Charging billing method and device, equipment and storage medium

Abstract

The invention provides a charging billing method and device, equipment and a storage medium. The method comprises the following steps: receiving a charging request; after the electric vehicle is connected with the charging pile, determining a target storage battery model of the electric vehicle according to the output current and the output voltage of the charging pile; querying a historical charging order quantity of the current charging user on a charging pile management platform according to the user information; if it is determined that the current charging user is a first type of user according to the number of historical charging orders and the target storage battery model exists in historical storage battery classification data, a first target historical charging order is obtained and analyzed based on a big data AI analysis algorithm, and the current remaining battery capacity of the electric vehicle is determined; and according to the current residual battery capacity, budgeting the charging cost required by the charging of the current charging user. According to the method, the charging cost of different battery capacities can be accurately estimated every time by considering the battery capacity of the storage battery of the electric vehicle, and the satisfaction degree of a user to the charging service provided by the charging pile can be improved.

Description

Technical Field

[0001] The present application relates to the field of charging technology, and in particular to a charging billing method, device, equipment and storage medium. Background Art

[0002] With the country's promotion of new energy, electric vehicles continue to grow, and the charging facilities supporting electric vehicles (such as charging piles) are also developing rapidly accordingly.

[0003] At present, charging piles usually use corresponding charging methods combined with pre-deduction methods to settle charging charges for electric vehicles. Current charging methods usually include the following: (1) Time-based charging: Charging piles charge according to charging time, such as charging per hour or per minute; (2) Electricity-based charging: Charging piles charge according to the amount of electricity consumed during charging, such as charging per kilowatt-hour; (3) Fixed fee charging: Regardless of time and electricity consumption, a fixed fee is charged.

[0004] However, the current charging billing method has the following limitations:

[0005] (1) The current charging method does not support charging based on battery capacity.

[0006] (II) Currently, many users are reluctant to deduct the prepayment first. For example, most prepayments are set at 5 yuan, which users think is too much. However, if the prepayment is set too low, a large number of users will not be able to fully charge their batteries at once. For example, for users with larger battery capacities, if the prepayment is set too low, the prepayment may be used up before the battery is fully charged.

[0007] (iii) Due to battery safety considerations, the capacity of the rechargeable battery needs to be limited, but the user cannot accurately limit the capacity of the rechargeable battery.

[0008] In summary, the current charging billing method cannot effectively improve the user's satisfaction with the charging service provided by the charging pile due to the above limitations. Therefore, it is necessary to provide a charging billing solution that can accurately estimate the charging costs of different battery capacities to improve the user's satisfaction with the charging service provided by the charging pile. Summary of the invention

[0009] The embodiments of the present application provide a charging billing method, device, equipment and storage medium to solve the problems existing in the related technologies. The technical solutions are as follows:

[0010] In a first aspect, an embodiment of the present application provides a charging billing method, including:

[0011] Receiving a charging request, wherein the charging request includes user information of a current charging user and charging pile information;

[0012] After the electric vehicle is connected to the charging pile, the target battery model of the current charging user is determined according to the output current and output voltage of the charging pile;

[0013] Querying the number of historical charging orders of the current charging user on the charging pile management platform according to the user information;

[0014] If it is determined that the current charging user is a first-category user according to the number of historical charging orders, and the target battery model exists in the historical battery classification data, then a first target historical charging order is obtained, the first-category user is a user with at least M historical charging orders, M is an integer greater than 2, the historical battery classification data includes historical charging orders classified by battery model based on the charging user as a dimension, and the first target historical charging order is a historical charging order corresponding to the target battery model among all historical charging orders of the current charging user;

[0015] Analyzing the first target historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle;

[0016] The charging fee required for the current charging user to charge is estimated according to the current remaining battery capacity.

[0017] In one embodiment, analyzing the first target historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle includes:

[0018] Counting the remaining capacity corresponding to each historical charging order in the first target historical charging order;

[0019] Based on the big data AI analysis algorithm, the remaining capacity corresponding to each historical charging order is analyzed to determine the current remaining battery capacity of the electric vehicle.

[0020] In one embodiment, analyzing the remaining capacity corresponding to each historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle includes:

[0021] Calculate the average remaining capacity of the remaining capacity corresponding to each of the historical charging orders;

[0022] If, based on the big data AI analysis algorithm, it is determined that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity does not exceed the preset floating threshold, the remaining capacity corresponding to the historical charging order closest to the current time in the first target historical charging order is used as the current remaining battery capacity;

[0023] If, based on the big data AI analysis algorithm, it is analyzed and determined that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity partially exceeds the preset floating threshold, the average value will be used as the current remaining battery capacity.

[0024] In one implementation, based on the current remaining battery capacity, estimating the charging fee required for the current charging user to charge includes:

[0025] Determine the charging time required for the current charging user to charge according to the current remaining battery capacity;

[0026] Determine the charging power interval corresponding to the charging of the electric vehicle, and determine the charging billing unit price corresponding to the current charging user according to the charging interval;

[0027] The charging fee required for the current charging user to charge this time is estimated according to the charging time and the charging billing unit price.

