Energy instant delivery service platform and implementation method

Abstract

The application discloses an energy instant distribution service platform and an implementation method, and particularly relates to the technical field of intelligent scheduling; the platform receives the battery replacement service order sent by an electric vehicle, extracts the electric vehicle position information and the battery demand information, analyzes the power supply demand characteristics of the electric vehicle, executes demand matching evaluation to determine the demand priority, obtains the demand analysis result, executes distribution feasibility evaluation to generate a matching scheme, obtains the preliminary distribution plan, combines the demand analysis result and the resource state information, executes distribution feasibility evaluation to generate a matching scheme, obtains the preliminary distribution plan, optimizes the distribution path and the scheduling time sequence, generates the optimized distribution scheme, executes the distribution scheduling instruction according to the optimized distribution scheme to trigger the distribution vehicle to execute the battery replacement service, and realizes the efficient and intelligent energy distribution service of the new energy electric vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent scheduling, and more particularly, to an energy instant delivery service platform and implementation method. BACKGROUND

[0002] With the rapid popularization of new energy vehicles, higher requirements are put forward for battery replacement and energy supply services in cities.

[0003] The existing energy delivery mode generally has problems such as untimely response, unreasonable delivery path, low resource scheduling efficiency, and inability to dynamically adjust service plans according to real-time positions of electric vehicles and battery needs, resulting in long user waiting time, low energy utilization rate, and serious waste of transportation capacity, which is difficult to meet the energy supply needs in multiple scenarios, multiple time periods, and high concurrency. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide an energy instant delivery service platform and implementation method to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0006] An energy instant delivery service implementation method, comprising the following steps:

[0007] S1: receiving a battery replacement service order from an electric vehicle, including electric vehicle position information and battery demand information;

[0008] S2: based on the electric vehicle position information and the battery demand information, analyzing the power supply demand characteristics of the electric vehicle, performing demand matching evaluation to determine the demand priority, and obtaining a demand analysis result;

[0009] S3: based on the electric vehicle position information and the battery demand information, querying the available battery information and the delivery resource state in the power supply inventory database, performing inventory availability check to evaluate the resource matching, and obtaining resource state information;

[0010] S4: according to the demand analysis result and the resource state information, performing delivery feasibility evaluation to generate a matching scheme, and obtaining a preliminary delivery plan;

[0011] S5: based on the preliminary delivery plan, optimizing the delivery path and scheduling time sequence, and obtaining an optimized delivery scheme;

[0012] S6, according to the optimized delivery scheme, executing delivery scheduling instructions to trigger the action of the delivery vehicle.

[0013] In a preferred embodiment, S1, specifically:

[0014] Receive the battery swap service order sent by the electric vehicle, wherein the battery swap service order comprises real-time position information and battery demand information of the electric vehicle.

[0015] In a preferred embodiment, the battery demand information comprises the type of the battery, the specification parameter of the battery, and the quantity of the battery demand.

[0016] In a preferred embodiment, S2 specifically comprises:

[0017] Based on the position information of the electric vehicle and the battery demand information, the battery demand of the electric vehicle is analyzed, and the battery demand level corresponding to the electric vehicle is determined according to the type of the battery, the specification parameter of the battery, and the quantity of the battery demand.

[0018] According to the battery demand level, the demand matching evaluation of the battery demand of the electric vehicle is performed, the priority of the battery demand is determined, and the battery demand analysis result is obtained.

[0019] In a preferred embodiment, S3 specifically comprises:

[0020] Based on the position information of the electric vehicle and the battery demand information, the power supply inventory database is queried to obtain the available battery information corresponding to the battery demand information in the power supply inventory database;

[0021] The distribution resource database is queried to obtain the real-time position of the distribution vehicle, the current carrying capacity of the distribution vehicle, and the real-time task execution state of the distribution vehicle;

[0022] The available battery information obtained from the power supply inventory database is subjected to inventory availability check to determine the available state of the battery inventory;

[0023] The real-time position of the distribution vehicle, the current carrying capacity of the distribution vehicle, and the real-time task execution state of the distribution vehicle are subjected to distribution resource state evaluation to determine the available state of the distribution resource;

[0024] According to the available state of the battery inventory and the available state of the distribution resource, the resource state information is obtained.

[0025] In a preferred embodiment, S4 specifically comprises:

[0026] Based on the battery demand priority in the battery demand analysis result, the priority order of the battery distribution is determined;

[0027] Based on the available state of the battery inventory and the available state of the distribution resource in the resource state information, the distribution resource matching evaluation is performed;

[0028] According to the distribution resource matching evaluation result and the priority order of the battery distribution, the distribution feasibility evaluation is performed to determine the distribution vehicle satisfying the battery demand and the corresponding battery information, and the preliminary distribution plan is generated.

[0029] In one preferred embodiment, S5, specifically:

[0030] Based on the preliminary distribution plan, a distribution path optimization model is established;

[0031] Based on the distribution path optimization model, the optimized distribution route of the distribution vehicle from the current real-time position to the electric vehicle position is determined;

[0032] According to the optimized distribution route, the distribution sequence of the distribution vehicle and the scheduling timing of the distribution task are determined;

[0033] Based on the distribution sequence of the distribution vehicle and the scheduling timing of the distribution task, the optimized distribution scheme is generated.

[0034] In one preferred embodiment, S6, specifically:

[0035] According to the optimized distribution scheme, the distribution scheduling instruction is sent to the distribution vehicle;

[0036] After receiving the distribution scheduling instruction, the distribution vehicle executes the distribution task according to the distribution sequence and the optimized distribution route.

