Flexible charging method, device and equipment for charging pile and storage medium

Abstract

The invention discloses a flexible charging method, device and equipment for a charging pile and a storage medium, and the method comprises the steps: obtaining battery related parameters and customer preference coefficients of a current charging automobile of the charging pile, the battery related parameters comprise a battery charge state, and the customer preference coefficients correspond to customer expected charging time; under the constraint of the expected charging time, screening an appropriate charging rate in a mode of calculating different actual charging times according to the state of charge of the battery and the charging rate of the system, and obtaining a candidate charging rate; calculating battery capacity total loss values corresponding to different candidate charging rates according to a preset battery capacity loss formula; and selecting the candidate charging rate corresponding to the minimum battery capacity total loss value as the optimal charging rate, and charging the current charging automobile. The technical problems that in the prior art, personalized preferences of customers are ignored, and charging is carried out by adopting a fixed charging strategy and parameters, so that the charging mode cannot meet the charging requirements of the customers, and battery life maintenance is not facilitated can be solved.

Description

Technical Field

[0001] The present application relates to the technical field of electric vehicle charging, and in particular to a charging stack flexible charging method, device, equipment and storage medium. Background Art

[0002] With the rapid development of electric vehicles, their number is increasing, and people have put forward higher requirements for electric vehicle charging devices. For example, different charging customers have different sensitivities to charging time and battery life, so in different situations, customers have different charging needs; how to meet the different needs of customers in different situations is an important technical issue currently being studied.

[0003] Existing charging methods often ignore the personalized needs of customers and are often based on fixed charging strategies and parameters, lacking comprehensive consideration of the characteristics of charging behavior. This static charging method not only fails to meet the personalized needs of customers, but is also not conducive to battery life maintenance. Summary of the invention

[0004] The present application provides a flexible charging method, device, equipment and storage medium for a charging stack, which is used to solve the technical problem that the prior art ignores the customer's personalized preferences, adopts fixed charging strategies and charging parameters, resulting in a charging method that cannot meet the customer's charging needs and is not conducive to battery life maintenance.

[0005] In view of this, the first aspect of the present application provides a charging stack flexible charging method, comprising:

[0006] Obtaining battery-related parameters and a customer preference coefficient of the vehicle currently being charged by the charging stack, wherein the battery-related parameters include a battery state of charge, and the customer preference coefficient corresponds to a customer's expected charging time;

[0007] Under the constraint of the expected charging time, a suitable charging rate is screened by calculating different actual charging times according to the battery state of charge and the system charging rate to obtain a candidate charging rate;

[0008] Calculate the total battery capacity loss value corresponding to different candidate charging rates according to a preset battery capacity loss formula;

[0009] The candidate charging rate corresponding to the smallest total battery capacity loss value is selected as the optimal charging rate to charge the currently charged vehicle.

[0010] Preferably, the step of obtaining the battery-related parameters and the customer preference coefficient of the vehicle currently being charged by the charging stack further includes:

[0011] Perform time division operation according to the start charging time of the charging vehicle to generate a time interval set;

[0012] A corresponding relationship is established between different preset preference coefficients and each time interval in the time interval set to obtain a preference expected time association set.

[0013] Preferably, under the constraint of the expected charging time, selecting a suitable charging rate by calculating different actual charging times according to the battery state of charge and the system charging rate to obtain a candidate charging rate includes:

[0014] calculating a plurality of actual charging times based on the battery state of charge and a plurality of system charging rates;

[0015] The system charging rates corresponding to the actual charging time that is less than or equal to the expected charging time are screened out to obtain candidate charging rates.

[0016] Preferably, the calculating the total battery capacity loss values ​​corresponding to the different candidate charging rates according to the preset battery capacity loss formula also includes:

[0017] Construct an initial battery capacity loss function based on the battery absolute temperature and the amount of power transferred by the battery during the charging process;

[0018] The initial battery capacity loss function is sorted and transformed based on the charging rate to obtain a preset battery capacity loss formula.