[0028] In one embodiment, the historical battery classification data further includes: the available power level corresponding to each type of battery model based on the charging user; the method further includes:

[0029] After the current charging is completed, the current charging order of the current charging user is obtained;

[0030] Obtaining the remaining battery capacity of the electric vehicle after the charging is completed according to the charging order;

[0031] Calculating a target battery SOC of the electric vehicle according to the remaining battery capacity and the rated battery capacity corresponding to the target battery model;

[0032] Determining a target available power level of the target battery model according to the target battery SOC and a correspondence between a preset battery SOC and an available power level;

[0033] If it is determined that the target available power level is consistent with the available power level corresponding to the target battery model in the historical battery classification data, the current charging order is classified into the historical charging order corresponding to the target battery model of the current charging user;

[0034] If it is determined that the target available power level is inconsistent with the available power level corresponding to the target battery model in the historical battery classification data, it is determined that the electric vehicle has a battery replacement, battery energy consumption has decreased, or the battery is abnormal, and new historical battery classification data is created;

[0035] The current charging order is filed into the new historical battery classification data.

[0036] In one embodiment, the method further comprises:

[0037] If the current charging user is determined to be the first category user according to the number of historical charging orders, but the target battery model does not exist in the historical battery classification data, or if the current charging user is determined to be the second category user according to the number of historical charging orders, then a second target historical charging order is obtained, the second category user is a user with less than M historical charging orders, and the second target historical charging order is a historical charging order corresponding to the target battery model among all historical charging orders of the charging management platform;

[0038] Analyzing the second target historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle;

[0039] The charging fee required for the current charging user to charge is estimated according to the current remaining battery capacity.

[0040] In one embodiment, the method further comprises:

[0041] If the current charging user is determined to be the first category user according to the number of historical charging orders, but the target battery model does not exist in the historical battery classification data, or if the current charging user is determined to be the second category user according to the number of historical charging orders, then the rated battery capacity of the electric vehicle is determined according to the target battery model;

[0042] The charging fee required for the current charging user to charge the battery is estimated according to the rated battery capacity.

[0043] In a second aspect, an embodiment of the present application further provides a charging billing device, including:

[0044] A receiving unit, configured to receive a charging request, wherein the charging request includes user information of a current charging user;

[0045] A query unit, configured to query the number of historical charging orders of the current charging user on a charging pile management platform according to the user information;

[0046] A first determination unit, configured to determine a target battery model of the current charging user according to an output current and an output voltage of the charging pile after the electric vehicle is connected to the charging pile;

[0047] a processing unit, configured to obtain a first target historical charging order if it is determined that the current charging user is a first category user according to the number of historical charging orders, and the target battery model exists in the historical battery classification data, wherein the first category user is a user with at least M historical charging orders, M is an integer greater than 2, the historical battery classification data includes historical charging orders classified by battery model based on the charging user as a dimension, and the first target historical charging order is a historical charging order corresponding to the target battery model among all historical charging orders of the current charging user;

[0048] A second determination unit is used to analyze the first target historical charging order based on a big data AI analysis algorithm to determine a current remaining battery capacity of the electric vehicle;

[0049] The budget unit is used to budget the charging fee required for the current charging user to charge this time according to the current remaining battery capacity.

[0050] In one embodiment, when the second determination unit is used to analyze the first target historical charging order based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle, it is specifically used to:

[0051] Counting the remaining capacity corresponding to each historical charging order in the first target historical charging order;

[0052] Based on the big data AI analysis algorithm, the remaining capacity corresponding to each historical charging order is analyzed to determine the current remaining battery capacity of the electric vehicle.

[0053] In one embodiment, when the second determination unit is used to analyze the remaining capacity corresponding to each historical charging order based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle, it is specifically used to:

[0054] Calculate the average remaining capacity of the remaining capacity corresponding to each of the historical charging orders;

[0055] If, based on the big data AI analysis algorithm, it is determined that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity does not exceed the preset floating threshold, the remaining capacity corresponding to the historical charging order closest to the current time in the first target historical charging order is used as the current remaining battery capacity;

[0056] If, based on the big data AI analysis algorithm, it is analyzed and determined that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity partially exceeds the preset floating threshold, the average value will be used as the current remaining battery capacity.

[0057] In one implementation, when the budget unit is used to budget the charging fee required for the current charging user to charge this time according to the current remaining battery capacity, it is specifically used to:

[0058] Determine the charging time required for the current charging user to charge according to the current remaining battery capacity;

[0059] Determine the charging power interval corresponding to the charging of the electric vehicle, and determine the charging billing unit price corresponding to the current charging user according to the charging interval;

[0060] The charging fee required for the current charging user to charge this time is estimated according to the charging time and the charging billing unit price.

[0061] In one embodiment, the historical battery classification data further includes: the available power level corresponding to each type of battery model based on the charging user; the processing unit is further configured to:

[0062] After the current charging is completed, the current charging order of the current charging user is obtained;

[0063] Obtaining the remaining battery capacity of the electric vehicle after the charging is completed according to the charging order;

[0064] Calculating a target battery SOC of the electric vehicle according to the remaining battery capacity and the rated battery capacity corresponding to the target battery model;

[0065] Determining a target available power level of the target battery model according to the target battery SOC and a correspondence between a preset battery SOC and an available power level;

[0066] If it is determined that the target available power level is consistent with the available power level corresponding to the target battery model in the historical battery classification data, the current charging order is classified into the historical charging order corresponding to the target battery model of the current charging user;

[0067] If it is determined that the target available power level is inconsistent with the available power level corresponding to the target battery model in the historical battery classification data, it is determined that the electric vehicle has a battery replacement, battery energy consumption has decreased, or the battery is abnormal, and new historical battery classification data is created;

[0068] The current charging order is filed into the new historical battery classification data.

