the system will analyze the route plan from the current location to each alternative outlet, and then from the outlet to the destination. Taking a certain outlet as an example, the system will collect real-time traffic information of the surrounding roads, including road conditions, traffic flow, speed limit signs, etc. Combined with the vehicle's driving speed and range, the system will calculate the estimated time and power consumption to reach the outlet.

[0085] Assume that the user is currently in A and plans to go to B, and the alternative network point X is located between A and B. The system calculates that the two sections from A to X and from X to B are 20km and 30km respectively. At the same time, based on real-time traffic analysis, the estimated driving time is 0.5 hours and 1 hour respectively, and the power consumption is 10% and 15% respectively.

[0086] After completing the analysis of a single node path, the system will traverse all candidate nodes and generate a set of potential driving routes. Taking three candidate nodes X, Y, and Z as an example, the possible route combinations include: AXB, AYB, and AZB.

[0087] The key technology of this step is that through the path planning algorithm and real-time traffic data analysis, the system can plan the best driving route for users. This can not only save time and reduce energy consumption, but also maximize driving safety.

[0088] S104, determining a number of optional alternative routes according to the number of alternative routes, the remaining power and the weight information, where the optional alternative routes are routes that the vehicle to be charged can travel completely;

[0089] The system determines several optional alternative routes based on several alternative routes, remaining power and weight information. The optional alternative routes are routes that the vehicle to be charged can travel completely. Several optional alternative routes correspond to several optional adapted rental and return outlets. Specifically: calculate the route lengths of several alternative routes respectively;

[0090] Determine the average power consumption of the amount of electricity to be charged and the current total vehicle mass;

[0091] The average power consumption is divided by the current total vehicle mass and multiplied by the weight information to obtain the increased power consumption;

[0092] The sum of the average power consumption and the increased power consumption is determined as the final power consumption;

[0093] Divide the remaining power by the final power consumption to get the final drivable distance;

[0094] Among the several alternative routes, the routes whose route length is less than the final drivable distance length are deleted to obtain several optional alternative routes.

[0095] In this step, the system will further select feasible routes that match the actual driving range of the vehicle from the alternative routes generated in the previous step. The core of this step is mileage calculation, which determines the feasibility of each alternative route by comparing the route length with the vehicle's mileage.

[0096] First, the system extracts the distance data of each alternative route, including the driving distance from the current location to the rental outlet, and from the outlet to the destination. Taking three alternative routes as an example, their distance data are:

[0097] Route 1: AXB, 50km (20km+30km)

[0098] Route 2: AYB, 60km (25km+35km)

[0099] Route 3: AZB, 55km (25km+30km)

[0100] Next, the system will calculate the vehicle's mileage under different operating conditions based on the vehicle's remaining power, taking into account factors such as the vehicle's average power consumption (kWh / 100km) and load capacity.

[0101] Assume that the remaining power of vehicle A is 30%, the range when fully charged is 200km, the vehicle weight is 1.5 tons, and the average power consumption is 15 kWh / 100km. If a charging box weighing 200kg is selected, the load capacity will increase to 1.7 tons.

[0102] According to the changes in power consumption and load, the system calculates that an increase of 200kg in load will increase power consumption by 2 kWh per 100 km. Therefore, the current average power consumption will reach 17 kWh / 100 km. Combined with the remaining power, it can be calculated that the actual mileage of vehicle A is about 35 km.

[0103] Comparing this drivable mileage with the distance data of the alternative routes, it is found that only route 1 has a total mileage of less than 35km. Therefore, the system marks route 1 as an optional route, and excludes routes 2 and 3 from the recommendation list. The rental point X corresponding to route 1 will also be marked as an optional point, and a rental plan will be generated in the next step.

[0104] S105, determining a rental price of each optional portable charging box with an idle real-time status among a plurality of optional rental and return outlets and a plurality of returnable outlets corresponding to the optional portable charging box;

[0105] In this step, the system will focus on the optional rental outlets selected in the previous step, extracting the price information of the idle charging boxes in each outlet and the potential return location data. The goal of this step is to provide users with comprehensive and transparent price comparisons and return previews, and improve the flexibility and convenience of rental decisions.

