Vehicle introduction number based on battery swap heavy truck and scale prediction method of charging and battery swap station

Abstract

The application provides a vehicle introduction number and charging station scale prediction method based on battery swap heavy trucks, comprising: setting the introduction of battery swap heavy truck models, determining the battery swap heavy truck operation parameters; based on the battery swap heavy truck operation parameters, calculating the daily total traffic demand and charging demand of the introduced battery swap heavy truck, and constructing a battery swap heavy truck vehicle number prediction model and a charging demand model; based on the number of battery swap heavy truck running times and the battery swap heavy truck vehicle number prediction model and the charging demand model, a charging station scale prediction model is constructed; based on the charging station scale prediction model, the dynamic relationship between the charging and battery swap equipment parameters and the battery swap workshop parameters is obtained for the investment operator to make reasonable investment scale prediction and planning. The application is suitable for various application scenarios, and will provide decision basis for operators who need to replace or introduce battery swap heavy trucks and operators of charging and battery swap stations, and help investors to make more scientific investment scale.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of energy storage planning of power systems, and relates to a capacity configuration method, in particular to a vehicle introduction number and charging station scale prediction method based on battery swap heavy trucks. BACKGROUND

[0002] At present, although the battery swap heavy truck has the advantages of high operation efficiency and low overall cost, the construction of the battery swap station still faces problems such as site selection and power distribution access difficulty, battery swap sharing and intelligentization promotion difficulty, and the like. The construction scale design of the battery swap station is difficult, and the operation cost is high. In addition, due to the fact that the battery standards cannot be unified at present, the infrastructure construction is self-governed, so that the power battery production manufacturers, specifications, shapes and sizes adopted by many enterprises are different and cannot be universal, and the enterprises can only construct their own battery swap stations, which are limited in infrastructure. At the same time, the application scenarios of the battery swap heavy truck are also limited, which has certain difficulty for the future large-area popularization of the battery swap heavy truck.

[0003] Therefore, in the prior art, due to the different demands of each battery swap station and the different models of the battery swap heavy truck, the demand and construction scale of the battery swap station cannot be accurately determined, and problems such as the battery swap station construction cannot be accurately designed according to the user demand to make reasonable investment scale decision of the battery swap station exist in the battery swap station construction process. SUMMARY

[0004] In view of the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a vehicle introduction number and charging station scale prediction method based on a battery swap heavy truck, which is used to solve the problem in the prior art that due to the different demands of each battery swap station and the different models of the battery swap heavy truck, the demand and construction scale of the battery swap station cannot be accurately determined, and further problems such as the battery swap station construction cannot be accurately designed according to the user demand to make reasonable investment scale decision of the battery swap station exist in the battery swap station construction process.

[0005] To achieve the above-mentioned purposes and other related purposes, in a first aspect, the present application provides a vehicle introduction number and charging station scale prediction method based on a battery swap heavy truck, comprising the following steps: setting a battery swap heavy truck model to be introduced, and determining battery swap heavy truck operation parameters; calculating daily total traffic demand and charging demand of the introduced battery swap heavy truck based on the battery swap heavy truck operation parameters, and constructing a battery swap heavy truck vehicle quantity prediction model and a charging demand model; constructing a charging station scale prediction model based on the number of battery swap heavy truck running times and the battery swap heavy truck vehicle quantity prediction model and the charging demand model; and obtaining a dynamic relationship between charging station charging equipment parameters and battery swap workshop parameters based on the charging station scale prediction model, so as to provide an investment operator with reasonable investment scale prediction and planning.

[0006] In an implementation form of the first aspect, the calculation of the total daily transport demand and the charging demand of the introduced battery swap heavy truck based on the battery swap heavy truck operation parameters, and the construction of the introduced battery swap heavy truck quantity prediction model and the charging demand model comprise the following steps: calculating the running mileage under the rated load of the vehicle based on the battery swap heavy truck operation parameters; analyzing the battery swap heavy truck operation scenario, calculating the total daily transport demand and the charging demand of the introduced battery swap heavy truck, and obtaining the introduced or replaced battery swap heavy truck quantity prediction model and the charging demand model.

[0007] In an implementation form of the first aspect, the battery swap heavy truck operation parameters comprise: the battery capacity of the vehicle, the power consumption per 100 km under the rated load, the rated load of the vehicle, and the charging and discharging depth of the battery; and the calculation formula of the running mileage under the rated load of the vehicle is:

[0008]

[0009] wherein k highest represents the upper limit of the charging and discharging depth of the battery, and the unit is %; k lowest represents the lower limit of the charging and discharging depth of the battery, and the unit is %; q B represents the battery capacity of the vehicle, and the unit is kWh; q car represents the power consumption per 100 km under the rated load, and the unit is kWh / 100 km; D car represents the running mileage under the rated load of the vehicle, and the unit is km.

[0010] In an implementation form of the first aspect, the battery swap heavy truck operation scenario comprises: the battery swap heavy truck replacement vehicle and the battery swap heavy truck introduced vehicle; the analysis of the battery swap heavy truck operation scenario and the calculation of the total daily transport demand of the introduced battery swap heavy truck to obtain the introduced or replaced battery swap heavy truck quantity prediction model comprise the following steps: when the battery swap heavy truck operation vehicle is the replacement vehicle, the annual total transport demand of the replacement vehicle should be kept at least flat to the original transport demand, and the daily transport demand to be achieved is calculated; the number of battery swap heavy trucks is calculated based on the daily transport demand to be achieved; the annual total transport demand calculation formula of the replacement vehicle is:

[0011] W EX = W1N1Q1 + W2N2Q2 + … + W n N n Q n

[0012] wherein W n represents the load of different vehicle models replaced by the operation plan; N n represents the annual operation times; Q n represents the number of vehicles; when the battery swap heavy truck operation vehicle is the newly introduced vehicle, the annual total transport demand is analyzed and formulated, and the daily transport demand to be achieved is calculated; the calculation formula of the daily transport demand to be achieved is:

[0013]

[0014] wherein, W in represents the total demand of annual transport capacity; n r.day represents the total number of annual operation days;

[0015] The formula for calculating the number of battery swap heavy truck vehicles is:

[0016]

[0017] wherein, W represents the daily transport volume to be achieved; W car represents the rated load of the vehicle; and n represents the daily operation frequency of the battery swap heavy truck.

[0018] In an implementation form of the first aspect, based on the operation frequency of the battery swap heavy truck and the introduced battery swap heavy truck vehicle quantity prediction model and the charging demand model, the charging and battery swap station scale prediction model is constructed, including the following steps: according to different operation scenarios, the running distance of the battery swap heavy truck vehicle and the total number of daily battery swaps required by the battery swap heavy truck are calculated; and based on the total number of daily battery swaps required by the battery swap heavy truck, the operation parameters of the charging and battery swap station are calculated to obtain the charging and battery swap station scale prediction model.