[0069] In one embodiment, the processing unit is further configured to: if it is determined according to the user information that the current charging user is the first category user, but the target battery model does not exist in the historical battery classification data, or if it is determined according to the user information that the current charging user is the second category user, then obtain a second target historical charging order, the second category user being a user with less than M historical charging orders, and the second target historical charging order being a historical charging order corresponding to the target battery model in the full amount of historical charging orders of the charging management platform;

[0070] The second determination unit is further used to: analyze the second target historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle;

[0071] The budget unit is further used to: budget the charging fee required for the current charging user to charge this time according to the current remaining battery capacity.

[0072] In one embodiment, the processing unit is further configured to: if the current charging user is determined to be the first category user according to the number of historical charging orders, but the target battery model does not exist in the historical battery classification data, or if the current charging user is determined to be the second category user according to the number of historical charging orders, determine the rated battery capacity of the electric vehicle according to the target battery model;

[0073] The budget unit is further used to: budget the charging fee required for the current charging user to charge this time according to the rated battery capacity.

[0074] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a memory and a processor, wherein the memory stores instructions, and the instructions are loaded and executed by the processor to implement a method in any one of the above-mentioned aspects, wherein the memory and the processor communicate with each other through an internal connection path.

[0075] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored. When the computer program runs on a computer, the method in any one of the above-mentioned embodiments is implemented.

[0076] The advantages or beneficial effects of the above technical solution include at least:

[0077] This application can take the battery capacity of the electric vehicle's battery itself into consideration, and can accurately budget the charging costs of different battery capacities each time. When the user pre-deducts the charging fee based on the budget, the cost requirements for this charging can be met, thereby improving the user's satisfaction with the charging service provided by the charging pile.

[0078] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present application will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in the present application and should not be regarded as limiting the scope of the present application.

[0080] Figure 1 A flowchart of a charging billing method provided in an embodiment of the present application;

[0081] Figure 2 A structural block diagram of a charging calculation device provided in an embodiment of the present application;

[0082] Figure 3 A structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0083] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present application. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0084] Figure 1 The flowchart of the charging billing method according to an embodiment of the present application is shown. The execution subject of the method may be a charging pile management platform, or other devices that interact with the charging pile management platform, which is not limited in the present embodiment. Figure 1 As shown, the method may include the following steps:

[0085] S10: Receive a charging request.

[0086] In one embodiment, the charging request may include, but is not limited to, user information of the current charging user and charging pile information. The user information may include, but is not limited to, a unique user number. The unique user number may be a mobile phone number, or may be obtained by numbering in other ways, which is not limited in the present embodiment.

[0087] As an example, the current charging user can initiate a charging request to the charging pile management platform through a user terminal (such as a mobile phone, etc.). For example, the current charging user first plugs the charging plug of the electric vehicle into the socket of the charging pile, then selects the charging pile on the mini program of the charging pile management platform through the user terminal, and then clicks the charging control on the mini program to initiate the charging request. Correspondingly, the charging pile management platform receives the charging request.

[0088] S11. After the electric vehicle is connected to the charging pile, the target battery model of the current charging user is determined according to the output current and output voltage of the charging pile.

[0089] In one embodiment, after the electric vehicle is connected to the charging pile, the target battery model of the current charging user can be determined based on the output current and output voltage of the charging pile. For example, the corresponding relationship between the output current and output voltage of the charging pile and the battery model of the electric vehicle can be pre-stored. Then, after the electric vehicle is connected to the charging pile, when the output current and output voltage of the charging pile are obtained, the target battery model of the current charging user can be determined based on the corresponding relationship.

[0090] In one embodiment, the battery model may include but is not limited to: battery model and battery capacity.

[0091] S12. Query the number of historical charging orders of the current charging user on the charging pile management platform according to the user information.

[0092] In one implementation, after receiving a charging request, the number of historical charging orders of the current charging user may be queried on a charging pile management platform based on user information.

[0093] In specific implementation, the embodiment of the present application does not limit the execution order of step S11 and step S12. For example, step S11 and step S12 can be executed simultaneously, or step S11 and step S12 can be executed in a corresponding sequence.

[0094] S13, judging whether the current charging user is a first-category user according to the number of historical charging orders. If the current charging user is a first-category user, executing step S14, otherwise determining that the current charging user is a second-category user, executing step S18 or executing step S21.

[0095] In one implementation, the first category of users may be users with at least M historical charging orders, where M is an integer greater than 2. The M historical charging orders may all be full-time automatic-stop charging orders.

[0096] In specific implementation, M can be specifically set according to actual needs, such as a value of 5, as long as it can meet the data quantity requirements of big data AI analysis. This embodiment of the present application does not limit this.

[0097] In one implementation, the second category of users may be users with less than M historical charging orders. If user B has 0 historical charging orders, user B may be a user who has registered on the charging pile management platform but has not charged, or a user who has newly registered on the charging pile management platform.

[0098] In one embodiment, if the number of historical charging orders is greater than or equal to M, it is determined that the current charging user is a first-category user, in which case step S14 can be executed. Alternatively, if the number of historical charging orders is less than M or 0, it is determined that the current charging user is a second-category user, in which case step S18 or step S21 can be executed.

[0099] S14, judging whether the target battery model exists in the historical battery classification data. If the target battery model exists in the historical battery classification data, executing step S15, otherwise executing step S18 or executing step S21.

[0100] In one embodiment, the historical battery classification data may include, but is not limited to: historical charging orders classified by battery model based on the charging user dimension.