[0106] First, the system will access the device management database of the optional outlets and read the rental standards of the currently available charging boxes. The rental prices of charging boxes of different models and different power levels may be different.

[0107] Take optional outlet No. X as an example, assuming that it currently has three idle charging boxes:

[0108] Model A: 400 yuan / day, 80% power

[0109] Model B: 500 yuan / day, 100% power

[0110] Model C: 450 yuan / day, 90% power

[0111] The system will extract this price information and indicate the corresponding charging box model and power status to form a complete rental quotation list. Users can flexibly choose the most suitable rental plan based on their budget and mileage requirements.

[0112] Next, the system will also identify potential return outlets for each optional charging box. Since different models of charging boxes may be compatible with different return facilities, the system needs to establish a matching relationship between charging boxes and return outlets.

[0113] Continuing with branch X as an example, assume that:

[0114] Model A charging boxes can be returned at P, Q, and R outlets

[0115] Model B charging box can be returned at S, T, and U outlets

[0116] Model C charging boxes can be returned at V, W, and X outlets

[0117] The system will generate a return preview table, listing the return points corresponding to each optional charging box. Users can plan their return trip in advance and choose the most convenient return location.

[0118] S106, receiving the return location input by the user terminal, and generating several rental return plans according to the optional alternative routes, rental prices, returnable outlets and return locations;

[0119] The system receives the return location input by the user terminal, and generates several rental return plans based on the optional alternative routes, rental prices, returnable outlets and return locations, specifically: determining the rental-compatible portable charging box and rental duration, and determining the rental outlet based on the rental-compatible portable charging box;

[0120] Determine the total rental amount based on the rental period;

[0121] Determine the rental route based on the rental outlets;

[0122] Determine a number of returnable outlets corresponding to the rental of the portable charging box;

[0123] Determine a rental return plan based on the return location, destination location and a returnable outlet.

[0124] In this step, the system will further combine the user's return needs to generate a series of personalized rental and return plans. The user can enter the expected return destination through the terminal device, and the system will match the most suitable rental outlets, return outlets and driving routes based on this.

[0125] Specifically, the system will first determine the best rental combination based on the information obtained in the previous steps, such as the available routes, charging box models and prices, etc. Here, it is necessary to comprehensively evaluate factors such as the length of the lease and the total rent to balance convenience and economy.

[0126] Assuming that the user plans to rent a model A charging box for 2 days at a daily rental fee of 400 yuan, the total rental amount is 800 yuan. At the same time, based on the optional route data, the system determines the nearest rental outlet X and the corresponding driving route.

[0127] Next, the system will extract a list of return points, such as P, Q, R, etc., based on the compatibility information of the charging box model A. Combined with the return location C entered by the user, the system will evaluate the convenience of each return point.

[0128] For example, if the user plans to return from destination B to destination C, and the P outlet is located between B and C, without detour, then the P outlet is the most convenient for return. Based on this, the system generates a complete rental and return plan: rent a model A charging box at X outlet for 2 days, the fee is 800 yuan, the driving route is XAB, the return outlet is P, and the return route is BPC.

[0129] S107, using a weighted average algorithm to calculate the rental return score corresponding to each of the rental return plans;

[0130] After generating several rental and return plans, the system will further use a weighted average algorithm to quantitatively evaluate and score each plan. The goal of this step is to establish a scientific and fair evaluation system to help users objectively compare the comprehensive benefits of different plans.

[0131] The basic principle of the weighted average algorithm is to assign different weight coefficients to different evaluation indicators according to their importance, and then add up the weighted scores of each indicator to obtain the final comprehensive score. This method can balance the pros and cons of multiple dimensions and objectively reflect the overall value of the solution.