[0019] In an implementation form of the first aspect, according to different operation scenarios, the running distance of the battery swap heavy truck vehicle and the total number of daily battery swaps required by the battery swap heavy truck are calculated, including the following steps: when the battery swap heavy truck vehicle is for one-way transportation: the running distance of the battery swap heavy truck vehicle is n*D tr ; and the calculation formula of the number of daily battery swaps of the battery swap heavy truck for one-way transportation is:

[0020]

[0021] The calculation formula of the total number of daily battery swaps of the battery swap heavy truck for one-way transportation in a certain period is:

[0022] N = Q * N single

[0023] wherein, D tr represents the distance of a single trip of the vehicle; n represents the daily operation frequency of the battery swap heavy truck; D car represents the running distance under the rated load of the vehicle, in units of km; and Q represents the number of battery swap heavy truck vehicles.

[0024] When the battery swap heavy truck vehicle is for two-way transportation: the actual running distance of the battery swap heavy truck vehicle is 2*n*D tr ; and the calculation formula of the number of daily battery swaps of the battery swap heavy truck for two-way transportation is:

[0025]

[0026] The calculation formula of the total daily battery replacement times of the battery replacement heavy truck in a certain period of time is:

[0027] N = Q * N return

[0028] wherein, D tr represents the distance of a single trip of the vehicle; n represents the daily operation times of the battery replacement heavy truck; D car represents the operation mileage under the rated load of the vehicle, in units of km; and Q represents the number of battery replacement heavy trucks.

[0029] In an implementation form of the first aspect, the charging and battery replacement station operation parameters include: daily total charging demand of the charging and battery replacement station, the number of charging machines, the number of battery replacement workshops, single battery replacement time, and single battery charging time; and the calculation formula of the daily total charging demand of the charging and battery replacement station is:

[0030] q D = Q * N * (k highest -k lowest ) q B

[0031] wherein, k highest represents the upper limit depth of battery charging and discharging, in units of %; k lowest represents the lower limit depth of battery charging and discharging, in units of %; q B represents the vehicle battery capacity, in units of kWh; Q represents the number of battery replacement heavy trucks; and N represents the total daily battery replacement times of the battery replacement heavy truck in a certain period of time.

[0032] The calculation formula of the single battery charging time is:

[0033]

[0034] wherein, T CH represents the single battery charging time, in units of min; P CH represents the charging power of the charging machine, in units of kWh / min; k highest represents the upper limit depth of battery charging and discharging, in units of %; k lowest represents the lower limit depth of battery charging and discharging, in units of %; and q B represents the vehicle battery capacity, in units of kWh.

[0035] In an implementation form of the first aspect, the obtaining the dynamic relationship between the charging and swapping station charging and swapping equipment parameters and the swapping station parameters based on the charging and swapping station scale prediction model comprises the following steps: calculating the number of charging and swapping stations based on the charging and swapping station operation parameters; calculating the number of daily charging services provided by a single charging and swapping station based on the number of charging and swapping stations and the number of charging machines, and obtaining the dynamic relationship between the charging and swapping station charging and swapping equipment parameters and the swapping station parameters; and determining the final number of swapping stations and the number of charging machines owned by the charging and swapping station according to the number of daily charging services provided by a single charging and swapping station.

[0036] In an implementation form of the first aspect, the number of charging and swapping stations is calculated according to the following formula:

[0037]

[0038] wherein, N CH represents the number of charging machines owned by the charging and swapping station; T EX represents the single swapping time, in min;

[0039] The number of daily charging services provided by a single charging and swapping station is calculated according to the following formula:

[0040]

[0041] wherein, T CH represents the single battery charging time, in min; T EX represents the single swapping time, in min; N CH represents the number of charging machines owned by the charging and swapping station; N EX represents the number of charging and swapping stations.

[0042] In an implementation form of the first aspect, the determining the final number of swapping stations and the number of charging machines owned by the charging and swapping station according to the number of daily charging services provided by a single charging and swapping station comprises the following steps: when the number of daily charging services provided by a single charging and swapping station is greater than or equal to the number of daily swapping times of the heavy truck for swapping during the total transportation in a certain time period, outputting the number of charging machines owned by the charging and swapping station and the number of swapping stations; and when the number of daily charging services provided by a single charging and swapping station is less than the number of daily swapping times of the heavy truck for swapping during the total transportation in a certain time period, returning the number of charging machines and performing the above steps in a loop until the output result is met.

[0043] In a second aspect, the application provides a vehicle introduction number and charging station scale prediction system based on battery swap heavy trucks, comprising: an acquisition module configured to set an introduced battery swap heavy truck model and determine battery swap heavy truck operation parameters; a quantity calculation module configured to calculate daily total traffic demand and charging demand of the introduced battery swap heavy trucks based on the battery swap heavy truck operation parameters, and construct a battery swap heavy truck vehicle quantity prediction model and a charging demand model; a scale calculation module configured to construct a charging station scale prediction model based on the number of battery swap heavy truck operations and the battery swap heavy truck vehicle quantity prediction model and the charging demand model; and a prediction and planning module configured to obtain a dynamic relationship between charging station charging and battery swap equipment parameters and battery swap workshop parameters based on the charging station scale prediction model, so as to provide a reasonable investment scale prediction and planning for an investor.

[0044] In a last aspect, the application provides a vehicle introduction number and charging station scale prediction device based on battery swap heavy trucks, comprising: a processor and a memory. The memory is configured to store a computer program; the processor is connected with the memory and is configured to execute the computer program stored in the memory, so that the vehicle introduction number and charging station scale prediction device based on battery swap heavy trucks executes the vehicle introduction number and charging station scale prediction method based on battery swap heavy trucks.

[0045] As described above, the vehicle introduction number and charging station scale prediction method based on battery swap heavy trucks has the following beneficial effects:

[0046] The application provides a vehicle introduction number and charging station scale prediction method based on battery swap heavy trucks. By analyzing battery swap heavy truck operation parameters, operation scenarios and operation modes, the battery swap heavy truck introduction demand quantity is calculated based on application scenarios, and various influencing factor parameters of battery swap heavy truck operation are parameterized, combined with vehicle introduction parameters, to build a charging station scale prediction model. The establishment of the model provides an estimation basis for operators who need to replace or introduce battery swap heavy trucks and operators of charging stations. The application is suitable for various application scenarios and provides a decision basis for operators who need to replace or introduce battery swap heavy trucks and operators of charging stations, which helps investors to make more scientific investment scale. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 A flowchart showing the vehicle introduction number and charging station scale prediction method based on battery swap heavy trucks in an embodiment of the application.

[0048] Figure 2 A flowchart showing S12 in the vehicle introduction number and charging station scale prediction method based on battery swap heavy trucks.

[0049] Figure 3A flowchart showing a vehicle replacement or vehicle number introduction prediction process of the application adapted to various operation scenarios.