[0037] In one preferred embodiment, the distribution scheduling instruction includes the battery type, battery specification parameters, battery demand quantity, distribution sequence of the distribution vehicle, and optimized distribution route that the distribution vehicle needs to distribute.

[0038] On the other hand, the present application provides an energy instant distribution service platform, comprising:

[0039] Order receiving module: receiving the battery replacement service order from the electric vehicle, including the electric vehicle position information and the battery demand information;

[0040] Demand analysis module: based on the electric vehicle position information and the battery demand information, analyzing the power supply demand characteristics of the electric vehicle, performing demand matching evaluation to determine the demand priority, and obtaining the demand analysis result;

[0041] Resource query module: based on the electric vehicle position information and the battery demand information, querying the available battery information and distribution resource state in the power supply inventory database, performing inventory availability check to evaluate resource matching, and obtaining resource state information;

[0042] Feasibility evaluation module: according to the demand analysis result and the resource state information, performing distribution feasibility evaluation to generate a matching scheme, and obtaining a preliminary distribution plan;

[0043] Path optimization module: based on the preliminary distribution plan, optimizing the distribution path and scheduling timing, and obtaining the optimized distribution scheme;

[0044] The scheduling execution module executes the distribution scheduling instruction to trigger the distribution vehicle action according to the optimized distribution scheme.

[0045] The technical effects and advantages of the energy instant distribution service platform and the implementation method are as follows:

[0046] By receiving the battery replacement service order sent by the electric vehicle in real time, the instant response of the service is ensured; by analyzing the electric vehicle position information and the battery demand information, the demand priority is reasonably evaluated, and differentiated scheduling is realized; by dynamically querying the inventory and distribution resource state and performing matching check, the resource utilization efficiency is improved; based on the demand analysis result and the resource state information, a preliminary distribution plan is generated to ensure reasonable task allocation; the preliminary distribution plan is optimized in terms of distribution path and scheduling time sequence, and the optimized distribution scheme is obtained to effectively shorten the distribution time and reduce the operation cost; according to the optimized distribution scheme, the distribution scheduling instruction is executed to drive the distribution vehicle to accurately perform the task, realize the whole-process collaborative control from demand receiving to task completion, and improve the instantaneity, intelligence and reliability of the energy distribution. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 The figure is a schematic diagram of the energy instant distribution service implementation method of the present application.

[0048] Figure 2 The figure is a schematic diagram of the structure of the energy instant distribution service platform of the present application. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application. Embodiment 1

[0050] Figure 1 The energy instant distribution service implementation method of the present application is given, which includes the following steps:

[0051] S1: receiving the battery replacement service order from the electric vehicle, including the electric vehicle position information and the battery demand information;

[0052] S2: based on the electric vehicle position information and the battery demand information, analyzing the power supply demand characteristics of the electric vehicle, performing demand matching evaluation to determine the demand priority, and obtaining the demand analysis result;

[0053] S3: Based on the electric vehicle location information and the battery demand information, query the available battery information and the distribution resource state in the power source inventory database, perform inventory availability check to evaluate resource matching, and obtain resource state information;

[0054] S4: According to the demand analysis result and the resource state information, perform distribution feasibility evaluation to generate a matching scheme, and obtain a preliminary distribution plan;

[0055] S5: Based on the preliminary distribution plan, optimize the distribution path and scheduling sequence, and obtain the optimized distribution scheme;

[0056] S6, according to the optimized distribution scheme, execute the distribution scheduling instruction to trigger the distribution vehicle action.

[0057] S1: Receive the battery replacement service order from the electric vehicle, including the electric vehicle location information and the battery demand information, including:

[0058] Receive the battery replacement service order sent by the electric vehicle, which includes the real-time location information and the battery demand information of the electric vehicle;

[0059] Specifically, the battery replacement service order sent by the electric vehicle is a set of information for requesting battery replacement service sent by the electric vehicle through the vehicle-mounted communication terminal device installed on the electric vehicle during driving or stopping to the energy instant distribution service platform. The electric vehicle is an electric vehicle with replaceable batteries, such as a replaceable battery electric bus or an electric logistics vehicle.

[0060] For example, the electric bus numbered as electric vehicle A01, when driving on urban roads, the vehicle-mounted communication terminal device automatically detects that the battery power has dropped below the pre-set threshold (such as 20% power), and then automatically or manually triggers the vehicle-mounted communication terminal device to send a battery replacement service order to the energy instant distribution service platform. The battery replacement service order will contain the accurate geographic location of the electric vehicle A01 at present, such as the latitude and longitude coordinate information (such as north latitude 31.2304°, east longitude 121.4737°) obtained by using Beidou positioning system or GPS positioning system, and is sent to the order receiving module in the energy instant distribution service platform in a specific data format.

[0061] At the same time, the battery replacement service order also contains the demand information of the electric vehicle A01 for the battery, so as to facilitate the energy instant distribution service platform to provide corresponding services.

[0062] The battery demand information is the information of the battery requirements proposed by the electric vehicle when sending the battery replacement service order, including the battery type, the battery specification parameters and the battery demand quantity.

[0063] Specifically, the type of the battery refers to the identification of the battery category for electric vehicles, distinguishing batteries of different technical routes or purposes to ensure that the delivered battery can be matched with the existing battery of the electric vehicle. For example, the battery type can be a lithium iron phosphate power battery, a nickel-cobalt-manganese ternary lithium battery, or other battery categories.