[0132] In the evaluation of the rental return plan, the core indicators that need to be considered include: time cost, economic cost, convenience, etc. Take a certain plan as an example, assuming that its time cost is 2 hours (weight 0.4), the rental cost is 800 yuan (weight 0.3), and the return convenience is 8 points (out of 10 points, weight 0.3).

[0133] According to the weighted average algorithm, the comprehensive score of the plan = 2×0.4+800 / 100×0.3+8×0.3=3.64 points.

[0134] S108. Sort the multiple rental return plans according to the rental return scores to obtain a rental return recommendation ranking table, and send the rental return recommendation ranking table to the user terminal.

[0135] After the plan generation and scoring is completed, the system will sort all the plans according to the comprehensive scores in this step to generate an optimized rental and return recommendation ranking list. This ranking list will present the best and most suitable travel plan combination to users in an intuitive and easy-to-read form.

[0136] Specifically, the system will extract the scoring results of each solution and arrange them in order from high to low. Take 4 solutions as an example, assuming that their comprehensive scores are:

[0137] Option 1: 4.2 points

[0138] Option 2: 3.8 points

[0139] Option 3: 4.5 points

[0140] Option 4: 3.6 points

[0141] The recommended ranking list for rental returns generated by the system will be: Plan 3, Plan 1, Plan 2, Plan 4.

[0142] Next, the system will present the ranking results to the user terminal in real time in the form of push notifications, APP lists, etc. Users can intuitively view the ranking, score and key information of each plan (such as rental outlets, return locations, cost estimates, etc.), and choose the most desired travel plan based on their actual needs and preferences.

[0143] The above embodiments have the following beneficial effects:

[0144] According to the charging parameters of the vehicle to be charged provided by the user, several alternative adapted rental and return outlets containing idle adapted portable charging boxes are matched in the charging map. By analyzing the remaining power of the vehicle to be charged, the current location, the destination location and the location information of the alternative outlets, multiple alternative routes passing through these alternative outlets can be determined. Furthermore, combined with the remaining power of the vehicle and the weight information of the portable charging box, the optional alternative routes that the vehicle can fully travel can be screened out, and the corresponding optional adapted rental and return outlets can be determined. Then, considering the user's return needs, the method receives the return location entered by the user, and comprehensively considers factors such as the optional alternative routes, the rental price of the charging box, and the returnable outlets, and generates multiple rental and return plans for the user to choose. Finally, the score of each plan is calculated by the weighted average algorithm, and a recommended ranking table is generated according to the score sorting, so that the user can make the best decision. According to the vehicle charging parameters and real-time network information, it intelligently matches suitable alternative rental outlets to improve the rental efficiency. It comprehensively considers factors such as vehicle power, driving route, and charging box weight to screen out feasible alternative routes and outlets to ensure that users can complete their trips smoothly. It also takes into account the user's return needs, provides a variety of rental return plans, improves user experience, and uses weighted average score sorting to scientifically and rationally recommend the best plan to users.

[0145] First, by calculating the length of each alternative route, the mileage can be preliminarily evaluated. Secondly, by comprehensively considering the average power consumption of the amount of electricity to be charged and the total mass of the vehicle, and quantifying the impact of the weight of the charging box on the power consumption as an increase in power consumption, the actual power consumption level of the vehicle can be estimated more accurately. Then, the remaining power of the vehicle is divided by the final power consumption that takes into account the impact of the weight of the charging box, and the final drivable mileage of the vehicle can be obtained. Finally, the alternative routes are compared and screened with the final drivable mileage, and infeasible routes with too long mileage are excluded to obtain several optional alternative routes. The lengths of the alternative routes are calculated separately to provide a basis for subsequent screening, and the impact of the weight of the charging box on power consumption is introduced to make the power consumption estimation closer to the actual situation. The maximum drivable mileage of the vehicle is scientifically calculated through the ratio of the remaining power to the final power consumption to avoid the risk of the vehicle running out of power halfway. The alternative routes are compared with the final drivable mileage to efficiently screen out infeasible routes and ensure the feasibility of the recommended solution.