[0050] Figure 4 A flowchart showing S13 in the vehicle number introduction and charging station scale prediction method based on the battery swap heavy truck of the application.

[0051] Figure 5 A flowchart showing a charging station service number and electricity demand prediction process of the application adapted to various operation scenarios.

[0052] Figure 6 A flowchart showing S14 in the vehicle number introduction and charging station scale prediction method based on the battery swap heavy truck of the application.

[0053] Figure 7 A flowchart showing a charging station scale prediction process of the application adapted to various operation scenarios in the vehicle number introduction and charging station scale prediction method based on the battery swap heavy truck.

[0054] Figure 8 A schematic diagram showing the principle structure of the vehicle number introduction and charging station scale prediction system based on the battery swap heavy truck of the application in an embodiment.

[0055] Figure 9 A schematic diagram showing the principle structure of the vehicle number introduction and charging station scale prediction device based on the battery swap heavy truck of the application in an embodiment.

[0056] Element number explanation

[0057] 81 Acquisition module

[0058] 82 Number calculation module

[0059] 83 Scale calculation module

[0060] 84 Prediction and planning module

[0061] 91 Processor

[0062] 92 Memory

[0063] S11-S14 steps DETAILED DESCRIPTION

[0064] Following make the embodiments of the present application more clear through specific, concrete examples, and those skilled in the art can easily understand other advantages and effects of the present application from the disclosure of the specification. The present application can also be implemented or applied through other different specific embodiments, and various modifications or changes can be made to the details in the specification based on different views and applications without departing from the spirit of the present application. It should be noted that the following examples and features in the examples can be combined with each other without conflict.

[0065] It should be noted that the diagrams provided in the following examples only illustrate the basic concept of the present application in a schematic manner, and only the components related to the present application are shown in the diagrams, not the number, shape and size of the components when actually implemented. The actual implementation of each component may be a random change in type, number and proportion, and the component layout type may also be more complex.

[0066] The vehicle introduction number and charging and battery swap station scale prediction method based on battery swap heavy trucks provided in the embodiments of the present application will be described in detail below with reference to the accompanying drawings of the embodiments of the present application. The present application is used to solve the problem in the prior art that the demand and construction scale of the battery swap station cannot be accurately determined due to different demands of each battery swap station and different models of the battery swap heavy trucks, thereby causing problems such as the battery swap station construction cannot be reasonably designed according to the user demand in the investment scale decision-making of the battery swap station construction.

[0067] The present application establishes the calculation of the introduction demand of the battery swap heavy truck based on the application scenario by analyzing the operation parameters, operation scenarios and operation modes of the battery swap heavy truck, and parameterizes each influencing factor of the battery swap heavy truck operation, combined with the vehicle introduction parameters, to build a charging and battery swap station scale prediction model. The establishment of the model will provide an estimation basis for the operator of the battery swap heavy truck and the operator of the charging and battery swap station.

[0068] Please refer to Figure 1 , which shows the flowchart of the vehicle introduction number and charging and battery swap station scale prediction method based on battery swap heavy trucks in an embodiment of the present application. As Figure 1 shown, the present embodiment provides a vehicle introduction number and charging and battery swap station scale prediction method based on battery swap heavy trucks.

[0069] The vehicle introduction number and charging and battery swap station scale prediction method based on battery swap heavy trucks specifically includes the following steps:

[0070] S11, set the introduced battery swap heavy truck model, and determine the battery swap heavy truck operation parameters.

[0071] In this embodiment, the model of the introduced battery swap heavy truck is set according to the user demand, and the battery swap heavy truck vehicle operation parameter is determined according to the model of the battery swap heavy truck. The battery swap heavy truck vehicle operation parameter includes but is not limited to: vehicle battery capacity, power consumption per 100 kilometers under rated load, vehicle rated load, battery charging and discharging depth, etc.

[0072] S12, based on the battery swap heavy truck vehicle operation parameter, the total daily traffic demand and the charging demand of the introduced battery swap heavy truck are calculated, and the introduced battery swap heavy truck vehicle quantity prediction model and the charging demand model are constructed. Please refer to Figure 2 and Figure 3 , respectively, showing the process schematic diagram of S12 in the vehicle introduction number and charging station scale prediction method based on the battery swap heavy truck of the application and the process schematic diagram of the application for predicting the number of vehicles introduced or replaced by the operator under various operation scenarios. As shown in Figure 2 and Figure 3 , the S12 comprises the following steps:

[0073] S121, based on the battery swap heavy truck vehicle operation parameter, the running mileage under the rated load of the vehicle is calculated.

[0074] In this embodiment, the running mileage under the rated load of the vehicle is calculated through the introduced battery swap heavy truck vehicle parameters, such as: vehicle battery capacity, power consumption per 100 kilometers under rated load, vehicle rated load, battery charging and discharging depth, etc. The battery charging and discharging depth is generally set with upper and lower limits of charging and discharging, such as: the upper limit of charging and discharging is set to 90%; the lower limit of charging and discharging is set to 10%, etc. The data can be set according to the actual situation.

[0075] Specifically, the calculation formula of the running mileage under the rated load of the vehicle is:

[0076]

[0077] wherein, k highest represents the upper limit of battery charging and discharging depth, unit: %; k lowest represents the lower limit of battery charging and discharging depth, unit: %; q B represents the vehicle battery capacity, unit: kWh; q car represents the power consumption per 100 kilometers under rated load, unit: kWh / 100km; D car represents the running mileage under the rated load of the vehicle, unit: km.

[0078] S122, analyzing the battery swap heavy truck operation scenario, calculating the total daily traffic demand and the charging demand of the introduced battery swap heavy truck, obtaining the introduced or replaced battery swap heavy truck vehicle quantity prediction model and the charging demand model.

[0079] In this embodiment, the analysis of the battery swap heavy truck operation scenario includes two cases, namely: analyzing the replacement of vehicles by the operator, or introducing the total daily operation demand of vehicles. According to the different operation scenarios of the battery swap heavy truck, the demand of the operation scenario traffic volume is analyzed, so as to calculate the total traffic volume of the replaced vehicle or the total traffic volume demand of the newly introduced vehicle, and then the total traffic volume to be achieved daily is obtained. Combined with the daily operation frequency of the battery swap heavy truck and the rated load of the vehicle corresponding to the different models of the battery swap heavy truck, the introduction quantity or replacement quantity of the battery swap heavy truck can be calculated.

[0080] Specifically, the battery swap heavy truck operation scenario is divided into two cases: the battery swap heavy truck replaces the vehicle and the battery swap heavy truck introduces the vehicle.

[0081] (1) When the vehicle operated by the battery swap heavy truck is a replacement vehicle, the annual total traffic volume of the replacement vehicle should be kept at least flat to the original transportation volume, and the daily traffic volume to be achieved is calculated; the number of battery swap heavy truck vehicles is calculated based on the daily traffic volume to be achieved.