[0064] The specification parameters of the battery are information that limits the technical performance and appearance size of the battery, including but not limited to the voltage level of the battery, the capacity of the battery, the size of the battery, the rated power, and other technical parameters. For example, electric vehicle A01 indicates in the battery replacement service order that the required battery specification parameters are: a lithium iron phosphate power battery with a rated voltage of 600 volts, a capacity of 250 ampere-hours, and an appearance size of 1200 mm x 800 mm x 500 mm. The energy instant delivery service platform thereby obtains the requirements for the battery to be delivered in terms of technical performance and appearance size to match the installation and use requirements of the existing electric vehicle.

[0065] The required number of batteries indicates the number of battery units required by the electric vehicle for this battery replacement, to meet the electric vehicle's demand for electric power. For example, electric vehicle A01 indicates that the required number of batteries for this time is 2. That is, the delivery task requires the energy instant delivery service platform to dispatch the corresponding delivery vehicle to provide 2 battery units that meet the above type and specification parameters to the location of the electric vehicle.

[0066] S2: Based on the electric vehicle location information and the battery demand information, analyze the power supply demand characteristics of the electric vehicle, perform demand matching evaluation to determine the demand priority, and obtain the demand analysis result, including:

[0067] Based on the electric vehicle location information and the battery demand information, analyze the battery demand characteristics of the electric vehicle, and determine the battery demand level corresponding to the electric vehicle according to the type of the battery, the specification parameters of the battery, and the required number of batteries;

[0068] Specifically, the electric vehicle A01 issued a battery replacement service order including the electric vehicle location information (such as north latitude 31.2304°, east longitude 121.4737°) and battery demand information (the battery type is a lithium iron phosphate power battery, the rated voltage is 600 volts, the capacity is 250 ampere-hours, the size is 1200 mm x 800 mm x 500 mm, and the required number is 2), after receiving the battery replacement service order, the energy instant distribution service platform first determines the environmental characteristics of the location of the electric vehicle A01 based on the electric vehicle location information, such as the road traffic conditions of the area, the distribution of nearby distribution resources, and the geographical environment characteristics, to analyze the actual environmental demand of the electric vehicle for battery distribution. According to the battery demand information, the characteristics of the battery type, specification parameters and quantity required by the electric vehicle are confirmed, such as determining that the battery type belongs to the characteristics of the lithium iron phosphate power battery, which is suitable for the special battery of urban public transportation, the specification parameters are rated voltage 600 volts, capacity 250 ampere-hours and specific size, and the quantity is 2, thereby determining the battery demand of the electric vehicle under the current conditions.

[0069] Specifically, the energy instant distribution service platform establishes a classification standard according to the type, specification parameters and quantity of the battery. Taking the electric vehicle A01 as an example, when the battery type belongs to the lithium iron phosphate power battery, the platform sets the battery demand level to A level; at the same time, if the battery specification parameters meet special requirements (such as capacity above 250 ampere-hours and voltage above 600 volts, which belong to high performance specifications), the energy instant distribution service platform classifies the battery demand level as A1 level (high priority); according to the battery quantity required, such as the requirement of 2 for the electric vehicle A01, the energy instant distribution service platform sets the battery quantity requirement greater than or equal to 2, improves the battery demand level, and determines it as a higher level A1+ in the A level.

[0070] Through the above determination of the battery demand level, the energy instant distribution service platform can quickly understand the importance of the current demand, distinguish the urgency and priority of the battery demand between different electric vehicles, so as to accurately allocate the inventory batteries and distribution vehicles, and ensure the efficient use of distribution resources.

[0071] According to the battery demand level, the battery demand of the electric vehicle is matched and evaluated to determine the priority of the battery demand, and the battery demand analysis result is obtained;

[0072] Specifically, the energy instant delivery service platform takes the determined battery demand level (such as A1+ level) as input, combines the information in the power supply inventory database and the delivery resource database in the energy instant delivery service platform, and analyzes the relative priority of the battery demand in the current overall demand queue. Assuming that other electric vehicles (such as electric vehicle B02 and electric vehicle C03) also send battery replacement service orders into the energy instant delivery service platform, the energy instant delivery service platform will compare and evaluate the battery demand levels of all electric vehicles. Among them, A-level battery demand will be prioritized over B-level or C-level, A1+ level over A2 level, and so on.

[0073] For example, the battery demand level of electric vehicle A01 is A1+ level, and the energy instant delivery service platform determines that the corresponding battery demand level is the highest level after demand matching evaluation. The delivery plan matching, delivery path optimization and delivery vehicle resource allocation will give priority to meeting the battery demand of electric vehicle A01.

[0074] After the above demand matching evaluation, the energy instant delivery service platform finally generates a battery demand analysis result, recording the battery demand characteristics, battery demand level and corresponding priority level of electric vehicle A01.

[0075] S3: Based on the electric vehicle location information and the battery demand information, query the available battery information and the delivery resource state in the power supply inventory database, perform inventory availability check to evaluate resource matching, and obtain resource state information, including:

[0076] Based on the electric vehicle location information and the battery demand information, query the power supply inventory database to obtain the available battery information corresponding to the battery demand information in the power supply inventory database;

[0077] Taking electric vehicle A01 as an example, the battery replacement service order issued by the electric vehicle indicates that the battery type is a lithium iron phosphate power battery, the specification parameters are rated voltage 600 volts, capacity 250 ampere-hours, size 1200 mm x 800 mm x 500 mm, and the quantity is 2. The power supply inventory database of the energy instant delivery service platform records the battery storage information of multiple storage points, including battery storage location, battery type, battery specification parameters, battery remaining quantity and current state. The energy instant delivery service platform performs precise conditional retrieval in the power supply inventory database according to the battery demand information provided by electric vehicle A01 and the real-time location of the electric vehicle (north latitude 31.2304°, east longitude 121.4737°).

