Vehicle cloud system, battery pack data sampling method and abnormal vehicle end determination method

Abstract

The invention discloses a vehicle cloud system, a battery pack data sampling method and an abnormal vehicle end determination method. The vehicle cloud system comprises a vehicle end and a cloud end. The vehicle end is used for sampling voltage data and current data of the battery pack in real time to obtain data sampling points; determining the data sampling points meeting a preset condition as effective sampling points, and transmitting the effective sampling points and the corresponding timestamps to the cloud in an associated manner; the cloud end is used for calculating a battery pack SOC value corresponding to the effective sampling point; according to the timestamp, the battery pack SOC value and a preset extreme value, effective sampling points in a preset time window range are selected, an effective sampling point set is obtained, and the battery pack SOC value extreme value of the effective sampling point set is larger than the preset extreme value; calculating and obtaining battery cell consistency parameters of the battery pack according to the effective sampling point set; and determining the vehicle end with abnormal battery cell consistency as an abnormal vehicle end according to the battery cell consistency parameter. According to the application, the accuracy of judging the consistency of the battery cells can be improved, and the network flow cost and the data storage cost are reduced.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicle technology, and specifically to a vehicle-cloud system, a battery pack data sampling method, and an abnormal vehicle-side determination method. Background Art

[0002] In the existing vehicle-to-cloud system, the current data of the charging stage is generally transmitted in real time from the vehicle to the cloud. The cloud receives the current data and stores it in a database, and uses the current data and the corresponding time to integrate and calculate the change in the battery cell capacity on the vehicle side, so as to judge the consistency of each battery cell based on the change in battery cell capacity.

[0003] However, because the existing technology only selects the current data during the charging phase, the credibility of the obtained battery cell capacity change is low, which affects the accuracy of the vehicle-side battery cell consistency judgment. In addition, real-time transmission of current data requires large network traffic costs and cloud data storage costs. Summary of the invention

[0004] In view of this, the present application provides a vehicle-to-cloud system, a battery pack data sampling method, and an abnormal vehicle-side determination method, which are used to improve the accuracy of battery cell consistency judgment and reduce the network traffic cost of the vehicle-to-cloud system and the data storage cost of the cloud. The technical solution of the present application is as follows: In a first aspect, the present application provides a vehicle-cloud system, comprising a vehicle side and a cloud side, wherein the vehicle side comprises a plurality of battery packs, and the cloud side is communicatively connected with the plurality of vehicle sides; the vehicle side is used to: sample the voltage data and current data of the battery pack in real time to obtain data sampling points; determine the data sampling points that meet preset conditions as valid sampling points, and transmit the valid sampling points and the corresponding timestamps to the cloud side in association; the cloud side is used to: calculate the SOC value of the battery pack corresponding to the valid sampling points; select the valid sampling points within a preset time window according to the timestamp, the battery pack SOC value and the preset extreme value to obtain a valid sampling point set, wherein the battery pack SOC value extreme value of the valid sampling point set is greater than the preset extreme value; calculate and obtain the cell consistency parameters of the battery pack according to the valid sampling point set; determine the vehicle side with abnormal cell consistency as an abnormal vehicle side according to the cell consistency parameters.

[0005] In one embodiment of the present application, determining that a data sampling point that meets a preset condition is a valid sampling point, and transmitting the valid sampling point and the corresponding timestamp to the cloud in association, includes: calculating the net battery pack power, pure ohmic voltage drop, and polarization voltage drop components of the data sampling point based on the voltage data and the current data; determining that a change in the net battery pack power is greater than a preset change, determining that the pure ohmic voltage drop is less than a first threshold, and determining that the polarization voltage drop component is less than a second threshold, determining that the corresponding data sampling point is the valid sampling point; wherein, the change in the net battery pack power is the change in the net battery pack power relative to the net battery pack power of the last valid sampling point.

[0006] In one embodiment of the present application, the effective sampling points include cell voltage, cumulative balanced power of cells, net power of battery pack, pure ohmic voltage drop and polarization voltage drop component; the calculation of cell consistency parameters of the battery pack based on the effective sampling point set includes: calculating the maximum difference value of the cell SOC of each effective sampling point set according to the cell voltage; screening and eliminating the effective sampling point set whose maximum difference value of the cell SOC is less than a third threshold to obtain a retained sampling point set; calculating the cell capacity of each cell in the retained sampling point set according to the cumulative balanced power of cells, the net power of the battery pack, the pure ohmic voltage drop and the polarization voltage drop component; and obtaining the cell consistency parameter according to the cell capacity.