[0082] Therefore, the annual total traffic volume calculation formula of the replacement vehicle is:

[0083] W EX = W1N1Q1 + W2N2Q2 + … + W n N n Q n

[0084] Wherein, W n represents the load of different vehicle models replaced by the operation plan; N n represents the annual operation frequency; Q n represents the number of holdings.

[0085] According to the annual total traffic volume of the replacement vehicle in the above formula, the daily traffic volume to be achieved is calculated as:

[0086]

[0087] Wherein, W EX represents the annual demand total traffic capacity; n r.day represents the total number of annual operation days.

[0088] (2) When the vehicle operated by the battery swap heavy truck is a newly introduced vehicle, the annual demand total traffic capacity needs to be analyzed and formulated, and the daily traffic volume to be achieved is calculated.

[0089] Therefore, the calculation formula of the daily traffic volume to be achieved of the newly introduced vehicle is:

[0090]

[0091] Wherein, W in represents the annual demand total traffic capacity; n r.day represents the total number of annual operation days.

[0092] The newly introduced battery swap heavy truck quantity calculation formula is:

[0093]

[0094] Wherein, W represents the daily transport volume to be achieved; W car represents the rated load of the vehicle; n represents the daily operation frequency of the battery swap heavy truck, and the vehicle is considered to be one-way transportation or round-trip transportation during calculation.

[0095] It should be noted that n r.day should be input according to the actual operation days of the whole year.

[0096] S13, based on the battery swap heavy truck operation frequency and the introduced battery swap heavy truck quantity prediction model and the charging demand model, a charging and battery swap station scale prediction model is constructed. Please refer to Figure 4 and Figure 5 , respectively showing the process schematic diagram of the battery swap heavy truck based vehicle introduction number and the S13 in the charging and battery swap station scale prediction method of the application, and the process schematic diagram of the power demand prediction process of the charging and battery swap station service frequency of the application adapted to various operation scenarios. As shown in Figure 4 and Figure 5 , the S13 comprises the following steps:

[0097] S131, according to different operation scenarios, the battery swap heavy truck operation distance and the total battery swap frequency required by the battery swap heavy truck per day are calculated.

[0098] In this embodiment, different operation scenarios are analyzed, and the known transportation distance, rated mileage and daily operation frequency of the battery swap heavy truck and other parameters of the battery swap heavy truck are combined to calculate the daily battery swap frequency; wherein, the one-way transportation or round-trip transportation situation is considered; and then combined with the quantity of the introduced battery swap heavy truck or the replaced battery swap heavy truck, the total charging frequency required by the introduced battery swap heavy truck or the replaced battery swap heavy truck per day is calculated.

[0099] Specifically, the operation scenarios can be divided into two scenarios: battery swap heavy truck unit transportation and battery swap heavy truck round-trip transportation. That is: when the battery swap heavy truck is unit transportation, the situation that the vehicle is full loaded to the destination and then returns empty is considered.

[0100] (1) When the battery swap heavy truck is one-way transportation:

[0101] The battery swap heavy truck operation distance is: n*D tr ;

[0102] The calculation formula of the battery swap heavy truck daily battery swap frequency when one-way transportation is:

[0103]

[0104] The calculation formula of the total number of daily battery replacement of the battery replacement heavy truck in a certain period of time is:

[0105] N = Q * N single

[0106] wherein, D tr represents the distance of a single trip of the vehicle; n represents the daily operation frequency of the battery replacement heavy truck; D car represents the operation mileage under the rated load of the vehicle, unit: km; Q represents the number of battery replacement heavy trucks.

[0107] It should be noted that the above calculation process is illustrated by taking a single battery replacement heavy truck as an example.

[0108] (2) When the battery replacement heavy truck is for bidirectional transportation:

[0109] The actual running distance of the battery replacement heavy truck is: 2 * n * D tr ;

[0110] The calculation formula of the total number of daily battery replacement of the battery replacement heavy truck in a certain period of time is:

[0111]

[0112] The calculation formula of the total number of daily battery replacement of the battery replacement heavy truck in a certain period of time is:

[0113] N = Q * N return

[0114] wherein, D tr represents the distance of a single trip of the vehicle; n represents the daily operation frequency of the battery replacement heavy truck; D car represents the operation mileage under the rated load of the vehicle, unit: km; Q represents the number of battery replacement heavy trucks.

[0115] S132, based on the total number of daily battery replacement of the battery replacement heavy truck, the operation parameters of the battery charging and replacing station are calculated to obtain a battery charging and replacing station scale prediction model.

[0116] In this embodiment, based on the total number of daily battery replacement of the battery replacement heavy truck, and the operation mileage under the rated load of the vehicle, etc., the charging time of a single battery is calculated.

[0117] The operation parameters of the battery charging and replacing station include: daily total charging demand of the battery charging and replacing station, number of charging machines, number of battery replacement workshops, single battery replacement time, single battery charging time, etc. The service frequency of the battery charging and replacing station is affected by the number of charging machines, the number of battery replacement workshops, the single battery replacement time, and the single battery charging time. Among them, the number of charging machines of the battery charging and replacing station represents the maximum number of batteries that can be charged at the same time in the station; the single battery charging time depends on the charging power of the charging machine.

[0118] Specifically, the daily total charging demand calculation formula of the charging and battery swapping station is:

[0119] q D = Q*N*(k highest -k lowest )q B

[0120] wherein k highest represents the upper limit depth of battery charging and discharging, unit: %; k lowest represents the lower limit depth of battery charging and discharging, unit: %; q B represents the vehicle battery capacity, unit: kWh; Q represents the number of battery swapping heavy trucks; N represents the number of battery swapping times of the battery swapping heavy truck per day in total two-way transportation within a certain time period.

[0121] The calculation formula of the single battery charging time is:

[0122]

[0123] wherein T CH represents the single battery charging time, unit: min; P CH represents the charging machine charging power, unit: kWh / min; k highest represents the upper limit depth of battery charging and discharging, unit: %; k lowest represents the lower limit depth of battery charging and discharging, unit: %; q B represents the vehicle battery capacity, unit: kWh.

[0124] S14, based on the charging and battery swapping station scale prediction model, obtains the dynamic relationship between the charging and battery swapping equipment parameters and the battery swapping workshop parameters, so as to provide the investment operator with reasonable investment scale prediction and planning. Please refer to Figure 6 and Figure 7 , which respectively show the process schematic diagram of S14 in the vehicle introduction number and charging and battery swapping station scale prediction method based on the battery swapping heavy truck of the application and the process schematic diagram of the charging and battery swapping station scale prediction method based on the battery swapping heavy truck of the application and suitable for various operation scenarios. As shown in Figure 6 and Figure 7 , the S14 comprises the following steps:

[0125] S141, calculating the number of battery swapping workshops based on the charging and battery swapping station operation parameters.