[0019] A second aspect of the present application provides a charging stack flexible charging device, comprising:

[0020] A data acquisition unit, used to acquire battery-related parameters and a customer preference coefficient of the vehicle currently being charged by the charging stack, wherein the battery-related parameters include a battery state of charge, and the customer preference coefficient corresponds to a customer's expected charging time;

[0021] A first screening unit is used to screen a suitable charging rate by calculating different actual charging times according to the battery state of charge and the system charging rate under the constraint of the expected charging time, so as to obtain a candidate charging rate;

[0022] A loss calculation unit, used to calculate the total battery capacity loss value corresponding to different candidate charging rates according to a preset battery capacity loss formula;

[0023] The second screening unit is used to select the candidate charging rate corresponding to the smallest total battery capacity loss value as the optimal charging rate to charge the currently charged vehicle.

[0024] Preferably, it also includes:

[0025] An interval division unit, used to divide the time period according to the start charging time of the charging vehicle and generate a time interval set;

[0026] The association establishing unit is used to establish a corresponding relationship between different preset preference coefficients and each time interval in the time interval set to obtain a preference expected time association set.

[0027] Preferably, the first screening unit is specifically used for:

[0028] calculating a plurality of actual charging times based on the battery state of charge and a plurality of system charging rates;

[0029] The system charging rates corresponding to the actual charging time that is less than or equal to the expected charging time are screened out to obtain candidate charging rates.

[0030] Preferably, it also includes:

[0031] An initial function building unit, used to build an initial battery capacity loss function according to the absolute temperature of the battery and the amount of power transmitted by the battery during the charging process;

[0032] The function arrangement and transformation unit is used to arrange and transform the initial battery capacity loss function based on the charging rate to obtain a preset battery capacity loss formula.

[0033] A third aspect of the present application provides a charging stack flexible charging device, the device comprising a processor and a memory;

[0034] The memory is used to store program code and transmit the program code to the processor;

[0035] The processor is used to execute the charging stack flexible charging method described in the first aspect according to the instructions in the program code.

[0036] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store program code, and the program code is used to execute the flexible charging method for the charging stack described in the first aspect.

[0037] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0038] In the present application, a flexible charging method for a charging stack is provided, including: obtaining battery-related parameters and a customer preference coefficient of a car currently being charged by the charging stack, the battery-related parameters including the battery state of charge, and the customer preference coefficient corresponding to the customer's expected charging time; under the constraint of the expected charging time, screening a suitable charging rate by calculating different actual charging times according to the battery state of charge and the system charging rate to obtain a candidate charging rate; calculating the total battery capacity loss values ​​corresponding to different candidate charging rates according to a preset battery capacity loss formula; selecting the candidate charging rate corresponding to the smallest total battery capacity loss value as the optimal charging rate to charge the currently charged car.

[0039] The flexible charging method for charging piles provided in the present application fully considers the personalized needs of customers based on the customer preference coefficient, calculates the battery capacity loss corresponding to different suitable charging rates on the basis of meeting the customer's expected time requirements, and selects the charging rate corresponding to the minimum loss, which is the optimal charging rate that can both meet the personalized needs of customers and minimize the battery charging loss. This process more comprehensively considers the trade-off between the customer's expected charging time and battery loss, can dynamically adjust the charging strategies of different customers, is more flexible and effective, and can also maintain battery life. Therefore, the present application can solve the technical problem that the prior art ignores the personalized preferences of customers, adopts fixed charging strategies and charging parameters, resulting in the charging method being unable to meet the charging needs of customers and is not conducive to the maintenance of battery life. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of a flow chart of a flexible charging method for a charging stack provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of the structure of a charging stack flexible charging device provided in an embodiment of the present application;

[0042] Figure 3 A schematic diagram of the charging rate of the charging stack flexible charging method under different working conditions provided in the application example of this application;

[0043] Figure 4 A schematic diagram of the charging time and battery capacity loss of the charging stack flexible charging method under different charging states provided in the application example of this application. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] For easier understanding, see Figure 1 , an embodiment of a flexible charging method for a charging stack provided in the present application includes:

[0046] Step 101: Obtain battery-related parameters and a customer preference coefficient of a vehicle currently being charged by the charging stack, wherein the battery-related parameters include a battery state of charge, and the customer preference coefficient corresponds to a customer's expected charging time.