[0007] In an embodiment of the present application, the step of calculating the cell consistency parameter of the battery pack according to the valid sampling point set further includes: screening and eliminating the valid sampling points in the valid sampling point set that are within a preset SOC value range.

[0008] In one embodiment of the present application, the calculating the cell capacity of each cell in the retained sampling point set includes: calculating the cell SOC value corresponding to the retained sampling point set according to the pure ohmic voltage drop and the polarization voltage drop component; calculating the cell charge change value corresponding to the retained sampling point set according to the cell SOC value, the cell accumulated balanced charge and the net charge of the battery pack; calculating the cell capacity of each cell in the retained sampling point set according to the cell charge change value and the cell SOC value.

[0009] In one embodiment of the present application, the calculation of the battery cell SOC value corresponding to the retained sampling point set includes: calculating the battery cell open circuit voltage of each battery cell in the retained sampling point set according to the pure ohmic voltage drop and the polarization voltage drop component; and obtaining the battery cell SOC value according to the battery cell open circuit voltage and the OCV-SOC characteristic curve.

[0010] In one embodiment of the present application, obtaining the battery cell consistency parameter according to the battery cell capacity includes: calculating the battery cell capacity standard deviation, the battery cell capacity extreme difference and the battery cell capacity center difference according to all the battery cell capacities of the retained sampling points as the battery cell consistency parameter.

[0011] In one embodiment of the present application, the vehicle end with abnormal cell consistency is determined as an abnormal vehicle end according to the cell consistency parameter, including: determining that the vehicle end corresponding to the cell capacity standard deviation greater than the fourth threshold is the abnormal vehicle end with poor cell capacity consistency; determining that the vehicle end corresponding to the cell capacity extreme difference greater than the fifth threshold is the abnormal vehicle end with excessive cell capacity extreme difference; determining that the vehicle end corresponding to the cell center difference greater than the sixth threshold is the abnormal vehicle end with part of the cell capacity outliers.

[0012] A second aspect of the present application provides a battery pack data sampling method, which is applied to a vehicle side, wherein the vehicle side includes multiple battery packs, and the vehicle side is communicatively connected to the cloud. The battery pack data sampling method includes: real-time sampling of voltage data and current data of the battery pack to obtain data sampling points; determining data sampling points that meet preset conditions as valid sampling points, and transmitting the valid sampling points and corresponding timestamps to the cloud.

[0013] A third aspect of the present application provides a method for determining an abnormal vehicle end, which is applied to a cloud, and the cloud is communicatively connected to a plurality of the vehicle ends; the method for determining an abnormal vehicle end comprises: receiving valid sampling points and corresponding timestamps transmitted by the vehicle end; calculating the battery pack SOC value corresponding to the valid sampling point; selecting valid sampling points within a preset time window according to the timestamp, the battery pack SOC value and a preset extreme value to obtain a valid sampling point set, wherein the battery pack SOC value extreme value of the valid sampling point set is greater than the preset extreme value; calculating the battery cell consistency parameters of the battery pack according to the valid sampling point set; and determining the vehicle end with abnormal battery cell consistency as an abnormal vehicle end according to the battery cell consistency parameters.

[0014] When the vehicle side of the present application obtains the data sampling point at the current moment, it will determine whether the data sampling point meets the preset conditions, and transmit the data sampling point that meets the preset conditions as a valid sampling point with an associated timestamp to the cloud, and remove the data sampling point that does not meet the preset conditions, thereby improving the accuracy of the cloud-side management calculation based on the sampling point, saving the network traffic for the vehicle-side data transmission, and saving the cost of cloud-side data storage. In the cloud, a valid sampling point set with a larger extreme value of the battery pack SOC value is further constructed through a preset time window to calculate the cell capacity, thereby improving the credibility of the calculated cell capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1It is a schematic block diagram of a car-cloud system provided in an embodiment of the present application.

[0016] Figure 2 It is a flow chart of a battery pack data sampling method provided in an embodiment of the present application.

[0017] Figure 3 It is a flow chart of an abnormal vehicle-side determination method provided in an embodiment of the present application.