[0126] In this embodiment, the number of battery swapping workshops is calculated based on the standard parameters of the charging and battery swapping station and the number of charging machines and other data.

[0127] The calculation formula of the number of battery swapping workshops is:

[0128]

[0129] wherein, N CH represents the number of charging machines owned by the charging and swapping station; T EX represents the single swapping time, unit: min.

[0130] S142, based on the number of charging and swapping stations and the number of charging machines, the number of charging services provided by a single charging and swapping station per day is calculated, and the dynamic relationship between the charging and swapping equipment parameters and the swapping station parameters of the charging and swapping station is obtained.

[0131] In this embodiment, based on the number of swapping stations and the charging time of a single battery, the charging and swapping equipment data and the dynamic relationship curve of the swapping station data of the charging and swapping station are established, and the number of charging services provided by a single charging and swapping station per day is calculated.

[0132] Specifically, the number of charging services provided by a single charging and swapping station per day is calculated by the following formula:

[0133]

[0134] wherein, T CH represents the charging time of a single battery, unit: min; T EX represents the single swapping time, unit: min; N CH represents the number of charging machines owned by the charging and swapping station; N EX the number of charging and swapping stations.

[0135] S143, according to the number of charging services provided by a single charging and swapping station per day, the final number of swapping stations and the number of charging machines owned by the charging and swapping station are obtained.

[0136] In this embodiment, when the number of charging services provided by a single charging and swapping station per day is greater than or equal to the number of swapping times of heavy-duty trucks per day in a certain time period, the number of charging machines owned by the charging and swapping station and the number of swapping stations are outputted;

[0137] When the number of charging services provided by a single charging and swapping station per day is less than the number of swapping times of heavy-duty trucks per day in a certain time period, the number of charging machines is substituted, and the above steps are executed in a loop until the result is outputted.

[0138] Specifically, the number greater than or equal to 0 in the total charging number N required by the heavy-duty truck introduced or replaced by the heavy-duty truck per day is substituted into the number of charging machines N CH owned by the charging and swapping station, and then the number of swapping stations N EX is calculated and substituted into the number of charging services provided by a single charging and swapping station per day N service in the calculation formula, and compared with the total charging number N required by the heavy-duty truck introduced or replaced by the heavy-duty truck per day.

[0139] When the number of daily charging services N provided by a single battery swap station service When the number of daily battery swap services N of the heavy truck with battery swap is greater than or equal to the total transportation times in a certain period, that is, when N service When N ≥ 0, output N CH , N EX ; otherwise, if N service When N ≥ 0, loop until the result is output.

[0140] The method of the application will be described below taking a common battery swap type pure electric motor new energy traction heavy truck 6x4 as an example.

[0141] First, determine the battery swap type pure electric motor new energy traction heavy truck 6x4, and determine its battery capacity, vehicle rated load, and data such as 100 km power consumption under rated load according to the vehicle type, which can calculate the running mileage under the rated load of the vehicle.

[0142] For example, the battery swap type pure electric motor new energy traction heavy truck 6x4 uses lithium iron phosphate battery, and the total vehicle power is 513 kWh, and the load capacity can reach more than 35 tons.

[0143] Then, by parameterizing the battery swap heavy truck model, operation parameters, operation scenarios and operation modes, combined with vehicle introduction parameters, a battery swap station scale prediction model is built.

[0144] Specifically, by analyzing the operation scenario of the vehicle model, the total transportation demand of the operator replacing or introducing vehicles is calculated, and then the daily transportation demand to be achieved is calculated, and the introduction or replacement amount of the battery swap heavy truck is calculated. Input the vehicle running distance, calculate the daily total charging demand of the introduced vehicle in this period, then calculate the number of charging machines and battery swap workshops of the battery swap station, and obtain the total charging times required by the introduced or replaced battery swap heavy truck per day through judgment.

[0145] For example, considering that a certain park needs to add 1 million tons per year, the operation is 365 days a year, the battery swap station operates 24 hours a day, the battery charge and discharge depth is considered to be 20% to 80%, the number of introduced vehicles in this period should be no less than 27, and the daily transportation should be more than 3 times. Assuming that the vehicle transportation distance is 100 km, and the vehicle operates in the full load to empty load mode, the total daily charging demand of the vehicle is 90 times, and the daily charging demand is 743.58 MWh. Assuming that it takes 40 minutes to fully charge a battery in the battery swap station, and 5 minutes for the battery swap process, then the battery swap station needs one battery swap workshop and at least 3 charging machines. Therefore, the battery swap type pure electric motor new energy traction heavy truck 6x4 needs one battery swap workshop and at least 3 charging machines in the battery swap station in the park.

[0146] The vehicle introduction number and the charging and battery swap station scale prediction method based on the battery swap heavy truck provided in the application can analyze the operation parameters, operation scenarios and operation modes of the battery swap heavy truck, calculate the battery swap heavy truck introduction demand based on the application scenario, parameterize various influencing factors of the battery swap heavy truck operation, combine the vehicle introduction parameters, and build a charging and battery swap station scale prediction model. The application is suitable for various application scenarios, can provide decision basis for the operators of the battery swap heavy truck and the operators of the charging and battery swap station, and is helpful for the investors to make investment scale more scientifically.

[0147] The protection scope of the vehicle introduction number and the charging and battery swap station scale prediction method based on the battery swap heavy truck is not limited to the step execution order listed in the embodiment, and the schemes realized by increasing, reducing or replacing the steps of the prior art according to the principle of the application are included in the protection scope of the application.

[0148] The embodiment additionally provides a computer readable storage medium having a computer program stored thereon, and the program is executed by a processor to implement the vehicle introduction number and the charging and battery swap station scale prediction method based on the battery swap heavy truck. Figure 1 The vehicle introduction number and the charging and battery swap station scale prediction method based on the battery swap heavy truck.

[0149] In any possible technical detail combination level, the application can be a system, a method and / or a computer program product. The computer program product can include a computer readable storage medium having computer readable program instructions stored therein to cause a processor to implement various aspects of the application.

[0150] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punched card or a hole and protrusion structure, and any suitable combination of the above. The computer readable storage medium used herein is not to be interpreted as a transitory signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (for example, an optical pulse through an optical fiber cable), or an electrical signal transmitted through a wire.

[0151] The computer readable program here described can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device. Computer readable program instructions for carrying out operations of the present application can be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions can execute entirely on the user's computing / processing device, partly on the user's computing / processing device, as a stand-alone software package, partly on the user's computing / processing device and partly on a remote computing / processing device or entirely on the remote computing / processing device. In the latter scenario, the remote computing / processing device can be connected to the user's computing / processing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present application.

[0152] The embodiment of the present application also provides a vehicle introduction number and charging and battery swapping station scale prediction system based on battery swapping heavy trucks, which can implement the vehicle introduction number and charging and battery swapping station scale prediction method based on battery swapping heavy trucks.