[0047] Furthermore, step 101 further includes:

[0048] Perform time division operation according to the start charging time of the charging vehicle to generate a time interval set;

[0049] A corresponding relationship is established between different preset preference coefficients and each time interval in the time interval set to obtain a preference expected time association set.

[0050] It should be noted that the current charging car is the electric car of the customer who is charging at the charging pile at the current moment. The charging pile can obtain the battery-related parameters of the current charging car through charging equipment, such as a charging gun; battery-related parameters include but are not limited to the battery state of charge SOC and charging demand, which is the charging power required by the battery. The charging pile can also provide a setting panel, which provides multiple preset preference coefficients For customers to choose, and after selection, the customer preference coefficient of the current customer is generated.

[0051] Different customers have different charging requirements. For example, some customers are in a hurry and need to charge in a short time before leaving, regardless of whether the battery is fully charged. In this case, the charging stack needs to provide a fast charging strategy to charge them, shorten the customer's waiting time, and improve the customer's charging experience. In another case, the customer may not have time to worry about it, and the customer is more concerned about the battery life and does not want the battery capacity to be lost too much or too quickly. In this case, the charging stack needs to provide a relatively slow and friendly charging mode to reduce battery capacity loss and extend battery life.

[0052] Therefore, this embodiment proposes a preset preference coefficient The concept of "charging time" is adopted, and the preset preference coefficients are associated with multiple time intervals. When a customer selects a preset preference coefficient, it means that the customer has selected the expected charging time; that is, each preset preference coefficient in the preference expected time association set corresponds to a time period, and this time period is the customer's expected charging time.

[0053] In the process of constructing the association set of the preferred expected time, it is necessary to base it on the start charging time of the charging car. Taking the current charging car as an example, take its start charging time as the initial time, divide the charging time of the electric car into time intervals equal to the number of preset preference coefficients, and then establish an association relationship between the time intervals and the preset preference coefficients according to a certain time length rule. The customer selects a preset preference coefficient to obtain the customer preference coefficient and the corresponding time interval, i.e. the expected charging time; customers who are pressed for time can select the coefficient corresponding to a short time period, and those who are concerned about battery life can select the coefficient corresponding to a long time period. The preset preference coefficients of this embodiment The value is in the range of (0,1) and one decimal place is retained, such as 0.1, 0.7, etc. The closer the value is to 1, the more urgent the customer's charging time is and the faster the charging needs to be completed.

[0054] Step 102: Under the constraint of the expected charging time, a suitable charging rate is screened by calculating different actual charging times according to the battery state of charge and the system charging rate to obtain a candidate charging rate.

[0055] Further, step 102 includes:

[0056] Calculate multiple actual charging times based on battery state of charge and multiple system charging rates;

[0057] The system charging rates corresponding to the actual charging times that are less than or equal to the expected charging times are screened out to obtain candidate charging rates.

[0058] It should be noted that the charging stack can provide a variety of different system charging rates, namely the system charging power, or the system charging service level, so the system charging rate can be expressed as ,in, A sequence number indicating the system charging rate, and can be expressed as the slowest system charging rate, For fastest system charging rates.

[0059] Different system charging rates can be calculated based on the battery state of charge Actual charging time under :

[0060]

[0061] in, , represents the cumulative charging time of the i-th currently charging vehicle in the constant rate stage and the cumulative charging time in the variable rate stage; is the rated capacity of the battery; , , It represents the critical point, initial SOC and SOC leaving the charging pile when the i-th currently charged vehicle changes from the constant rate phase to the variable rate phase.