[0078] For example, the energy instant delivery service platform queries and finds that the battery inventory warehouse "A area energy warehouse" closest to the current location of the electric vehicle A01 has 5 pieces of battery units that match the lithium iron phosphate power battery and fully match the specifications. The inventory database records the current state of the battery as available, that is, there is no fault, no reservation, and the power state meets the delivery requirements. Through the above query, the energy instant delivery service platform obtains the inventory battery data that meets the electric vehicle A01 battery demand information conditions, including the number, location and state of available batteries, so as to accurately match the delivery service.

[0079] Query the delivery resource database to obtain the real-time location of the delivery vehicle, the current carrying capacity of the delivery vehicle, and the real-time task execution state of the delivery vehicle;

[0080] The delivery resource database of the energy instant delivery service platform records detailed information of all delivery vehicles, such as vehicle number, real-time geographic location, vehicle load capacity, current battery carrying capacity of the vehicle, delivery task execution state, etc. After receiving the battery demand information of the electric vehicle A01, the energy instant delivery service platform retrieves the current vehicle resource state information according to the delivery resource database and selects the vehicle suitable for executing the delivery task of the electric vehicle A01.

[0081] For example, the energy instant delivery service platform queries the delivery resource database and finds that the delivery vehicle X100 is currently located 2 kilometers away from the A area energy warehouse, with a real-time location coordinate of north latitude 31.2310°, east longitude 121.4745°. The current carrying capacity of the delivery vehicle X100 is recorded as being able to transport a maximum of 4 pieces of lithium iron phosphate power battery at the same time, which is greater than the required number of batteries (2 pieces) of the electric vehicle A01; The real-time task execution state of the delivery vehicle X100 is displayed as idle in the delivery resource database, without other delivery tasks arranged, and in an executable state.

[0082] Through the above query process, the energy instant delivery service platform obtains detailed data of the delivery vehicle resource state that meets the demand of the electric vehicle A01.

[0083] Perform inventory availability check on the available battery information obtained from the power supply inventory database to determine the available state of the battery inventory;

[0084] The energy instant delivery service platform performs an inventory availability check process on the 5 lithium iron phosphate power batteries in the "A area energy warehouse" inventory, including real-time verification of the latest update records in the inventory database, confirmation of the current charging status of the batteries, and whether the batteries have been reserved by other tasks in the recent period. After confirmation, it is found that 3 batteries have been reserved by another delivery task. Therefore, the energy instant delivery service platform finally determines that the actual available number of batteries that can be delivered by electric car A01 from the A area energy warehouse is 2, which meets the actual demand information conditions of electric car A01.

[0085] Through the above process, the energy instant delivery service platform obtains the real-time available state of the battery inventory, i.e., the number and location state of the batteries that meet the demand of the electric car.

[0086] The real-time location of the delivery vehicle, the current carrying capacity of the delivery vehicle, and the real-time task execution state of the delivery vehicle are evaluated to determine the available state of the delivery resource;

[0087] The energy instant delivery service platform cross-verifies and evaluates the real-time location, carrying capacity, and real-time task state of delivery vehicle X100, confirms that the current location of delivery vehicle X100 (close to the battery inventory location and the electric car location), the current carrying capacity (4 battery capacity, exceeding the demand), and the current task state (idle and no reserved task), and based on the above information, determines that delivery vehicle X100 is currently in an available state and can immediately be arranged to perform the battery delivery task of electric car A01.

[0088] According to the available state of the battery inventory and the available state of the delivery resource, the resource state information is obtained;

[0089] After the above evaluation and analysis, the resource state information obtained by the energy instant delivery service platform includes: the battery inventory location is "A area energy warehouse", the actual available battery number is 2; the real-time location of delivery vehicle X100 is 2 kilometers away from the battery inventory warehouse, the current carrying capacity is sufficient, the task execution state is idle and available, and meets the demand of electric car A01.

[0090] S4: According to the demand analysis results and the resource state information, perform a delivery feasibility evaluation to generate a matching scheme and obtain a preliminary delivery plan, including:

[0091] Based on the battery demand priority in the battery demand analysis result, the priority of battery delivery is determined;

[0092] Taking the electric vehicle A01 as an example, the battery demand analysis result of the electric vehicle A01 has been determined as A1+ level, indicating that the battery demand raised by the electric vehicle A01 has the highest urgency and importance. Assuming that the energy instant delivery service platform receives the battery demand information of other electric vehicles such as the electric vehicle B02 and the electric vehicle C03 at this time, the corresponding demand level of the electric vehicle B02 is A2, and the demand level of the electric vehicle C03 is B1, then the energy instant delivery service platform judges that the demand level of the electric vehicle A01 is higher than that of the electric vehicle B02 and the electric vehicle C03, and therefore, the delivery task of the electric vehicle A01 will be given priority in the allocation of delivery resources.