[0153] The vehicle introduction number and charging and battery swapping station scale prediction system based on battery swapping heavy trucks provided by the embodiment will be described in detail below in combination with the drawings.

[0154] The embodiment provides a vehicle introduction quantity and charging station scale prediction system based on battery swap heavy trucks.

[0155] Please refer to Figure 8 , which shows the principle structure schematic diagram of the vehicle introduction quantity and charging station scale prediction system based on battery swap heavy trucks in an embodiment of the present application. As shown in Figure 8 , the vehicle introduction quantity and charging station scale prediction system based on battery swap heavy trucks comprises an acquisition module 81, a quantity calculation module 82, a scale calculation module 83, and a prediction and planning module 84.

[0156] The acquisition module 81 is configured to set the introduced battery swap heavy truck model and determine the battery swap heavy truck operation parameters.

[0157] In the embodiment, the model of the introduced battery swap heavy truck is set according to the user demand, and the battery swap heavy truck operation parameters are determined according to the model of the battery swap heavy truck. The battery swap heavy truck operation parameters include but are not limited to the vehicle battery capacity, the power consumption per 100 kilometers under the rated load, the vehicle rated load, the battery charging and discharging depth, etc.

[0158] The quantity calculation module 82 is connected with the acquisition module 81 and is configured to calculate the daily total transport demand and charging demand of the introduced battery swap heavy truck based on the battery swap heavy truck operation parameters, and construct a battery swap heavy truck vehicle quantity prediction model and a charging demand model.

[0159] In the embodiment, the running mileage under the rated load of the vehicle is calculated based on the battery swap heavy truck operation parameters. The daily total transport demand of the introduced battery swap heavy truck is calculated by analyzing the battery swap heavy truck operation scenario, and the battery swap heavy truck vehicle quantity prediction model is obtained.

[0160] In the embodiment, the running mileage under the rated load of the vehicle is calculated by the parameters of the introduced battery swap heavy truck, such as the vehicle battery capacity, the power consumption per 100 kilometers under the rated load, the vehicle rated load, the battery charging and discharging depth, etc. The battery charging and discharging depth is generally set to have an upper limit and a lower limit, such as the upper limit of 90% and the lower limit of 10%, which can be set according to the actual situation.

[0161] The analysis of the battery swap heavy truck operation scenario includes two cases, i.e. the analysis of the daily total transport demand of the vehicle replaced by the operator or the introduced vehicle. According to the different operation scenarios of the battery swap heavy truck, the demand achieved by the operation scenario is analyzed, so that the total transport demand of the replaced vehicle or the total transport demand of the newly added vehicle is calculated, and then the total transport demand achieved per day is obtained. In combination with the data such as the daily operation frequency of the battery swap heavy truck and the vehicle rated load corresponding to the battery swap heavy truck of different models, the introduction quantity or the replacement quantity of the battery swap heavy truck can be calculated.

[0162] The scale calculation module 83 is configured to construct a scale prediction model of the charging and swapping station based on the battery swapping heavy truck running frequency and the introduced battery swapping heavy truck quantity prediction model and the charging demand model.

[0163] In this embodiment, the battery swapping heavy truck running distance and the total daily battery swapping frequency required by the battery swapping heavy truck are calculated according to different operation scenarios. The charging and swapping station operation parameters are calculated based on the total daily battery swapping frequency required by the battery swapping heavy truck, and the scale prediction model of the charging and swapping station is obtained.

[0164] In this embodiment, different operation scenarios are analyzed, and the daily battery swapping frequency is calculated in combination with the known transportation distance of the battery swapping heavy truck, the rated mileage, the daily running frequency of the battery swapping heavy truck and other parameters. The daily battery swapping frequency needs to consider the case of one-way transportation or round-trip transportation. In combination with the quantity of the introduced battery swapping heavy truck or the replaced battery swapping heavy truck, the total daily charging frequency required by the introduced battery swapping heavy truck or the replaced battery swapping heavy truck is calculated.

[0165] Specifically, the operation scenarios can be divided into two scenarios: battery swapping heavy truck unit transportation and battery swapping heavy truck round-trip transportation. That is, when the battery swapping heavy truck is in unit transportation, the case of empty return after full load transportation to the destination needs to be considered.

[0166] In this embodiment, the charging time of a single battery is calculated based on the total daily battery swapping frequency required by the battery swapping heavy truck and the running mileage under the rated load of the vehicle.

[0167] The charging and swapping station operation parameters include the total daily charging demand of the charging and swapping station, the number of charging machines, the number of battery swapping rooms, the single battery swapping time, the single battery charging time and other parameter contents. The service frequency provided by the charging and swapping station is affected by the number of self-owned charging machines of the charging and swapping station, the number of battery swapping rooms, the single battery swapping time and the single battery charging time. The number of self-owned charging machines of the charging and swapping station represents the maximum number of batteries that can be simultaneously charged in the station; the single battery charging time depends on the charging power of the charging machine.

[0168] The prediction and planning calculation module 84 is configured to obtain the dynamic relationship between the charging and swapping equipment parameters and the battery swapping room parameters of the charging and swapping station based on the scale prediction model of the charging and swapping station, so as to provide the investment operator with reasonable investment scale prediction and planning. The daily charging service frequency provided by a single charging and swapping station is calculated based on the number of battery swapping rooms and the number of charging machines, and the dynamic relationship between the charging and swapping equipment parameters and the battery swapping room parameters of the charging and swapping station is obtained. According to the daily charging service frequency provided by a single charging and swapping station, the final number of battery swapping rooms and the number of self-owned charging machines of the charging and swapping station are obtained.

[0169] In this embodiment, based on the standard parameters of the charging and swapping station and the data such as the number of charging machines, the number of battery swapping stations is calculated. Based on the number of battery swapping stations and the charging time of a single battery, a dynamic relationship curve of the charging and swapping station charging and swapping equipment data and the battery swapping station data is established, and the number of daily charging services that a single charging and swapping station can provide is calculated.

[0170] When the number of daily charging services that a single charging and swapping station can provide is greater than or equal to the number of daily battery swapping times of the heavy truck for total transportation in a certain time period, the number of charging machines and the number of battery swapping stations owned by the charging and swapping station are output; when the number of daily charging services that a single charging and swapping station can provide is less than the number of daily battery swapping times of the heavy truck for total transportation in a certain time period, the number of charging machines is returned, and the above steps are executed in a loop until the result is output.

[0171] Specifically, the number greater than or equal to 0 of the total charging times N required by the heavy truck for battery swapping or replacing the heavy truck vehicle in the current period is substituted into the number of charging machines N owned by the charging and swapping station CH , and the number of battery swapping stations N EX is calculated. service The number of daily charging services N that a single charging and swapping station can provide is substituted into the calculation formula

[0172] When the number of daily charging services N that a single charging and swapping station can provide is greater than or equal to the number of daily battery swapping times N of the heavy truck for total transportation in a certain time period, that is, when N service , the result is output. service , N CH , and N EX ; otherwise, if N service -N≧0, then the loop is executed until the result is output.