[0146] First, by determining the compatible portable charging box and the rental duration, the rental outlets and the total rental amount can be determined. Secondly, a detailed rental route can be planned based on the rental outlets. Thirdly, combined with the attributes of the charging box itself, several matching return outlets can be determined. Finally, a series of complete rental return plans can be generated by comprehensively considering the return location, the established destination, and each returnable outlet provided by the user. By selecting the compatible charging box and determining the rental duration, the rental outlets and fees can be clarified, providing key decision-making information for users, planning detailed routes based on the rental outlets, allowing users to clearly understand the driving route, matching the returnable outlets corresponding to the compatible charging box, and providing users with a variety of options for return, taking into account the user's return needs, integrating information such as the destination and return location, and generating a complete rental-use-return-return full-process plan to meet user needs.

[0147] Based on the vehicle charging parameters submitted by the user, the system matches all eligible rental and return outlets in the charging map. These outlets all contain at least one compatible charging box for compatible vehicles. Then, based on the above matching results, the system further determines the real-time status of the charging box of each compatible outlet, eliminates outlets without available equipment, and finally obtains a set of alternative outlets that meet real-time rental needs. Make full use of vehicle parameters and charging map data to achieve accurate matching, ensure that the equipment of the alternative outlets is compatible with the vehicle model, and improve the adaptability of the rental. On the basis of preliminary matching, real-time status screening is introduced, and the range of alternative outlets is dynamically updated to ensure that the recommended results are consistent with the actual available resources, thereby improving the successful rental rate of users after arriving at the outlets. The two-step screening effectively balances the comprehensiveness and real-time nature of the matching, while ensuring compatibility, minimizing invalid recommendations, thereby improving the accuracy of the entire recommendation service and user experience.

[0148] This embodiment will describe in detail the step of using the weighted average algorithm to calculate the rental return score corresponding to each of the rental return schemes in S107 with reference to a specific example. Figure 2 , another recommended method for renting and returning a portable charging box in an embodiment of the present application is described:

[0149] See also Figure 2 , which is another flow chart of a recommended method for renting and returning a portable charging box in an embodiment of the present application.

[0150] S201, obtaining rental records of a user terminal within a preset time period;

[0151] In this step, the system will obtain historical rental data of the user terminal within a certain time range to gain in-depth insights into the user's real rental behavior and preference characteristics. This is the basis and prerequisite for achieving personalized recommendations.

[0152] Specifically, the system will retrieve all rental records within a certain period of time (such as 30 days) based on the unique identifier such as the user ID. These records will contain key information such as rental time, start and end locations, usage duration, fees, charging box model, etc.

[0153] Assume that user A has 5 rental records in the past 30 days:

[0154] Record 1: January 1, from X to Y, rental time 2 hours, fee 20 yuan, rental of Model A charging box

[0155] Record 2: January 5, from P to Q, rental time 6 hours, fee 50 yuan, rental of Model B charging box

[0156] Record 3: January 12, from M to N, rental time 4 hours, cost 30 yuan, rental of C-type charging box

[0157] Record 4: January 20, from X to Z, rental time 3 hours, fee 25 yuan, rental of Model A charging box

[0158] Record 5: January 28, from S to T, rental time 2 hours, fee 15 yuan, rental of Model B charging box

[0159] The system will summarize these records and extract key features, such as average rental duration, cost level, preferred route, and charging box model. This information will become an important basis for the subsequent generation of personalized rental return plans.

[0160] S202, determining the weight ratios of the rental path, the total rental amount, and the return path in the rental return plan according to the rental records;

[0161] This step will calculate the weights of key factors such as rental path, total rental amount, and return path based on the user's historical rental records through statistical analysis and other data mining techniques. This is the core link in building a rental return scoring model.

[0162] Specifically, the system will sort out the rental records of all users and extract the following key features:

[0163] Rental path: statistics on the frequency of occurrence of different starting and ending location combinations, average rental duration, etc.