[0093] Specifically, the energy instant delivery service platform establishes a delivery priority order determination mechanism, which arranges the battery delivery order according to the battery demand level from high to low, for example, automatically sets the A1+ level delivery task as the highest priority task, to ensure that high-level demand is given priority response. According to the rules of the delivery priority order determination mechanism, the battery delivery demand of the electric vehicle A01 is automatically determined as the highest priority, and the energy instant delivery service platform will give priority to the electric vehicle A01 in all delivery scheme planning.

[0094] Based on the available state of the battery inventory and the available state of the delivery resource in the resource state information, the delivery resource matching evaluation is performed;

[0095] Taking the electric vehicle A01 as an example, according to the resource state information, the available state of the battery inventory has been recorded as that the A area energy warehouse currently has a total of 2 pieces of required lithium iron phosphate power battery; at the same time, the available state of the delivery resource is also recorded as that the delivery vehicle X100 is currently in an idle state, the real-time position is only 2 kilometers away from the A area energy warehouse, and the delivery vehicle X100 can carry up to 4 pieces of lithium iron phosphate power battery at a time, which fully meets the demand conditions raised by the electric vehicle A01.

[0096] In the delivery resource matching evaluation process, the energy instant delivery service platform compares the actual available location (A area energy warehouse) and quantity (2 pieces) of the battery inventory with the real-time position, carrying capacity and state of the delivery vehicle X100, to confirm whether the matching between the resources is completely reasonable.

[0097] For example, after the delivery resource matching evaluation, the energy instant delivery service platform determines that the delivery vehicle X100 meets the resource requirements of the battery delivery demand, because the vehicle carrying capacity (4 pieces) exceeds the number of batteries required by the electric vehicle A01 (2 pieces) and the current position of the vehicle is close to the battery inventory warehouse, which can complete the pickup action and ensure the smooth execution of the delivery plan. Therefore, the energy instant delivery service platform judges that the matching between the battery demand and the resource state information at this time reaches the satisfaction state.

[0098] According to the matching evaluation result of the distribution resource and the priority order of the battery distribution, a distribution feasibility evaluation is performed to determine a distribution vehicle and corresponding battery information that meet the battery demand, and a preliminary distribution plan is generated;

[0099] The distribution feasibility evaluation of the energy instant distribution service platform will consider multiple factors, such as the accurate time of the distribution vehicle arriving at the warehouse, the preparation time of the warehouse, the estimated time of the distribution vehicle arriving at the electric vehicle location, and the actual traffic environment conditions, etc. Through the feasibility evaluation, the energy instant distribution service platform determines that the estimated time for the distribution vehicle X100 to travel from the current location to the A area energy warehouse is 5 minutes, the estimated time for the battery loading in the warehouse is 10 minutes, and after the loading is completed, the estimated time for the distribution vehicle X100 to travel from the warehouse to the electric vehicle A01 location (North Latitude 31.2304°, East Longitude 121.4737°) is 15 minutes, and the total estimated distribution time is about 30 minutes.

[0100] In the distribution feasibility evaluation process, the energy instant distribution service platform confirms the specific identification number of the battery in the battery inventory for distribution, such as battery numbers LF600-250-001 and LF600-250-002, and the status of the two batteries has been confirmed by the platform to be available and meet the requirements of the battery specification parameters of the electric vehicle A01. Therefore, the energy instant distribution service platform determines that the distribution vehicle X100 will load the above two batteries after the distribution feasibility evaluation, and plans to complete the distribution task according to the distribution order and time schedule.

[0101] Based on the above feasibility evaluation, the energy instant distribution service platform finally generates a preliminary distribution plan. The preliminary distribution plan records the distribution vehicle (X100), the distribution battery number (LF600-250-001 and LF600-250-002), the battery pickup location (A area energy warehouse), the distribution order (the most priority distribution electric vehicle A01), the estimated arrival time (to be completed within about 30 minutes), etc. as the basis for distribution path optimization and distribution task execution.

[0102] S5: Based on the preliminary distribution plan, the distribution path is optimized and the scheduling time sequence is optimized to obtain an optimized distribution scheme, including:

[0103] Based on the preliminary distribution plan, a distribution path optimization model is established;

[0104] Taking the electric vehicle A01 as an example, the energy instant delivery service platform has obtained a preliminary delivery plan, which includes the real-time position of the delivery vehicle X100 (north latitude 31.2310°, east longitude 121.4745°), the position of the battery inventory warehouse (A area energy warehouse), the actual position of the electric vehicle A01 (north latitude 31.2304°, east longitude 121.4737°), the delivery battery number (LF600-250-001 and LF600-250-002), and the preliminary estimated delivery time (within 30 minutes) and other information.

[0105] In order to improve the delivery efficiency, the energy instant delivery service platform establishes a delivery path optimization model according to the preliminary delivery plan. The establishment process of the delivery path optimization model includes taking the real-time position of the delivery vehicle, the position of the warehouse, and the position of the electric vehicle as the basic input data; at the same time, considering the actual traffic environment, road congestion, delivery vehicle load capacity limit, vehicle average driving speed, warehouse goods loading time, battery picking time and other constraint conditions, forming a complete mathematical model or a set of logical rules, so as to calculate the most suitable path scheme for the delivery vehicle to execute through the model.