[0173] Based on the vehicle introduction number of the battery swapping heavy truck and the charging and swapping station scale prediction model, a vehicle introduction number and charging and swapping station scale prediction system based on the battery swapping heavy truck is built. For different battery swapping heavy truck models and various application scenarios and operation modes of heavy trucks, a vehicle introduction number and charging and swapping station scale prediction model suitable for various operation scenarios is established. Through parameterization of the battery swapping heavy truck model, operation parameters, operation scenarios and operation modes, combined with the vehicle introduction parameters, a charging and swapping station scale prediction model is built. The present application can be applied to various application scenarios, and can provide decision basis for operators who need to replace or introduce battery swapping heavy trucks and operators of charging and swapping stations, and can help investors to make more scientific investment scale.

[0174] It should be noted that the division of the above system modules is only a logical functional division, and all or part of them can be integrated into a physical entity or physically separated during actual implementation. These modules can all be implemented in the form of software called by a processing element; all in the form of hardware; or some modules in the form of software called by a processing element and some modules in the form of hardware. For example, the x module can be a separately established processing element, or it can be integrated into a certain chip of the above system, in addition, it can also be stored in the form of program code in the memory of the above system, and the function of the above x module is called and executed by a certain processing element of the above system. The implementation of other modules is similar. In addition, all or part of these modules can be integrated together or independently implemented. The processing element described herein can be an integrated circuit with signal processing capability. In the implementation process, each step of the above method or each module can be completed by the integrated logic circuit of the hardware in the processor element or the instructions in the form of software.

[0175] The above modules can be one or more integrated circuits configured to implement the above method, such as one or more application specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs), etc. For another example, when a certain module above is implemented in the form of program code called by a processing element, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call program code. For another example, these modules can be integrated together to implement in the form of system on a chip (SOC).

[0176] Please refer to Figure 9 , which shows the principle structure of the vehicle introduction number based on the battery replacement heavy truck and the charging and battery replacement station scale prediction device in an embodiment of the present application. As Figure 9As shown, the embodiment provides a vehicle introduction number and charging station scale prediction device based on battery swap heavy truck, which comprises a processor 91 and a memory 92; the memory 92 is used for storing a computer program; the processor 91 is connected with the memory 92 and used for executing the computer program stored in the memory 92, so that the vehicle introduction number and charging station scale prediction device based on battery swap heavy truck executes each step of the vehicle introduction number and charging station scale prediction method based on battery swap heavy truck as described above.

[0177] Preferably, the memory can include a random access memory (RAM) and can also include a non-volatile memory such as at least one disk memory.

[0178] The above processor can be a general processor including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0179] In summary, the vehicle introduction number and charging station scale prediction method based on battery swap heavy truck provided by the present application has the following beneficial effects:

[0180] The vehicle introduction number and charging station scale prediction method based on battery swap heavy truck provided by the present application establishes a prediction model for the number of vehicles introduced or replaced by an operator in various operation scenarios, builds a charging station scale prediction model by parameterizing the battery swap heavy truck model, operation parameters, operation scenarios and operation modes, and combining vehicle introduction parameters. That is, by analyzing the operation parameters, operation scenarios and operation modes of the battery swap heavy truck, the demand calculation of the battery swap heavy truck is established based on the application scenario, and the parameters of various influencing factors of the battery swap heavy truck operation are parameterized, combined with the vehicle introduction parameters, and a charging station scale prediction model is built. The present application is suitable for various application scenarios and can provide decision basis for operators who need to replace or introduce battery swap heavy trucks and operators of charging stations, which helps investors to make investment scale more scientifically.

[0181] The above embodiments are only illustrative of the principles of the present application and its efficacy, and are not intended to limit the present application. Any modification or change made by any person skilled in the art without departing from the spirit and scope of the present application shall be covered by the claims of the present application.