[0018] Figure 4 It is a flowchart of a method for determining effective sampling points provided in an embodiment of the present application.

[0019] Figure 5 It is a flow chart of a method for calculating consistency parameters of a battery cell provided in an embodiment of the present application.

[0020] Figure 6 It is a flow chart of a method for calculating battery cell capacity provided in an embodiment of the present application.

[0021] Figure 7 It is a flow chart of a method for calculating the SOC value of a battery cell provided in an embodiment of the present application.

[0022] Figure 8 It is a flowchart of determining abnormal vehicle end by cell consistency parameters provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] It should be noted that in the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: the existence of A alone, the existence of A and B at the same time, and the existence of B alone, where A and B can be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and drawings of this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0024] It should also be noted that the method disclosed in the embodiments of the present application or the method shown in the flowchart includes one or more steps for implementing the method. Without departing from the scope of the claims, the execution order of multiple steps can be interchangeable with each other, and some of the steps can also be deleted.

[0025] In the existing vehicle-to-cloud system, the current data of the charging stage is generally transmitted in real time from the vehicle to the cloud. The cloud receives the current data and stores it in a database, and uses the current data and the corresponding time to integrate and calculate the change in the battery cell capacity on the vehicle side, so as to judge the consistency of each battery cell based on the change in battery cell capacity.

[0026] However, because the existing technology only selects the current data during the charging phase, the credibility of the obtained battery cell capacity change is low, which affects the accuracy of the vehicle-side battery cell consistency judgment. In addition, real-time transmission of current data requires large network traffic costs and cloud data storage costs.

[0027] The present application provides a vehicle-to-cloud system, a battery pack data sampling method, and an abnormal vehicle-side determination method, which are used to improve the accuracy of battery cell consistency judgment and reduce the network traffic cost of the vehicle-to-cloud system and the data storage cost of the cloud.

[0028] Please refer to Figure 1 , Figure 1 A schematic block diagram of a vehicle-cloud system provided in an embodiment of the present application, wherein the vehicle-cloud system 100 includes a vehicle end 110 and a cloud end 120, the vehicle end 110 includes multiple battery packs 111, and the cloud end 120 is communicatively connected with multiple vehicle ends 110. In the embodiment of the present application, the vehicle end 110 includes a pure electric vehicle, a hybrid electric vehicle, and other vehicles equipped with power batteries.

[0029] In some embodiments, the cloud 120 may be communicatively connected with multiple vehicle terminals 110 , and the vehicle-cloud system 100 may include multiple cloud terminals 120 .

[0030] Next, combine Figure 1 A battery pack data sampling method provided in an embodiment of the present application is introduced, wherein the method is applied to and executed by the vehicle side. Figure 2 , specifically including the following steps: Step S21: sampling the voltage data and current data of the battery pack in real time to obtain data sampling points.

[0031] In an embodiment of the present application, the vehicle end includes a main controller, which is used to connect to the battery management unit of each battery pack in the vehicle end. When the battery pack on the vehicle end is working, the main controller can sample the voltage and current of the battery pack in real time through the battery management unit, and obtain voltage data and current data as data sampling points of the battery pack.

[0032] Step S22: Determine the data sampling points that meet the preset conditions as valid sampling points, and transmit the valid sampling points and corresponding timestamps to the cloud in an associated manner.

[0033] In an embodiment of the present application, after obtaining the data sampling point at the current moment, the main controller will determine whether the data sampling point meets the preset conditions, and transmit the data sampling point that meets the preset conditions as a valid sampling point with an associated timestamp to the cloud, and eliminate the data sampling points that do not meet the preset conditions, thereby improving the accuracy of the cloud-side management calculations based on the sampling points, saving network traffic for transmitting data on the vehicle side, and saving the cost of storing data on the cloud.

[0034] Next, combine Figure 1 The present invention provides an abnormal vehicle-side determination method, wherein the method is applied to and executed by the cloud. Figure 3 , specifically including the following steps: Step S31: receiving valid sampling points and corresponding timestamps transmitted by the vehicle end.