[0106] For example, in the established delivery path optimization model, the route (about 2 kilometers long) from the real-time position of the delivery vehicle X100 to the battery inventory warehouse is included in the model, and the real-time traffic conditions of the route are considered. Assuming that part of the route is congested at this time, the model will provide multiple optional routes for the platform to comprehensively evaluate. In addition, the delivery path optimization model also considers the route from the delivery vehicle loading the battery from the inventory warehouse to the position of the electric vehicle A01, and in the same way, multiple path schemes are included, and the expected time, route length and traffic condition index data of each scheme are obtained through the calculation model.

[0107] Based on the delivery path optimization model, the optimized delivery route of the delivery vehicle from the current real-time position to the electric vehicle position is determined;

[0108] Taking the delivery vehicle X100 executing the delivery task to the electric vehicle A01 as an example, the energy instant delivery service platform evaluates two path schemes for the delivery vehicle X100 to go from the current position to the battery inventory warehouse (A area energy warehouse) through model analysis: path one is the main road line, the length is 2.0 kilometers, the traffic is congested, and the expected time is about 8 minutes; path two is the secondary road line, the length is 2.5 kilometers, the traffic is smooth, and the expected time is about 6 minutes. After the platform calculates through the optimization model, path two is selected as the best route for the delivery vehicle X100 to go to the inventory warehouse.

[0109] At the same time, the energy instant delivery service platform analyzes the path scheme of the delivery vehicle X100 from the inventory warehouse to the location of the electric vehicle A01 (north latitude 31.2304°, east longitude 121.4737°) through the model, and also analyzes two feasible paths: scheme one is the main highway, the total length is 4 kilometers, the traffic is congested, and the time consumption is 15 minutes; scheme two is the ordinary road, the total length is 5 kilometers, the traffic is smooth, and the time consumption is 12 minutes. The energy instant delivery service platform determines the second scheme as the best route through the optimization model calculation.

[0110] Based on the analysis of the two routes, the energy instant delivery service platform finally determines the optimized delivery route of the delivery vehicle X100 as: "current location (north latitude 31.2310°, east longitude 121.4745°) - secondary road route - A area energy warehouse - ordinary road - electric vehicle A01 location", and records the details of the optimized route and the estimated time consumption of each stage.

[0111] According to the optimized delivery route, the delivery sequence of the delivery vehicle and the scheduling sequence of the delivery task are determined;

[0112] Taking the delivery task of the electric vehicle A01 as an example, the energy instant delivery service platform determines the delivery task scheduling sequence according to the determined optimized route as:

[0113] The delivery vehicle X100 starts from the current location (north latitude 31.2310°, east longitude 121.4745°) at 10:00, selects the secondary road route, and arrives at the A area energy warehouse at 10:06;

[0114] The delivery vehicle X100 loads the batteries (number LF600-250-001 and LF600-250-002) in the warehouse, and the loading process is expected to last 10 minutes, and the battery loading is completed at 10:16;

[0115] The delivery vehicle X100 starts from the A area energy warehouse, travels through the ordinary road, and is expected to travel for 12 minutes, and arrives at the location of the electric vehicle A01 (north latitude 31.2304°, east longitude 121.4737°) at 10:28;

[0116] After the delivery vehicle arrives at the location of the electric vehicle A01, it performs the battery replacement action, which is expected to take about 5 minutes, and completes the delivery task at 10:33.

[0117] The energy instant delivery service platform records the delivery sequence and task scheduling sequence of each step above to form a delivery execution plan.

[0118] Based on the delivery sequence of the delivery vehicle and the scheduling sequence of the delivery task, an optimized delivery scheme is generated;

[0119] The energy instant delivery service platform determines the optimized delivery scheme to include:

[0120] The delivery vehicle number is X100.

[0121] The delivery battery numbers are LF600-250-001 and LF600-250-002.

[0122] The delivery path plan is: "vehicle real-time position-secondary road-A area energy warehouse-common road-tramcar A01 position".

[0123] The delivery task timing arrangement is: 10:00 vehicle departure; 10:06 arrival at warehouse for battery loading; 10:16 departure from warehouse after completing loading; 10:28 arrival at tramcar position; 10:33 completion of battery swap service.

[0124] The above delivery plan ensures the accuracy and timeliness of task implementation by recording the vehicle number, path selection, delivery battery information, and specific timing of task execution.

[0125] S6, according to the optimized delivery plan, execute the delivery scheduling instruction to trigger the action of the delivery vehicle, including:

[0126] According to the optimized delivery plan, send the delivery scheduling instruction to the delivery vehicle;

[0127] Taking the tramcar A01 battery swap delivery task as an example, the energy instant delivery service platform obtains the optimized delivery plan. The optimized delivery plan records the delivery vehicle number X100, the battery numbers LF600-250-001 and LF600-250-002 that need to be delivered, the battery type is lithium iron phosphate power battery, the battery specification parameters are rated voltage 600 volts, capacity 250 ampere-hours, outer dimensions 1200 mm long x 800 mm wide x 500 mm high, the number of batteries required is 2, and the delivery path and specific timing required by the delivery vehicle X100 to execute, including the vehicle departure time from the current position, the specific time to arrive at the warehouse, the warehouse pickup time, the route and specific time node to the tramcar A01 position.

[0128] The energy instant delivery service platform generates a special delivery scheduling instruction according to the optimized delivery plan. The delivery scheduling instruction contains all the necessary information related to this task, and through wireless network communication technology, the delivery scheduling instruction is transmitted to the vehicle-mounted scheduling terminal device installed on the delivery vehicle X100 in the form of data transmission, such as using 5G mobile communication or vehicle-to-everything (V2X) special communication link.