[0164] Total rental amount: statistics on the distribution, average, median, etc. of different cost ranges;

[0165] Return path: Statistics on the preference of different return locations, distance from the destination, etc.

[0166] Then, the system will evaluate the importance of these features based on business scenarios and expert experience, and calculate their contribution weights to user satisfaction. For example, through analysis, it was found that:

[0167] The convenience of the rental route has the greatest impact on satisfaction, accounting for 40%;

[0168] The total rental amount has the second greatest impact on satisfaction, accounting for 35%;

[0169] The flexibility of the return path has a relatively small impact on satisfaction, accounting for 25%.

[0170] S203. Add the values ​​obtained by multiplying the value of the rental path by the corresponding weight ratio, the total rental amount by the corresponding weight ratio, and the value of the rental return path by the corresponding weight ratio to obtain a rental return score corresponding to the rental return plan.

[0171] This step will comprehensively apply the personalized scoring model built earlier to evaluate and score each rental and return plan generated by the system. This is the last mile of the intelligent recommendation engine and is directly related to the quality of the recommendation effect.

[0172] Specifically, for each solution, the system will extract its key features, including:

[0173] Rental route: actual starting and ending locations, estimated duration, etc.

[0174] Total amount of the lease: amount before discounts, coupons, final fees, etc.

[0175] Return path: suggested return points, user preferred locations, etc.

[0176] The system will then calculate the standardized score for each feature. Taking the rental route as an example, factors such as congestion coefficient and number of POIs can be considered, and a horizontal evaluation result of 0-10 points can be obtained through weighted summation.

[0177] Assume that the scores of a set of solutions are as follows:

[0178] Loan Path Score: 8.5

[0179] Total rental amount score: 7.0 points

[0180] Return Path Score: 9.0

[0181] At the same time, the personalized weight proportion corresponding to the user is:

[0182] Rental path weight: 40%

[0183] Total rental amount weight: 35%

[0184] Return path weight: 25%

[0185] According to the weighted average scoring model, the final score of the solution is:

[0186] 0.4×8.5+0.35×7+0.25×9.0=8.075 points

[0187] The system will perform similar calculations on all recommended solutions and derive quantitative evaluation scores. This is the essence of intelligent recommendation: through algorithm empowerment, the optimal option can be efficiently identified from a large number of solution combinations.

[0188] The above embodiments have the following beneficial effects:

[0189] By obtaining the user's recent rental records, the user's preference habits can be analyzed. Secondly, determine the importance of each key factor (such as rental path, total rental amount, return path, etc.) in the user's decision-making based on historical data, and quantify it into the corresponding weight ratio. Finally, use the weighted average algorithm to multiply the key factor values ​​of each plan by the weight ratio and then sum them to get the comprehensive score of each plan. Based on the user's own historical behavior data, analyze user preferences and provide personalized recommendation references. Quantify the importance of key factors through weight ratios to highlight the user's focus and provide targeted evaluations. Use the weighted average algorithm to scientifically and rationally consider multiple factors to make the scoring results more comprehensive and balanced, and convert each plan into a comparable score, which is convenient for users to compare intuitively and make choices quickly. Then a typical weighted average scoring model is constructed:

[0190] Rental return score = 0.4 × rental path score + 0.35 × total rental amount score + 0.25 × return path score.

[0191] Take a user's rental as an example. Assume that based on his historical preferences, the system gives the following prediction:

[0192] Rental route XY, the convenience score is 8 points (out of 10 points);

[0193] The total rental amount is 80 yuan, and the cost-effectiveness score is 7 points;

[0194] Return path YZ, flexibility score is 9 points.

[0195] Substituting into the model, the rental return score of this plan = 0.4×8+0.35×7+0.25×9=8.0 points.