[0101] In one implementation, the historical battery classification data may be obtained in the following manner:

[0102] The first step is to count all historical charging orders.

[0103] During specific implementation, all historical charging orders on the charging pile management platform can be counted.

[0104] The second step is to analyze all historical charging orders according to voltage specifications or current specifications to determine the battery model corresponding to each historical charging order.

[0105] In the specific implementation, all historical charging orders can be analyzed according to voltage specifications or current specifications based on the corresponding big data AI intelligent analysis algorithm to determine the battery model corresponding to each historical charging order.

[0106] As an example, you can obtain multiple factors such as battery capacity, voltage, current, etc. based on all historical charging orders, combine AI intelligent learning and intelligent analysis, summarize multiple factors that affect battery capacity, and then identify and confirm the corresponding battery model based on voltage specifications or current specifications. For example, you can pre-process all historical charging orders by clearing and sorting (removing irrelevant information, such as orders that were not terminated normally). Then, classify by user dimensions, extract data on factors that affect battery capacity, such as battery capacity, voltage, current, etc., from each historical charging order, and then determine the battery model corresponding to each historical charging order based on these data.

[0107] For example, taking only voltage and current factors into consideration, the corresponding battery model can be determined in the following way:

[0108] (1) The output voltage is between 36V--42VDC, so the battery model is 36V

[0109] ①The output current is 1.5A, then the battery capacity is 10AH;

[0110] ②The output current is 1.6A, so the battery capacity is 12AH.

[0111] (2) The output voltage is between 48V--59VDC, so the battery model is 48V

[0112] ①The output current is 1.7A, then the battery capacity is 10AH;

[0113] ②The output current is 1.8A, then the battery capacity is 12AH;

[0114] ③The output current is 2.0A, then the battery capacity is 14AH;

[0115] ④The output current is 2.3A, then the battery capacity is 17AH;

[0116] ⑤If the output current is 2.5A, the battery capacity is 20AH.

[0117] The third step is to classify all historical orders based on charging users and battery models to obtain historical battery classification data.

[0118] In specific implementation, historical charging orders with the same battery model may be clustered for the same charging user.

[0119] As an example, if user A has a total of 100 historical charging orders and there are two battery models, namely 36V12AH and 48V17AH, then after clustering the historical charging orders with the same battery model, the obtained battery classification data can be: user A has a total of 30 historical charging orders with a battery model of 36V12AH, and user A has a total of 70 historical charging orders with a battery model of 48V17AH.

[0120] S15. Obtain the first target historical charging order.

[0121] In one embodiment, the first target historical charging order may include, but is not limited to: historical charging orders corresponding to the target battery model in all historical charging orders of the current charging user. For example, taking the above example, if the target battery model is 48V17AH, then in this case, 70 historical charging orders of user A with a battery model of 48V17AH can be obtained.

[0122] S16. Analyze the historical charging orders of the first target based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle.

[0123] In one implementation, the remaining capacity corresponding to each historical charging order in the first target historical charging order may be counted; then, based on the big data AI analysis algorithm, the remaining capacity corresponding to each historical charging order may be analyzed to determine the current remaining battery capacity of the electric vehicle.

[0124] As an example, during the charging process, the charging pile management platform will record the output voltage, output current and charging time of the charging pile, so it can be understood that the output voltage, output current and charging time corresponding to each historical charging order are known. According to the following formula (1), the remaining battery capacity corresponding to each historical charging order can be calculated. For the current charging user, there are many historical charging orders according to each battery model classification, that is, the target battery model will correspond to multiple remaining battery capacities.

[0125] Remaining battery capacity (mAh) = output voltage (V) × output current (mA) × charging time (h) / 1000 (1)

[0126] In this case, the multiple remaining battery capacities can be analyzed based on the big data AI analysis algorithm to determine the current remaining battery capacity corresponding to the target battery model. For example, machine learning technology can be used to automatically identify the pattern of the multiple remaining battery capacities to derive the current remaining battery capacity corresponding to the target battery model.

[0127] Exemplarily, the average remaining capacity of the remaining capacity corresponding to each historical charging order can be calculated first; then, based on the big data AI analysis algorithm, the remaining capacity corresponding to each historical charging order is compared and analyzed with the average remaining capacity. If the analysis determines that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity does not exceed the preset floating threshold, the remaining capacity corresponding to the historical charging order closest to the current time in the first target historical charging order is used as the current remaining battery capacity. Alternatively, if the analysis determines that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity partially exceeds the preset floating threshold, the average value is used as the current remaining battery capacity.

[0128] Among them, the "part" can be set according to specific needs, for example, it can refer to one or more, and the embodiment of the present application does not limit this. The preset floating threshold can also be set according to actual needs, for example, it can be set to 0.5, and the embodiment of the present application does not limit this.

[0129] In the embodiment of the present application, by executing step S16, the output voltage and output current of the charging pile can be analyzed and processed to calculate the current remaining battery capacity corresponding to the target battery model.

[0130] S17. Estimate the charging fee required for the current charging user based on the current remaining battery capacity.

[0131] In one implementation, the charging time required for the current charging user to charge this time can be determined based on the current remaining battery capacity; and then the charging fee required for the current charging user to charge this time can be estimated based on the charging time.

[0132] As an example, the charging time required for the current charging user to charge this time can be determined according to the current remaining battery capacity and the current output current and current output voltage of the charging pile according to the following formula (2).