[0129] For example, when the on-board dispatch terminal device on the delivery vehicle X100 receives the dispatch instruction sent by the energy instant delivery service platform, it will automatically inform the delivery vehicle driver of the delivery task content in the form of text, image or voice prompt, including the battery information that needs to be delivered, the description of the delivery path and the time requirements of each delivery link.

[0130] The delivery dispatch instruction includes the battery type, battery specification parameters, battery quantity required, delivery sequence of the delivery vehicle and the optimized delivery route;

[0131] Taking electric vehicle A01 as an example, this delivery dispatch instruction includes:

[0132] It indicates that the battery type that needs to be delivered by the delivery vehicle X100 is lithium iron phosphate power battery;

[0133] The specification parameters of the battery are rated voltage 600 volts, battery capacity 250 ampere-hours, and battery size 1200 mm x 800 mm x 500 mm, which ensures that the delivery vehicle can accurately identify and extract the correct battery in the inventory warehouse;

[0134] The required quantity of the battery is recorded as 2 pieces, and the battery numbers are LF600-250-001 and LF600-250-002, respectively, which can help the delivery vehicle driver or automatic loading device to accurately select the inventory battery and avoid delivery errors;

[0135] The delivery dispatch instruction also identifies the delivery sequence of the delivery vehicle to perform the delivery task, and the delivery sequence is the only task performed by the delivery vehicle X100 in this task, i.e. the vehicle first goes to the A-area energy warehouse to load the specified battery from the current location (31.2310° N, 121.4745° E), and then goes to the location of electric vehicle A01 to perform the battery replacement task;

[0136] At the same time, the delivery dispatch instruction describes the details of the optimized delivery route, i.e. the delivery vehicle X100 must complete the delivery task according to the route "current location (31.2310° N, 121.4745° E) - secondary road route - A-area energy warehouse - ordinary road - location of electric vehicle A01 (31.2304° N, 121.4737° E)". This route scheme must identify the specific road name or path identifier and the specific time point of arrival in the dispatch instruction to ensure that the delivery vehicle driver fully understands the route information required to perform the task.

[0137] After receiving the delivery dispatch instruction, the delivery vehicle performs the delivery task according to the delivery sequence and the optimized delivery route;

[0138] Taking the electric vehicle A01 distribution task performed by the distribution vehicle X100 as an example, after the on-board scheduling terminal device of the distribution vehicle X100 receives the scheduling instruction of the energy instant distribution service platform, the driver immediately determines the task arrangement in the distribution instruction, including that the vehicle first departs from the current real-time position according to the specified route at a specific time, accurately arrives at the energy warehouse position in the A area along the secondary road route (the estimated time is 6 minutes, and the arrival time is 10:06); then, the distribution vehicle accurately loads the 2 pieces of lithium iron phosphate power battery (the numbers are LF600-250-001 and LF600-250-002) specified in the scheduling instruction in the warehouse, and the estimated loading time is 10 minutes, and the loading is completed at 10:16.

[0139] After the loading is completed, the distribution vehicle X100 departs from the warehouse position along the ordinary road to the position of the electric vehicle A01 according to the optimized distribution route of the scheduling instruction, the whole vehicle driving process is estimated to take 12 minutes, and the vehicle accurately arrives at the position of the electric vehicle A01 at 10:28; after the distribution vehicle arrives at the destination, the battery replacement service is performed according to the time requirement and task requirement of the distribution instruction, the estimated service time is 5 minutes, and the distribution task is successfully completed at 10:33.

[0140] The whole distribution process is performed by the driver of the distribution vehicle, and the on-board scheduling terminal device on the distribution vehicle feeds back the distribution progress to the energy instant distribution service platform in real time, the platform records and tracks the actual running state of the distribution vehicle, and ensures that the distribution task is efficiently completed according to the scheduling instruction provided by the platform. Embodiment 2

[0141] The difference between the embodiment 2 and the embodiment 1 of the present application is that the embodiment 2 is to introduce an energy instant distribution service platform.

[0142] Figure 2 The structural schematic diagram of the energy instant distribution service platform is given, and the energy instant distribution service platform comprises:

[0143] The order receiving module receives the power exchange service order from the electric vehicle, including the electric vehicle position information and the battery demand information;

[0144] The demand analysis module analyzes the power supply demand characteristics of the electric vehicle based on the electric vehicle position information and the battery demand information, performs demand matching evaluation to determine the demand priority, and obtains the demand analysis result;

[0145] The resource query module queries the available battery information and the distribution resource state in the power supply inventory database based on the electric vehicle position information and the battery demand information, performs inventory availability check to evaluate the resource matching, and obtains the resource state information;

[0146] The feasibility evaluation module: according to the requirement analysis result and the resource state information, performs the distribution feasibility evaluation to generate the matching scheme, and obtains the preliminary distribution plan;

[0147] The path optimization module: based on the preliminary distribution plan, optimizes the distribution path and the scheduling time sequence, and obtains the optimized distribution scheme;

[0148] The scheduling execution module: according to the optimized distribution scheme, executes the distribution scheduling instruction to trigger the distribution vehicle action.

[0149] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another, for example, the computer instructions can be transferred from one website, computer, server or data center to another by wired (for example, infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center and the like containing one or more available medium sets. The available medium can be a magnetic medium (for example, floppy disk, hard disk, magnetic tape), an optical medium (for example, DVD) or a semiconductor medium. The semiconductor medium can be a solid state disk.