[0196] In addition, after sorting the several rental return plans according to the rental return scores to obtain a rental return recommendation sorting table, and sending the rental return recommendation sorting table to the user terminal, the system generates filter controls corresponding to the rental path, the total rental amount, the return path, and the rental return score;

[0197] Added filter controls to the rental return recommendation sorting table;

[0198] In response to the user clicking the current filter control, the sorting order in the rental return recommendation sorting table is modified to sort according to the size of the sorting data corresponding to the current filter control, and the sorting data is the rental path, total rental amount, return path or rental return score.

[0199] In the above embodiment, the system generates corresponding filter controls based on key information (such as rental path, total rental amount, return path, comprehensive score, etc.), and adds them to the recommended sorting table. When a user clicks on a filter control, the system can dynamically adjust the order of the sorting table and re-sort it according to the data size corresponding to the selected control. By setting the filter controls, key information of different dimensions can be intuitively presented to the user, which is convenient for the user to quickly understand and compare. The user can flexibly choose the sorting scheme according to their own needs and preferences, realize personalized and customized recommendation sorting, and enhance the user's dominance and satisfaction. The interactive filtering operation replaces the cumbersome parameter setting, simplifies the user's selection process, provides a smooth and convenient operation experience, dynamically adjusts the display of the sorting results, realizes real-time updating of information, and helps users obtain the latest and most relevant recommendation schemes in a timely manner.

[0200] In addition, after sorting the several rental return plans according to the rental return scores to obtain a rental return recommendation ranking table, and sending the rental return recommendation ranking table to the user terminal, the system determines the rental-adaptive portable charging box and rental outlet in the rental return plan in response to the user terminal's operation of selecting the rental return plan;

[0201] Determine the arrival time based on the current location, rental outlet, and driving speed of the vehicle to be charged;

[0202] The time period from the current time point to the arrival time point is added to the reservation list for renting an adapted portable charging box.

[0203] In the above embodiment, when the user selects a rental return plan on the terminal, the system determines the rental-adaptive charging box and rental outlet in the plan. At the same time, based on the user's current location, the location of the rental outlet, and the speed of the vehicle, the time point when the user arrives at the rental outlet can be estimated. Then, the system adds the time period from the current time to the estimated arrival time to the reservation list of the selected charging box, and reserves the charging equipment for the user in advance. By estimating the user's arrival time in advance and incorporating it into the reservation period, the availability of the charging equipment when the user arrives can be maximized, reducing the user's waiting time. The setting of the reservation list helps the rental outlets to allocate equipment resources more reasonably, improve equipment utilization and operational efficiency, and seamlessly connect the entire process from user selection of the plan to actual vehicle pickup.

[0204] The following describes the system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the physical device structure of a portable charging box rental and return recommendation system provided in an embodiment of the present application.

[0205] It should be noted that Figure 3 The structure of the system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0206] like Figure 3 As shown, the system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through a bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0207] The following components are connected to the I / O interface 305: an input section 306 including a camera, an infrared sensor, etc.; an output section 307 including a liquid crystal display (LCD) and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0208] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0209] It should be noted that the computer-readable medium shown in the embodiment of the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.

[0210] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0211] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the system described in the above embodiment; or may exist independently without being assembled into the system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of a system, the system implements the method provided in the above embodiment.