Claims

1. A method for predicting the number of vehicles introduced and the scale of a battery swap and charging station based on a battery swap heavy truck, characterized in that, The method comprises the following steps: Setting the introduced battery swap heavy truck model, determining the battery swap heavy truck operation parameters; Based on the battery swap heavy truck operation parameters, the daily total transport demand and charging demand of the introduced battery swap heavy truck are calculated, and a battery swap heavy truck quantity prediction model and a charging demand model are constructed; including: based on the battery swap heavy truck operation parameters, the running mileage under the rated load of the vehicle is calculated; the battery swap heavy truck operation scene is analyzed, the daily total transport demand of the introduced battery swap heavy truck is calculated, and the battery swap heavy truck quantity prediction model and the charging demand model are obtained; Based on the battery swap heavy truck operation frequency and the battery swap heavy truck quantity prediction model and the charging demand model, a charging and battery swap station scale prediction model is constructed; including: according to different operation scenes, the running distance of the battery swap heavy truck and the total battery swap frequency required by the battery swap heavy truck per day are calculated; based on the total battery swap frequency required by the battery swap heavy truck per day, the charging and battery swap station operation parameters are calculated, and the charging and battery swap station scale prediction model is obtained; Based on the charging and battery swap station scale prediction model, the dynamic relationship between the charging and battery swap equipment parameters and the battery swap yard parameters is obtained for the investment operator to make reasonable investment scale prediction and planning; including: the number of charging and battery swap yards is calculated based on the charging and battery swap station operation parameters; the daily charging service frequency provided by a single charging and battery swap station is calculated based on the number of charging and battery swap yards and the number of charging machines, and the dynamic relationship between the charging and battery swap equipment parameters and the battery swap yard parameters is obtained; according to the daily charging service frequency provided by a single charging and battery swap station, the final number of battery swap yards and the number of charging machines owned by the charging and battery swap station are obtained. 2.The method of claim 1, wherein, The battery swap heavy truck operation parameters include: vehicle battery capacity, 100 km power consumption under rated load, vehicle rated load, and battery charge and discharge depth; The calculation formula of the running mileage under the rated load of the vehicle is: wherein k highest represents the upper limit of the battery charge and discharge depth, unit: %; k lowest represents the lower limit of the battery charge and discharge depth, unit: %; q B represents the vehicle battery capacity, unit: kWh; q car represents the energy consumption per 100 km under the rated load, unit: kWh / 100km; D car represents the operating mileage of the vehicle under the rated load, unit: km. 3.The method of claim 1, wherein, The battery swap heavy truck operation scene includes: battery swap heavy truck replacement vehicles and introduced battery swap heavy trucks; analyzing the battery swap heavy truck operation scene, calculating the daily total transport demand of the introduced battery swap heavy truck, and obtaining the battery swap heavy truck quantity prediction model include the following steps: When the battery swap heavy truck operation vehicle is a replacement vehicle, the annual total transport volume of the replacement vehicle should at least remain flat to the original transport volume, and the daily transport volume to be achieved is calculated; Based on the daily transport volume to be achieved, the number of battery swap heavy trucks is calculated; The annual total transport volume calculation formula of the replacement vehicle is: W EX = W1N1Q1 + W2N2Q2 +... + W n N n Q n Wherein, W n represents the load of different vehicle models replaced by the operation plan; N n represents the annual operation times; Q n represents the number of holdings; When the battery swap heavy truck operation vehicle is a newly introduced vehicle, the annual total transport capacity needs to be analyzed and formulated, and the daily transport volume to be achieved is calculated; The calculation formula of the daily transport volume to be achieved is: Wherein, W in represents the total demand of annual transport capacity; n r.day represents the total number of annual operation days; The calculation formula of the number of battery swap heavy trucks is: Wherein, W represents the daily volume to be achieved; W car represents the rated load of the vehicle; n represents the daily operation frequency of the heavy truck. 4.The method of claim 1, wherein, According to different operation scenes, the running distance of the battery swap heavy truck and the total battery swap frequency required by the battery swap heavy truck per day are calculated, including the following steps: When the battery swap heavy truck is unidirectional transportation: The running distance of the battery replacement heavy truck is: n * D tr ; The calculation formula of the daily battery swap frequency of the battery swap heavy truck in unidirectional transportation is: The calculation formula of the daily battery swap frequency of the battery swap heavy truck in total unidirectional transportation within a certain period of time is: N = Q*N single wherein D tr represents the distance of a single trip of the vehicle; n represents the number of daily trips of the heavy-duty electric vehicle; D car represents the running distance under the rated load of the vehicle, unit: km; Q represents the number of heavy-duty electric vehicles When the battery swap heavy truck is bidirectional transportation: The actual running distance of the battery replacement heavy truck vehicle is: 2*n*D tr ; The calculation formula of the daily battery swap frequency of the battery swap heavy truck in bidirectional transportation is: The calculation formula of the daily battery swap frequency of the battery swap heavy truck in total bidirectional transportation within a certain period of time is: N = Q*N return wherein D tr represents the distance of a single trip of the vehicle; n represents the number of daily trips of the heavy-duty electric vehicle; D car represents the running distance under the rated load of the vehicle, unit: km; Q represents the number of heavy-duty electric vehicles. 5.The method of claim 1, wherein, The charging and battery swapping station operation parameters include: daily total charging demand of the charging and battery swapping station, number of charging machines, number of battery swapping workshops, single battery swapping time, and single battery charging time. The daily total charging demand calculation formula of the charging and battery swapping station is: q D = Q * N * (k highest -k lowest )q B wherein k highest represents the upper limit of the battery charge and discharge depth, unit: %; k lowest represents the lower limit of the battery charge and discharge depth, unit: %; q B represents the vehicle battery capacity, unit: kWh; Q represents the number of battery swap heavy truck vehicles; N represents the number of battery swap heavy truck daily battery swap times in a certain time period The single battery charging time calculation formula is: wherein T CH represents the single battery charging time, unit: min; P CH represents the charger charging power, unit: kWh / min; k highest represents the battery charge and discharge upper limit depth, unit: %; k lowest represents the battery charge and discharge lower limit depth, unit: %; q B represents the vehicle battery capacity, unit: kWh. 6.The method of claim 1, wherein, The charging and battery swapping workshop number calculation formula is: N CH represents the number of charging machines owned by the charging station; T EX represents the single battery swap time, unit: min; The single charging and battery swapping station daily charging service number calculation formula is: Wherein, T CH represents the charging time of a single battery, unit: min; T EX represents the single battery replacement time, unit: min; N CH N represents the number of self-owned charging machines of the charging station EX The number of charging and battery swapping workshops 7.The method of claim 1, wherein, According to the single charging and battery swapping station daily charging service number, the final battery swapping workshop number and the charging and battery swapping station self-owned charging machine number are obtained through the following steps: When the single charging and battery swapping station daily charging service number is greater than or equal to the total transportation time battery swapping heavy truck daily battery swapping number in a certain time period, the charging and battery swapping station self-owned charging machine number and the battery swapping workshop number are outputted. When the single charging and battery swapping station daily charging service number is less than the total transportation time battery swapping heavy truck daily battery swapping number in a certain time period, the charging machine number is returned, and the above steps are executed in a loop until the result is outputted. 8.A system for predicting a number of vehicles introduced based on a battery swap heavy truck and a scale of a battery charging and swapping station, characterized in that, It comprises: An acquisition module is configured to set an introduced battery swapping heavy truck model and determine battery swapping heavy truck operation parameters. A number calculation module is configured to calculate daily total transportation demand and charging demand of the introduced battery swapping heavy truck based on the battery swapping heavy truck operation parameters, and construct a battery swapping heavy truck number prediction model and a charging demand model, including: calculating a vehicle rated load running distance based on the battery swapping heavy truck operation parameters; analyzing a battery swapping heavy truck operation scenario, calculating daily total transportation demand and charging demand of the introduced battery swapping heavy truck, and obtaining the battery swapping heavy truck number prediction model and the charging demand model. A scale calculation module is configured to construct a charging and battery swapping station scale prediction model based on the battery swapping heavy truck running number and the battery swapping heavy truck number prediction model and the charging demand model, including: calculating a battery swapping heavy truck running distance and a daily total battery swapping number required by the battery swapping heavy truck according to different operation scenarios; calculating charging and battery swapping station operation parameters based on the daily total battery swapping number required by the battery swapping heavy truck, and obtaining the charging and battery swapping station scale prediction model. A prediction and planning module is configured to obtain a dynamic relationship between charging and battery swapping station charging and battery swapping equipment parameters and battery swapping workshop parameters based on the charging and battery swapping station scale prediction model, so as to provide reasonable investment scale prediction and planning for investors, including: calculating a charging and battery swapping workshop number based on charging and battery swapping station operation parameters; calculating a single charging and battery swapping station daily charging service number based on the charging and battery swapping workshop number and the charging machine number, obtaining the dynamic relationship between the charging and battery swapping station charging and battery swapping equipment parameters and the battery swapping workshop parameters; and judging according to the single charging and battery swapping station daily charging service number to obtain the final battery swapping workshop number and the charging and battery swapping station self-owned charging machine number. 9.A device for predicting a number of vehicles introduced and a scale of a charging and battery swapping station based on a battery swapping heavy truck. It comprises: A processor and a memory; The memory is configured to store a computer program; The processor is connected with the memory and is configured to execute the computer program stored in the memory, so that the vehicle introduction number based on the battery swapping heavy truck and the charging and battery swapping station scale prediction device execute the vehicle introduction number based on the battery swapping heavy truck and the charging and battery swapping station scale prediction method in any one of claims 1 to 7.

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