[0150] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0151] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working process of the above-described system, device and module can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0152] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the division of the above-described device embodiment is merely a logical function division, and there can be another division manner for the actual implementation, for example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different modules can be indirect couplings or communication connections through some interfaces, devices or modules, and can be electrical, mechanical or other forms.

[0153] The modules illustrated as separated components can or can not be physically separated, and the components illustrated as modules can or can not be physical modules, and can be located in one place, or can be distributed on multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0154] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can be physically present alone, or two or more modules can be integrated into one module.

[0155] If the functions are realized in the form of software function modules and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program codes that can be stored in the medium.

[0156] The above description is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, and all should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0157] Finally: the above only for the preferred embodiments of the present application, and not for limiting the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application, should be included in the scope of protection of the present application.

Claims

1. An energy instant delivery service implementation method, characterized by, The method comprises the following steps: S1: receiving a battery replacement service order from an electric vehicle, including electric vehicle location information and battery demand information; the battery demand information includes the type of the battery, the specification parameters of the battery, and the quantity of the battery required; S2: based on the electric vehicle location information and the battery demand information, analyzing the power supply demand characteristics of the electric vehicle, performing demand matching evaluation to determine the demand priority, and obtaining a demand analysis result, specifically: based on the electric vehicle location information and the battery demand information, performing characteristic analysis on the battery demand of the electric vehicle, determining the battery demand level corresponding to the electric vehicle according to the type of the battery, the specification parameters of the battery, and the quantity of the battery required; based on the battery demand level, performing demand matching evaluation on the battery demand of the electric vehicle, determining the priority of the battery demand, and obtaining the battery demand analysis result; S3: based on the electric vehicle location information and the battery demand information, querying the available battery information and the distribution resource state in the power supply inventory database, performing inventory availability check to evaluate the resource matching, and obtaining resource state information, specifically: based on the electric vehicle location information and the battery demand information, querying the power supply inventory database to obtain the available battery information corresponding to the battery demand information in the power supply inventory database; querying the distribution resource database to obtain the real-time location of the distribution vehicle, the current carrying capacity of the distribution vehicle, and the real-time task execution state of the distribution vehicle; performing inventory availability check on the available battery information obtained from the power supply inventory database to determine the available state of the battery inventory; performing distribution resource state evaluation on the real-time location of the distribution vehicle, the current carrying capacity of the distribution vehicle, and the real-time task execution state of the distribution vehicle to determine the available state of the distribution resource; obtaining the resource state information according to the available state of the battery inventory and the available state of the distribution resource; S4: based on the demand analysis result and the resource state information, performing distribution feasibility evaluation to generate a matching scheme, and obtaining a preliminary distribution plan; S5: based on the preliminary distribution plan, optimizing the distribution path and the scheduling sequence to obtain an optimized distribution scheme; S6: based on the optimized distribution scheme, executing distribution scheduling instructions to trigger the action of the distribution vehicle.

2. The method of claim 1, wherein, S1, specifically: receiving a battery replacement service order sent from an electric vehicle, the battery replacement service order including real-time location information of the electric vehicle and battery demand information.

3. The method of claim 2, wherein, S4, specifically: based on the battery demand priority in the battery demand analysis result, determining the priority order of battery distribution; based on the available state of the battery inventory and the available state of the distribution resource in the resource state information, performing distribution resource matching evaluation; based on the distribution resource matching evaluation result and the priority order of battery distribution, performing distribution feasibility evaluation to determine the distribution vehicle and the corresponding battery information that meet the battery demand, and generating a preliminary distribution plan.

4. The method of claim 3, wherein, S5, specifically: based on the preliminary distribution plan, establishing a distribution path optimization model; based on the distribution path optimization model, determining the optimized distribution route of the distribution vehicle from the current real-time location to the electric vehicle location; based on the optimized distribution route, determining the distribution sequence of the distribution vehicle and the scheduling sequence of the distribution task; based on the distribution sequence of the distribution vehicle and the scheduling sequence of the distribution task, generating an optimized distribution scheme.

5. The method of claim 4, wherein, S6, specifically: According to the optimized distribution scheme, a distribution scheduling instruction is sent to the distribution vehicle; After receiving the distribution scheduling instruction, the distribution vehicle performs the distribution task according to the distribution sequence and the optimized distribution route.

6. The method of claim 5, wherein, The distribution scheduling instruction includes the battery type, battery specification parameters, battery demand quantity, distribution sequence and optimized distribution route of the distribution vehicle.

7. An energy instant delivery service platform for implementing the energy instant delivery service implementation method of any one of claims 1-6, characterized in that, Comprise: The order receiving module receives the battery swap service order from the electric vehicle, including the electric vehicle location information and the battery demand information; The demand analysis module analyzes the power supply demand characteristics of the electric vehicle based on the electric vehicle location information and the battery demand information, performs demand matching evaluation to determine the demand priority, and obtains the demand analysis result; The resource query module queries the available battery information and distribution resource state in the power supply inventory database based on the electric vehicle location information and the battery demand information, performs inventory availability check to evaluate the resource matching, and obtains the resource state information; The feasibility evaluation module performs distribution feasibility evaluation according to the demand analysis result and the resource state information to generate a matching scheme and obtain a preliminary distribution plan; The path optimization module optimizes the distribution path and scheduling time sequence based on the preliminary distribution plan to obtain the optimized distribution scheme; The scheduling execution module executes the distribution scheduling instruction to trigger the action of the distribution vehicle according to the optimized distribution scheme.

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