[0062] The constant rate stage and variable rate stage described here refer to the charging characteristics of the electric vehicle itself. The relationship between the charging rate and the battery state of charge SOC is as follows:

[0063]

[0064] in, , , They represent the current battery state of charge (SOC) of the currently charged vehicle, the minimum SOC specified by the battery manufacturer, and the SOC of the electric vehicle when it leaves the charging pile. According to this formula, the charging rate includes two stages: constant rate and variable rate. The charging rate in the first stage is constant until Exceed This critical point; the second stage is after exceeding the critical point, the charging rate will increase The price decreases linearly at this level.

[0065] Through the operation in step 101, a suitable time period can be selected according to the customer preference coefficient, and this time period is the customer's expected charging time; and different system charging rates Different actual charging times can be calculated ; By filtering according to the expected charging time, one, two or more candidate charging rates can be obtained; that is, according to the customer's preference for time, the charging stack may have different system charging rates to meet their charging needs and complete charging within their expected charging time. It is understandable that if only one actual charging time meets the constraint of the expected charging time, then there is no need to consider the subsequent battery capacity loss problem, and the system charging rate corresponding to the actual charging time can be directly selected. Just charge it; this means that the customer has a high time requirement and has not considered the battery loss issue, so the charging time is tight. If there are two or more candidate charging rates, you need to further calculate the corresponding total battery capacity loss value and select the candidate charging rate with the smaller loss to charge it.

[0066] Step 103: Calculate the total battery capacity loss values ​​corresponding to different candidate charging rates according to a preset battery capacity loss formula.

[0067] Furthermore, step 103, before that, also includes:

[0068] Construct an initial battery capacity loss function based on the battery absolute temperature and the amount of power transferred by the battery during the charging process;

[0069] The initial battery capacity loss function is rearranged and transformed based on the charging rate to obtain a preset battery capacity loss formula.

[0070] It should be noted that the preset battery capacity loss formula is the result obtained through formula transformation. The initial battery capacity loss function constructed based on the absolute temperature of the battery and the amount of power transmitted by the battery during the charging process is expressed as:

[0071]

[0072] in, is the battery capacity loss ratio, that is, the percentage of battery capacity loss relative to battery capacity, and B is the pre-factor. is the absolute temperature of the battery, R is the universal gas constant, which is 8.314 J / mol, is the activation energy obtained according to the Arrhenius law, is the power law factor, and the power law factor of lithium-ion batteries is 0.55; The amount of electricity transmitted by the battery during the charging process can be directly obtained.

[0073] It is understandable that the charging method is crucial for electric vehicles because it has a direct impact on the battery life. If charged in the wrong way, the performance and life of the battery will be significantly affected; battery capacity loss usually increases with the increase of charging rate, and the semi-empirical capacity loss model can determine the battery capacity loss of electric vehicles during charging, and takes into account the effects of charging rate, charging time and temperature.

[0074] For the activation energy in the initial battery capacity loss function and the pre-exponential factor B, both of which can be used to construct the Coulomb rate Function:

[0075]

[0076]

[0077] According to the above formula, the system charging rate can be combined Further deduction leads to:

[0078]

[0079]

[0080] in, =47.836; =1215; =9418.9; =36042; =370.3; =-31700, , , They represent the coefficients before the cubic term, square term, and linear term of the polynomial B, respectively. represents the constant term of the polynomial; Representing polynomials The coefficient before the first-order term, represents the constant term of the polynomial, is the battery capacity. Based on this, we can get the activation energy and the pre-exponential factor B on the system charging rate expression.

[0081] Next, considering that the battery capacity loss will increase exponentially with the increase of temperature, the absolute temperature of the battery It is also a function of the system charging rate and can be expressed as:

[0082]

[0083] in, is the battery thermal resistance of the electric vehicle, is the ambient temperature.