[0133] Charging time = (current remaining battery capacity / current output current) × current output voltage (2)

[0134] As another example, the user can select the target power for charging on the mini program of the charging pile management platform. If the user does not select, the default selection is to charge to 100%. When the user selects the target power for charging, the estimated charging time when the battery is fully charged to 100% can be calculated according to the current remaining battery capacity and the current output current and current output voltage of the charging pile according to the above formula (2). Then, based on the current remaining capacity, target power and estimated charging time, determine the charging time required for the current charging user to charge this time. For example, based on the current remaining capacity, target power and estimated charging time, the charging time required for the current charging user to charge this time can be determined according to the following formula (3).

[0135]

[0136] In this example, since the battery will be consumed accordingly with the frequency of use, after the user selects the target power, the above formula (3) can be used to calculate a more accurate charging time, thereby facilitating a more accurate charging cost budget.

[0137] As an example, the charging price corresponding to the electric vehicle can be determined, and then the charging fee required for the electric vehicle for this charging can be estimated according to the charging time and the charging price. The charging price can be fixed (can be set according to actual needs) or determined according to the charging power.

[0138] For example, the charging price corresponding to each charging power range can be configured in the following tiered charging method, and then the historical full charging orders in the charging pile management platform are analyzed to count the charging power ranges corresponding to each battery model in the previous charging process. After that, the charging power range corresponding to the electric vehicle can be determined according to the target battery model of the electric vehicle, and the corresponding charging price can be obtained.

[0139] Tiered charging method based on charging power:

[0140] Level 1: Charging price is 0.16 yuan / hour, and the corresponding charging power range is 0-120 watts;

[0141] Level 2: Charging price is 0.2 yuan / hour, and the corresponding charging power range is 121W-200W;

[0142] Tier 3: Charging price is 0.25 yuan / hour, and the corresponding charging power range is 201W-300W;

[0143] Level 4: Charging price is 0.35 yuan / hour, and the corresponding charging power range is 301W-500W;

[0144] Level 5: Charging price is 0.43 yuan / hour, and the corresponding charging power range is 501W-700W;

[0145] Level 6: Charging charge price is 1 yuan / hour, and the corresponding charging power range is 701W-1000W.

[0146] In the embodiment of the present application, by executing steps S10 to S17, the battery capacity of the electric vehicle's battery itself can be considered, and the current remaining battery capacity of the electric vehicle's battery can be accurately determined each time to budget the charging cost required for this charging, thereby being able to accurately budget the charging costs of different battery capacities. When the user pre-deducts the charging cost according to the budget, the cost requirements for this charging can be met, thereby improving the user's satisfaction with the charging service provided by the charging pile.

[0147] S18. Obtain the second target historical charging order.

[0148] In one embodiment, the second target historical charging order may be a historical charging order corresponding to the target battery model among all historical charging orders of the charging management platform. It can be understood that when the current charging user is a second type of user, the corresponding historical charging order may not be obtained according to the charging user dimension, but only the corresponding historical charging order may be obtained according to the target battery model.

[0149] S19. Analyze the historical charging orders of the second target based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle.

[0150] In one implementation, the implementation of step S19 is the same as or similar to the implementation of the above-mentioned step S16, and will not be repeated again in this embodiment of the present application.

[0151] S20: Estimate the charging fee required for the current charging user based on the current remaining battery capacity.

[0152] In one implementation, the implementation of step S20 is the same as or similar to the implementation of step S17 described above, and will not be described in detail in this embodiment of the present application.

[0153] In the embodiment of the present application, by executing steps S10-S14 and S18-S20, the battery capacity of the electric vehicle's battery itself can be considered, and the current remaining battery capacity of the electric vehicle's battery can be accurately determined each time to budget the charging cost required for this charging, thereby being able to accurately budget the charging costs of different battery capacities. When the user pre-deducts the charging cost according to the budget, the cost requirements for this charging can be met, thereby improving the user's satisfaction with the charging service provided by the charging pile.

[0154] S21. Determine the rated battery capacity of the electric vehicle according to the target battery model.

[0155] For example, if the target battery model is 36V12AH, then it can be determined that the rated battery capacity of the electric vehicle is 12AH.

[0156] S22: Estimate the charging fee required for the current charging user based on the rated battery capacity.

[0157] In one implementation, the charging time of the electric vehicle can be determined based on the rated battery capacity; and based on the charging time, the charging fee required for the current charging user to charge the vehicle can be estimated.

[0158] As an example, the charging time of the electric vehicle can be determined according to the rated battery capacity and the current output current and current output voltage of the charging pile according to the following formula (4).

[0159] Charging time = (rated battery capacity / current output current) × current output voltage (4)

[0160] Among them, the method of estimating the charging fee required for the current charging user to charge this time according to the charging time in step S21 is the same or similar to the method of estimating the charging fee required for the current charging user to charge this time according to the charging time in the above-mentioned step S17, and the embodiments of the present application will not be repeated here.

[0161] In the embodiment of the present application, by executing steps S10-S14 and S21-S22, the charging cost can be budgeted according to the rated battery capacity for charging users who are second-category users and whose battery models do not have historical battery classification data. That is, the charging costs of different battery capacities can be accurately budgeted for new users or users who have never charged their batteries. When the user makes a pre-deduction according to the budgeted charging cost, the cost requirements for this full charging can be met, thereby improving the user's satisfaction with the charging service provided by the charging pile.