[0212] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0213] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0214] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0215] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A portable charging box rental and return recommendation method, characterized in that: include: In the case of determining that a network point query request sent by the user terminal is received, matching a number of corresponding alternative adaptive rental and return network points in the charging map according to the charging parameters of the vehicle to be charged, wherein the alternative adaptive rental and return network points contain at least one adaptive portable charging box with a real-time idle status; Determine the remaining power of the vehicle to be charged, the current location, the destination location, the locations of several network points corresponding to the several candidate adapted rental and return network points, and the weight information of the adapted portable charging box whose real-time status is idle; Determining a plurality of alternative routes corresponding to the plurality of alternative adapted rental and return outlets according to the current location, the destination location, and the plurality of outlet locations, specifically includes: Calculating the route lengths of the plurality of alternative routes respectively; Determine the average power consumption and current total vehicle mass of the vehicle to be charged; The average power consumption is divided by the current total vehicle mass, and the result is multiplied by the weight information to obtain the increased power consumption; Determine the sum of the average power consumption and the increased power consumption as the final power consumption; Divide the remaining power by the final power consumption to obtain the final drivable distance; Deleting routes whose route lengths are shorter than the final drivable distance from the plurality of alternative routes, to obtain a plurality of optional alternative routes; Determine a plurality of optional alternative routes according to the plurality of alternative routes, the remaining power and the weight information, wherein the optional alternative routes are routes that the vehicle to be charged can travel completely, and the plurality of optional alternative routes correspond to a plurality of optional adapted rental and return outlets, specifically including: In the case of determining that a network point query request sent by the user terminal is received, matching a number of corresponding adapted rental and return network points in the charging map according to the charging parameters of the vehicle to be charged, wherein the adapted rental and return network points include at least one adapted portable charging box; Deleting the outlets that do not contain the adapted portable charging box whose real-time status is idle from the plurality of adapted rental and return outlets, to obtain a plurality of candidate adapted rental and return outlets; Determine the rental price of each optional portable charging box with an idle real-time status among the plurality of optional rental and return outlets and the plurality of returnable outlets corresponding to the optional portable charging box; Receiving the return location input by the user terminal, and generating a plurality of rental return plans according to the optional alternative routes, the rental price, the returnable outlets and the return location, the rental return plans including the rental outlets, the rental-adapted portable charging box, the rental route, the total rental amount, the return outlets and the return route; Calculate the rental return score corresponding to each of the several rental return plans using a weighted average algorithm; Sorting the plurality of rental return plans according to the rental return scores to obtain a rental return recommendation ranking table, and sending the rental return recommendation ranking table to the user terminal; In response to the user terminal selecting an operation of a rental return plan, determining a rental-adaptive portable charging box and a rental outlet in the rental return plan; Determining an arrival time point according to the current location, the rental outlet, and the driving speed of the vehicle to be charged; The time period from the current time point to the arrival time point is added to the reservation list for renting the adapted portable charging box.

2. The method according to claim 1, characterized in that The generating of a plurality of rental return plans according to the optional alternative routes, the rental price, the returnable outlets and the return location specifically includes: Determine the rental of a suitable portable charging box and the rental period, and determine a rental outlet based on the rental of the suitable portable charging box; Determine the total rental amount based on the rental period; Determining a rental route according to the rental outlets; Determine a number of returnable outlets corresponding to the rental adapted portable charging box; A rental return plan is determined based on the return location, the destination location and a returnable network point.

3. The method according to claim 1, characterized in that The using of a weighted average algorithm to calculate the rental return score corresponding to each of the plurality of rental return schemes specifically includes: Obtaining rental records of the user terminal within a preset time period; Determine the weight ratio of the rental path, the total rental amount and the return path in the rental return plan according to the rental record; The values ​​obtained by multiplying the value of the rental path by the corresponding weight ratio, the total rental amount by the corresponding weight ratio, and the value of the rental return path by the corresponding weight ratio are added together to obtain the rental return score corresponding to the rental return plan.

4. The method according to claim 1, characterized in that: After sorting the plurality of rental return schemes according to the rental return scores to obtain a rental return recommendation ranking table, and sending the rental return recommendation ranking table to the user terminal, the method further includes: Generate a filter control corresponding to the rental path, the total rental amount, the return path, and the rental return score; Adding the filter control to the rental return recommendation ranking table; In response to the user clicking on the current filter control, the arrangement order in the rental return recommendation sorting table is modified to be sorted according to the size of the arrangement data corresponding to the current filter control, and the arrangement data is the rental path, the total rental amount, the return path or the rental return score.

5. A portable charging box rental and return recommendation system, characterized in that: The system comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the system to execute the method as described in any one of claims 1-4.

6. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a system, the system is caused to execute the method according to any one of claims 1 to 4.

7. A computer program product, characterized in that When the computer program product is run on a system, the system is caused to execute the method according to any one of claims 1 to 4.

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