[0084] The amount of electricity transferred during the charging process It can be expressed as:

[0085]

[0086] in, for arrive The battery current during the period.

[0087] Since the charging rate changes continuously, it is necessary to calculate the battery capacity loss at each system charging rate during the entire charging process; by combining the above formulas and transforming them, the preset battery capacity loss formula can be obtained:

[0088]

[0089] in,

[0090]

[0091] in, represents the battery capacity loss in the i-th period, Represents the cumulative battery capacity loss in the i-th period and the i+1-th period.

[0092] If there are two or more candidate charging rates above, they can be substituted into the preset battery capacity loss formula to calculate the battery capacity loss value during the entire charging process, and further calculate the total battery capacity loss value during the entire charging process:

[0093]

[0094] in, Indicates the total number of time periods. represents the battery capacity loss value in the i-th time period, Indicates that the lth candidate charging rate The total battery capacity loss value under , that is, the cumulative loss value.

[0095] Step 104: Select the candidate charging rate corresponding to the minimum total battery capacity loss value as the optimal charging rate to charge the currently charged vehicle.

[0096] Under the condition of meeting the customer's expected charging time conditions, selecting the charging rate with less battery loss can meet the customer's charging needs and battery life maintenance to a certain extent. Therefore, the candidate charging rate corresponding to the smallest total battery capacity loss value is selected as the optimal charging rate. , to charge the current charging cars.

[0097] For ease of understanding, the present application provides an application example of a flexible charging method for a charging pile. It is assumed that each charging gun in the charging pile can provide 5 different charging service levels, that is, the system charging rate corresponds to 50~100kW, respectively, and is divided into five value segments of [50,60], [60,70], [70,80], [80,90], and [90,100]. The corresponding preference coefficient value ranges are [0,0.2], [0.2,0.4], [0.4,0.6], [0.6,0.8], and [0.8,1]. There is a corresponding correlation between the values ​​in the two value ranges, for example, 0.2 corresponds to 60. The number of electric vehicles connected to the charging pile for charging is 10, the battery models are exactly the same, and the initial SOC is different. In addition, electric vehicles equipped with the same type of battery follow the same charging rate curve, and the values ​​are the same regardless of the charging service level.

[0098] When customers prefer the shortest charging time and do not consider battery life, the input customer preference coefficient value is 1. At this time, the charging pile determines the optimal charging rate through a flexible charging method to minimize charging time and improve customer charging experience. In this scenario, the optimal charging rate obtained by all electric vehicles is 100kW. Figure 3 As shown in the working condition (A).

[0099] When customers prefer the longest battery life regardless of the length of charging time, the input customer preference index value is 0. At this time, the charger determines the optimal charging rate through a flexible charging method to maximize battery life and improve customer charging experience. In this scenario, the optimal charging rate for all electric vehicles is 50kW. Figure 3 As shown in the working condition (B).

[0100] Customer preferences for charging time and battery life are random: Customer preferences are random. Some customers prefer charging time, while others prefer battery life. Therefore, the input customer preference index value is a random value in the range of [0,1]. At this time, the charging stack determines the optimal charging rate through a flexible charging method to improve customer experience. Figure 3 As shown in the (C) working condition, the charging rate of 3 electric vehicles is 50 kW, which indicates that they prefer the longest battery life and do not consider the length of the charging time. The input value is 0 at this time; the charging rate of 2 electric vehicles is 100 kW, which indicates that they prefer the shortest charging time. The input value is 1 at this time; the charging rate of 1 electric vehicle is 70 kW, which indicates that he prefers battery life and has a certain charging time requirement. The input value is 0.4 at this time; the charging rate of 2 electric vehicles is 60 kW, which indicates that they prefer battery life and have a certain charging time requirement. The input value is 0.2 at this time; the charging power of 2 electric vehicles is 80 kW, which indicates that they prefer charging time and hope that the battery life will not decrease so quickly. The input value is 0.6 at this time.