[0162] In an available scenario provided in an embodiment of the present application, if the current charging user is a first-category user and the target battery model exists in the historical battery classification data, then after the current charging is completed, the current charging user's current charging order can be obtained, and then the target available power level of the target battery model can be determined based on the current charging order.

[0163] For example, this charging order can record the remaining battery capacity of the electric vehicle after the charging is completed (i.e., the above-mentioned current remaining battery capacity), and calculate the target battery SOC of the electric vehicle based on the remaining battery capacity and the rated battery capacity corresponding to the target battery model. For example, the target battery SOC can be calculated according to the following formula (5) based on the remaining battery capacity and the rated battery capacity corresponding to the target battery model. Afterwards, the target available power level of the target battery model can be determined based on the corresponding relationship between the target battery SOC and the preset battery SOC and the available power level.

[0164]

[0165] Among them, SOC is the current state of charge of the battery, that is, the target battery SOC, SOC 0 is the initial state of charge of the battery, I is the battery charge and discharge current, Q is the rated battery capacity, and ∫Idt is the cumulative effect of I over time t, i.e., the remaining battery capacity.

[0166] As an example, the correspondence between the battery SOC and the available power level can be: the battery SOC is 80%-100%, and the corresponding available power level is 1; the battery SOC is 60%-80%, and the corresponding available power level is 2; the battery SOC is 40%-60%, and the corresponding available power level is 3; the battery SOC is below 40%, and the corresponding available power level is 4.

[0167] In this scenario, if it is determined that the target available power level is consistent with the available power level corresponding to the target battery model in the historical battery classification data, the current charging order is classified into the historical charging order corresponding to the target battery model of the current charging user. If it is determined that the target available power level is inconsistent with the available power level corresponding to the target battery model in the historical battery classification data, it is determined that the electric vehicle has a battery replacement, battery energy consumption has decreased, or the battery is abnormal, and new historical battery classification data is created; then the current charging order is archived in the new historical battery classification data.

[0168] Since the same user may have replaced the battery even if the battery model is the same, for example, battery 1 has insufficient capacity and is replaced with battery 2, or the battery may be aged, in the embodiment of the present application, it is determined whether the target available power level is consistent with the available power level corresponding to the target battery model in the historical battery classification data to determine whether there is a difference between the two, so as to accurately determine the battery energy consumption.

[0169] The embodiment of the present application can classify the current charging order into the historical charging orders corresponding to the target battery model of the current charging user when the target available power level is consistent with the available power level corresponding to the target battery model in the historical battery classification data. This can be cyclically mined and analyzed in accordance with the current energy consumption of the battery, so that the budget result for the charging costs of different battery capacities is more accurate, which facilitates the accurate budgeting of the charging costs for the next charging order of the electric vehicle.

[0170] The embodiment of the present application creates new historical battery classification data when it is determined that the target available power level is inconsistent with the available power level corresponding to the target battery model in the historical battery classification data, and then archives the current charging order into the new historical battery classification data. On the basis of retaining the original historical battery classification data, the current charging order can be additionally archived, so that when the target available power level of subsequent charging orders is still inconsistent with the available power level corresponding to the target battery model in the historical battery classification data, these subsequent charging orders and the current charging order are re-analyzed to obtain new historical battery classification data, which can further accurately budget the charging costs of different battery capacities, thereby facilitating improving user satisfaction with the charging service provided by the charging pile.

[0171] In summary, the charging billing method provided in the embodiment of the present application can take the battery capacity of the electric vehicle's battery itself into consideration, and can accurately budget the charging costs of different battery capacities each time. When the user pre-deducts the payment based on the budgeted charging cost, the cost demand for this charging can be met, thereby improving the user's satisfaction with the charging service provided by the charging pile.

[0172] Figure 2 FIG. 1 is a block diagram showing a charging billing device according to an embodiment of the present application. Figure 2 As shown, the device may include:

[0173] The receiving unit 100 is used to receive a charging request, where the charging request includes user information of a current charging user;

[0174] A query unit 200 is used to query the number of historical charging orders of the current charging user on the charging pile management platform according to the user information;

[0175] The first determination unit 300 is used to determine the target battery model of the current charging user according to the output current and output voltage of the charging pile after the electric vehicle is connected to the charging pile;

[0176] The processing unit 400 is configured to obtain a first target historical charging order if it is determined that the current charging user is a first-category user according to the number of historical charging orders, and the target battery model exists in the historical battery classification data, wherein the first-category user is a user with at least M historical charging orders, where M is an integer greater than 2, and the historical battery classification data includes historical charging orders classified by battery model based on the charging user as a dimension, and the first target historical charging order is a historical charging order corresponding to the target battery model among all historical charging orders of the current charging user;

[0177] The second determining unit 500 is used to analyze the first target historical charging order based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle;

[0178] The budget unit 600 is used to budget the charging fee required by the current charging user for this charging according to the current remaining battery capacity.

[0179] In one embodiment, when the second determination unit 500 is used to analyze the first target historical charging order based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle, it is specifically used to:

[0180] Counting the remaining capacity corresponding to each historical charging order in the first target historical charging order;

[0181] Based on the big data AI analysis algorithm, the remaining capacity corresponding to each historical charging order is analyzed to determine the current remaining battery capacity of the electric vehicle.

[0182] In one embodiment, when the second determining unit 500 is used to analyze the remaining capacity corresponding to each historical charging order based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle, it is specifically used to:

[0183] Calculate the average remaining capacity of each historical charging order;

[0184] If it is determined based on the big data AI analysis algorithm that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity does not exceed the preset floating threshold, the remaining capacity corresponding to the historical charging order closest to the current time in the first target historical charging order is used as the current remaining battery capacity;

[0185] If, based on the big data AI analysis algorithm, it is determined that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity partially exceeds the preset floating threshold, the average value will be used as the current remaining battery capacity.

[0186] In one implementation, when the budget unit 600 is used to budget the charging fee required for the current charging user to charge this time according to the current remaining battery capacity, it is specifically used to:

[0187] Determine the charging time required for the current charging user based on the current remaining battery capacity;

[0188] Determine the charging power range corresponding to the electric vehicle charging, and determine the charging billing unit price corresponding to the current charging user according to the charging range;

[0189] According to the charging time and charging billing unit price, estimate the charging fee required for the current charging user.

[0190] In one embodiment, the historical battery classification data further includes: the available power level corresponding to each type of battery model based on the charging user; the processing unit 400 is further used to:

[0191] After the current charging is completed, the current charging order of the current charging user is obtained;

[0192] Obtain the remaining battery capacity of the electric vehicle after the charging is completed according to the charging order;

[0193] Calculate the target battery SOC of the electric vehicle based on the remaining battery capacity and the rated battery capacity corresponding to the target battery model;

[0194] Determine the target available power level of the target battery model according to the corresponding relationship between the target battery SOC and the preset battery SOC and available power level;

[0195] If it is determined that the target available power level is consistent with the available power level corresponding to the target battery model in the historical battery classification data, the current charging order is classified into the historical charging order corresponding to the target battery model of the current charging user;

[0196] If it is determined that the target available power level is inconsistent with the available power level corresponding to the target battery model in the historical battery classification data, it is determined that the electric vehicle has a battery replacement, battery energy consumption has decreased, or the battery is abnormal, and new historical battery classification data is created;

[0197] Archive this charging order into the new historical battery classification data.

[0198] In one embodiment, the processing unit 400 is further configured to: if it is determined according to the user information that the current charging user is a first-category user, but the target battery model does not exist in the historical battery classification data, or if it is determined according to the user information that the current charging user is a second-category user, then obtain a second target historical charging order, the second-category user is a user with less than M historical charging orders, or a user newly registered on the charging pile management platform, and the second target historical charging order is a historical charging order corresponding to the target battery model in the full amount of historical charging orders on the charging management platform;

[0199] The second determination unit 500 is further used to: analyze the second target historical charging order based on the big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle;

[0200] The budget unit 600 is further used to budget the charging fee required by the current charging user for this charging according to the current remaining battery capacity.

[0201] In one embodiment, the processing unit 400 is further configured to: if the current charging user is determined to be a first-category user according to the number of historical charging orders, but the target battery model does not exist in the historical battery classification data, or if the current charging user is determined to be a second-category user according to the number of historical charging orders, determine the rated battery capacity of the electric vehicle according to the target battery model;

[0202] The budget unit 600 is further used to budget the charging fee required by the current charging user for this charging according to the rated battery capacity.

[0203] The functions of each unit of the charging billing device in the embodiment of the present application can be found in the corresponding description in the above method, and will not be repeated here.

[0204] Figure 3 FIG. 1 is a block diagram showing a structure of an electronic device according to an embodiment of the present application. Figure 3 As shown, the electronic device includes: a memory 1000 and a processor 2000. The memory 1000 stores instructions, and the instructions are loaded and executed by the processor 2000 to implement the charging billing method in the above embodiment. The number of the memory 1000 and the processor 2000 can be one or more.

[0205] The electronic device also includes:

[0206] The communication interface 3000 is used to communicate with external devices and perform data exchange transmission.

[0207] If the memory 1000, the processor 2000 and the communication interface 3000 are implemented independently, the memory 1000, the processor 2000 and the communication interface 3000 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0208] Optionally, in a specific implementation, if the memory 1000, the processor 2000 and the communication interface 3000 are integrated on a chip, the memory 1000, the processor 2000 and the communication interface 3000 can communicate with each other through an internal interface.

[0209] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program runs on a computer, the method provided in the embodiment of the present application is implemented.

[0210] An embodiment of the present application also provides a chip, which includes a processor for calling and executing instructions stored in a memory, so that a communication device equipped with the chip executes the method provided by the embodiment of the present application.

[0211] An embodiment of the present application also provides a chip, including: an input interface, an output interface, a processor and a memory, wherein the input interface, the output interface, the processor and the memory are connected via an internal connection path, and the processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the method provided in the embodiment of the application.

[0212] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor supporting the Advanced RISC Machines (ARM) architecture.

[0213] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory, and may also include a non-volatile random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct rambus RAM (DR RAM).

[0214] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the present application is generated in whole or in part. 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 transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0215] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0216] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0217] Any process or method description in the flow chart or otherwise described herein can be understood to represent a module, fragment or portion of a code including one or more executable instructions for implementing the steps of a specific logical function or process. And the scope of the preferred embodiment of the present application includes other implementations, in which the functions may not be performed in the order shown or discussed, including in a substantially simultaneous manner or in a reverse order according to the functions involved.

[0218] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, which can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processor or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0219] It should be understood that the various parts of the present application can be implemented with hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method can be completed by instructing the relevant hardware through a program, which can be stored in a computer-readable storage medium, and when the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0220] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a disk or an optical disk, etc.