[0101] See also Figure 4 It can be found that for all electric vehicles, a) has the shortest charging time and the largest battery capacity loss, corresponding to working condition A. b) has the longest charging time and the smallest battery capacity loss, corresponding to working condition B. The charging time and battery capacity loss in c) are different. Some electric vehicles have a longer charging time and a smaller battery capacity loss, some electric vehicles have a shorter charging time and a larger battery capacity loss, while others have a moderate charging time and a moderate battery capacity loss. This is due to the charging preferences of different customers, corresponding to working condition C.

[0102] The flexible charging method for the charging stack provided in the embodiment of the present application fully considers the personalized needs of customers based on the customer preference coefficient, calculates the battery capacity loss corresponding to different suitable charging rates on the basis of meeting the customer's expected time requirements, and selects the charging rate corresponding to the minimum loss, which is the optimal charging rate that can both meet the personalized needs of customers and minimize the battery charging loss. This process more comprehensively considers the trade-off between the customer's expected charging time and battery loss, can dynamically adjust the charging strategies of different customers, is more flexible and effective, and can also maintain the battery life. Therefore, the embodiment of the present application can solve the technical problem that the prior art ignores the personalized preferences of customers, adopts fixed charging strategies and parameter charging, resulting in the charging method failing to meet the charging needs of customers and is not conducive to the maintenance of battery life.

[0103] For easier understanding, see Figure 2 The present application provides an embodiment of a charging stack flexible charging device, including:

[0104] The data acquisition unit 201 is used to acquire the battery-related parameters and customer preference coefficient of the vehicle currently being charged by the charging stack, the battery-related parameters including the battery state of charge, and the customer preference coefficient corresponding to the customer's expected charging time;

[0105] A first screening unit 202 is used to screen a suitable charging rate by calculating different actual charging times according to the battery state of charge and the system charging rate under the constraint of the expected charging time, so as to obtain a candidate charging rate;

[0106] A loss calculation unit 203 is used to calculate the total battery capacity loss value corresponding to different candidate charging rates according to a preset battery capacity loss formula;

[0107] The second screening unit 204 is used to select the candidate charging rate corresponding to the minimum total battery capacity loss value as the optimal charging rate to charge the current charging vehicle.

[0108] Furthermore, it also includes:

[0109] The interval division unit 205 is used to divide the time period according to the charging start time of the charging vehicle to generate a time interval set;

[0110] The association establishing unit 206 is used to establish a corresponding relationship between different preset preference coefficients and each time interval in the time interval set to obtain a preference expected time association set.

[0111] Furthermore, the first screening unit 202 is specifically used for:

[0112] Calculate multiple actual charging times based on battery state of charge and multiple system charging rates;

[0113] The system charging rates corresponding to the actual charging times that are less than or equal to the expected charging times are screened out to obtain candidate charging rates.

[0114] Furthermore, it also includes:

[0115] An initial function construction unit 207, used to construct an initial battery capacity loss function according to the absolute temperature of the battery and the amount of power transmitted by the battery during the charging process;

[0116] The function arrangement and transformation unit 208 is used to arrange and transform the initial battery capacity loss function based on the charging rate to obtain a preset battery capacity loss formula.

[0117] The present application also provides a charging stack flexible charging device, the device comprising a processor and a memory;

[0118] The memory is used to store the program code and transmit the program code to the processor;

[0119] The processor is used to execute the flexible charging method of the charging stack in the above method embodiment according to the instructions in the program code.

[0120] The present application also provides a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the flexible charging method for the charging stack in the above method embodiment.

[0121] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0122] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0124] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions for executing all or part of the steps of the method described in each embodiment of the present application through a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (full name in English: Read-Only Memory, English abbreviation: ROM), random access memory (full name in English: Random Access Memory, English abbreviation: RAM), disk or optical disk and other media that can store program codes.