[0221] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A charging billing method, characterized in that: include: Receiving a charging request, wherein the charging request includes user information of a current charging user and charging pile information; After the electric vehicle is connected to the charging pile, the target battery model of the current charging user is determined according to the output current and output voltage of the charging pile; Querying the number of historical charging orders of the current charging user on the charging pile management platform according to the user information; If it is determined that the current charging user is a first-category user according to the number of historical charging orders, and the target battery model exists in the historical battery classification data, then a first target historical charging order is obtained, the first-category user is a user with at least M historical charging orders, M is an integer greater than 2, the historical battery classification data includes historical charging orders classified by battery model based on the charging user as a dimension, and the first target historical charging order is a historical charging order corresponding to the target battery model among all historical charging orders of the current charging user; Analyzing the first target historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle; The charging fee required for the current charging user to charge is estimated according to the current remaining battery capacity.

2. The method according to claim 1, characterized in that: Analyzing the first target historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle includes: Counting the remaining capacity corresponding to each historical charging order in the first target historical charging order; Based on the big data AI analysis algorithm, the remaining capacity corresponding to each historical charging order is analyzed to determine the current remaining battery capacity of the electric vehicle.

3. The method according to claim 2, characterized in that Analyzing the remaining capacity corresponding to each historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle includes: Calculate the average remaining capacity of the remaining capacity corresponding to each of the historical charging orders; If, based on the big data AI analysis algorithm, it is determined that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity does not exceed the preset floating threshold, the remaining capacity corresponding to the historical charging order closest to the current time in the first target historical charging order is used as the current remaining battery capacity; If, based on the big data AI analysis algorithm, it is analyzed and determined that the absolute value between the remaining capacity corresponding to each historical charging order and the average remaining capacity partially exceeds the preset floating threshold, the average value will be used as the current remaining battery capacity.

4. The method according to claim 1, characterized in that According to the current remaining battery capacity, the estimated charging fee required for the current charging user to charge this time includes: Determine the charging time required for the current charging user to charge this time according to the current remaining battery capacity; Determine the charging power interval corresponding to the charging of the electric vehicle, and determine the charging billing unit price corresponding to the current charging user according to the charging interval; The charging fee required for the current charging user to charge this time is estimated according to the charging time and the charging billing unit price.

5. The method according to claim 1, characterized in that The historical battery classification data also includes: the available power level corresponding to each type of battery model based on the charging user; the method also includes: After the current charging is completed, the current charging order of the current charging user is obtained; Obtaining the remaining battery capacity of the electric vehicle after the charging is completed according to the charging order; Calculating a target battery SOC of the electric vehicle according to the remaining battery capacity and the rated battery capacity corresponding to the target battery model; Determining a target available power level of the target battery model according to the target battery SOC and a correspondence between a preset battery SOC and an available power level; If it is determined that the target available power level is consistent with the available power level corresponding to the target battery model in the historical battery classification data, the current charging order is classified into the historical charging orders corresponding to the target battery model of the current charging user; If it is determined that the target available power level is inconsistent with the available power level corresponding to the target battery model in the historical battery classification data, it is determined that the electric vehicle has a battery replacement, battery energy consumption has decreased, or the battery is abnormal, and new historical battery classification data is created; The current charging order is filed into the new historical battery classification data.

6. The method according to any one of claims 1 to 5, characterized in that The method further comprises: If the current charging user is determined to be the first category user according to the number of historical charging orders, but the target battery model does not exist in the historical battery classification data, or if the current charging user is determined to be the second category user according to the number of historical charging orders, then a second target historical charging order is obtained, the second category user is a user with less than M historical charging orders, and the second target historical charging order is a historical charging order corresponding to the target battery model among all historical charging orders of the charging management platform; Analyzing the second target historical charging order based on a big data AI analysis algorithm to determine the current remaining battery capacity of the electric vehicle; The charging fee required for the current charging user to charge is estimated according to the current remaining battery capacity.

7. The method according to any one of claims 1 to 5, characterized in that The method further comprises: If the current charging user is determined to be the first category user according to the number of historical charging orders, but the target battery model does not exist in the historical battery classification data, or if the current charging user is determined to be the second category user according to the number of historical charging orders, then the rated battery capacity of the electric vehicle is determined according to the target battery model; The charging fee required for the current charging user to charge the battery is estimated according to the rated battery capacity.

8. A charging billing device, characterized in that: include: A receiving unit, configured to receive a charging request, wherein the charging request includes user information of a current charging user; A query unit, configured to query the number of historical charging orders of the current charging user on a charging pile management platform according to the user information; A first determination unit, configured to determine a target battery model of the current charging user according to an output current and an output voltage of the charging pile after the electric vehicle is connected to the charging pile; a processing unit, configured to obtain a first target historical charging order if it is determined that the current charging user is a first category user according to the number of historical charging orders, and the target battery model exists in the historical battery classification data, wherein the first category user is a user with at least M historical charging orders, M is an integer greater than 2, the historical battery classification data includes historical charging orders classified by battery model based on the charging user as a dimension, and the first target historical charging order is a historical charging order corresponding to the target battery model among all historical charging orders of the current charging user; A second determination unit is used to analyze the first target historical charging order based on a big data AI analysis algorithm to determine a current remaining battery capacity of the electric vehicle; The budget unit is used to budget the charging fee required for the current charging user to charge this time according to the current remaining battery capacity.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores instructions, and the instructions are loaded and executed by the processor to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed on a computer, the method according to any one of claims 1 to 7 is implemented.

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