[0125] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A flexible charging method for a charging stack, characterized in that: include: Obtaining battery-related parameters and a customer preference coefficient of the vehicle currently being charged by the charging stack, wherein the battery-related parameters include a battery state of charge, and the customer preference coefficient corresponds to a customer's expected charging time; Under the constraint of the expected charging time, a suitable charging rate is screened by calculating different actual charging times according to the battery state of charge and the system charging rate to obtain a candidate charging rate; Calculate the total battery capacity loss value corresponding to different candidate charging rates according to a preset battery capacity loss formula; The candidate charging rate corresponding to the smallest total battery capacity loss value is selected as the optimal charging rate to charge the currently charged vehicle.

2. The flexible charging method for charging stack according to claim 1, characterized in that: The obtaining of battery-related parameters and customer preference coefficients of the vehicle currently being charged by the charging stack also includes: Perform time division operation according to the start charging time of the charging vehicle to generate a time interval set; A corresponding relationship is established between different preset preference coefficients and each time interval in the time interval set to obtain a preference expected time association set.

3. The flexible charging method for charging stack according to claim 1, characterized in that: Under the constraint of the expected charging time, selecting a suitable charging rate by calculating different actual charging times according to the battery state of charge and the system charging rate to obtain a candidate charging rate includes: calculating a plurality of actual charging times based on the battery state of charge and a plurality of system charging rates; The system charging rates corresponding to the actual charging time that is less than or equal to the expected charging time are screened out to obtain candidate charging rates.

4. The flexible charging method for charging stack according to claim 1, characterized in that: The method further comprises: calculating the total battery capacity loss value corresponding to different candidate charging rates according to a preset battery capacity loss formula; Construct an initial battery capacity loss function based on the battery absolute temperature and the amount of power transferred by the battery during the charging process; The initial battery capacity loss function is sorted and transformed based on the charging rate to obtain a preset battery capacity loss formula.

5. A charging stack flexible charging device, characterized in that: include: A data acquisition unit, used to acquire battery-related parameters and a customer preference coefficient of the vehicle currently being charged by the charging stack, wherein the battery-related parameters include a battery state of charge, and the customer preference coefficient corresponds to a customer's expected charging time; A first screening unit is used to screen a suitable charging rate by calculating different actual charging times according to the battery state of charge and the system charging rate under the constraint of the expected charging time, so as to obtain a candidate charging rate; A loss calculation unit, used to calculate the total battery capacity loss value corresponding to different candidate charging rates according to a preset battery capacity loss formula; The second screening unit is used to select the candidate charging rate corresponding to the minimum total battery capacity loss value as the optimal charging rate to charge the currently charged vehicle.

6. The charging stack flexible charging device according to claim 5, characterized in that: Also includes: An interval division unit, used to divide the time period according to the start charging time of the charging vehicle and generate a time interval set; The association establishing unit is used to establish a corresponding relationship between different preset preference coefficients and each time interval in the time interval set to obtain a preference expected time association set.

7. The charging stack flexible charging device according to claim 5, characterized in that: The first screening unit is specifically used for: calculating a plurality of actual charging times based on the battery state of charge and a plurality of system charging rates; The system charging rates corresponding to the actual charging time that is less than or equal to the expected charging time are screened out to obtain candidate charging rates.

8. The charging stack flexible charging device according to claim 5, characterized in that: Also includes: An initial function building unit, used to build an initial battery capacity loss function according to the absolute temperature of the battery and the amount of power transmitted by the battery during the charging process; The function arrangement and transformation unit is used to arrange and transform the initial battery capacity loss function based on the charging rate to obtain a preset battery capacity loss formula.

9. A charging stack flexible charging device, characterized in that: The device comprises a processor and a memory; The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the flexible charging method for a charging stack according to any one of claims 1 to 4 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes, and the program codes are used to execute the charging stack flexible charging method according to any one of claims 1 to 4.

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