[0035] In the embodiment of the present application, the cloud includes various computer devices, such as a server. The cloud is connected to multiple vehicle terminals for communication, and receives valid sampling points and timestamps transmitted by the vehicle terminals in real time. When the cloud is connected to multiple vehicle terminals for communication, after receiving valid sampling points and timestamps transmitted by a certain vehicle terminal, the information corresponding to the vehicle terminal can be associated and stored with the valid sampling points and timestamps.

[0036] Step S32: Calculate the battery pack SOC value corresponding to the effective sampling point.

[0037] In the embodiment of the present application, after receiving the valid sampling point, the cloud can also calculate the battery pack SOC value corresponding to the valid sampling point based on the voltage data and current data in the valid sampling point.

[0038] Step S33: According to the timestamp, the battery pack SOC value and the preset extreme value, select the valid sampling points within the preset time window to obtain a valid sampling point set, and the battery pack SOC value extreme value of the valid sampling point set is greater than the preset extreme value.

[0039] In an embodiment of the present application, after the cloud obtains the battery pack SOC values ​​of all valid sampling points corresponding to the vehicle side through calculation, it can select valid sampling points that are more suitable for battery cell consistency judgment based on the battery pack SOC values, and eliminate valid sampling points that are not suitable for battery cell consistency judgment to form a valid sampling point set.

[0040] Among them, the cloud can first select all battery pack SOC values ​​within the preset time window range of the latest time, calculate the battery pack SOC value extreme value, that is, calculate the difference between the maximum SOC value and the minimum SOC value within the preset time window range, and judge whether the current battery pack SOC value extreme value is greater than the preset extreme value. If the current battery pack SOC value extreme value is not greater than the preset extreme value, then move the preset time window to select a new battery pack SOC value to calculate the battery pack SOC value extreme value and size judgment until the above-mentioned valid sampling point set is obtained.

[0041] In some embodiments, when moving the preset time window, the window length may be moved forward by a preset multiple according to time, or moved backward by a preset multiple of the window length, for example, by half the window length, which is not limited here.

[0042] If the battery pack SOC value extreme value is still not greater than the preset extreme value when the preset time window moves to the upper limit, the subsequent steps can be stopped. It can be understood that if the battery pack SOC value extreme value is too small, the reliability of the battery cell capacity calculated in the subsequent steps will be low.

[0043] The present application can improve the credibility of the calculated cell capacity by obtaining a valid sampling point set where the battery pack SOC value extreme value is greater than a preset extreme value.

[0044] Step S34: Calculate and obtain the cell consistency parameters of the battery pack according to the valid sampling point set.

[0045] In an embodiment of the present application, after obtaining the valid sampling point set corresponding to the vehicle side, the cloud side can calculate the cell capacity of each cell in the battery pack according to the valid sampling point set, and then obtain the cell consistency parameters of the battery pack according to the capacity of each cell.

[0046] Step S35: determining the vehicle end with abnormal battery cell consistency as an abnormal vehicle end according to the battery cell consistency parameter.

[0047] In an embodiment of the present application, after the cloud determines the abnormal vehicle end according to the battery cell consistency parameters, it can also notify the abnormal vehicle end, or notify the after-sales personnel of the vehicle end, so as to avoid serious failure of the vehicle end due to inconsistent battery cell capacity.

[0048] In some embodiments, please refer to Figure 4 The above step S22 may further include the following steps: Step S41: Calculate the net power of the battery pack, the pure ohmic voltage drop, and the polarization voltage drop components at the data sampling point according to the voltage data and the current data.

[0049] In the embodiment of the present application, the voltage data includes the battery pack voltage value , Cell voltage , cell voltage balance ,in, Indicates the cell number. Current data includes the battery pack current value Among them, the net power of the battery pack is The pure ohmic voltage drop is expressed as Taking a battery pack consisting of two cells as an example, the polarization voltage drop component of the first cell is expressed as The polarization voltage drop component of the second cell is expressed as The polarization voltage drop is expressed as express: ; Among them, the net power of the battery pack is The formula is as follows: ; In the formula, is the net power of the battery pack at the current sampling moment, is the net power of the battery pack at the last sampling moment, is the battery pack current value sampled this time, is the time interval between this sampling moment and the previous sampling moment.

[0050] Pure ohmic voltage drop The formula is as follows: ; In the formula, represents the pure ohmic voltage drop at the current sampling moment, Indicates the pure ohmic internal resistance of the battery pack. It is the battery pack current value sampled this time.

[0051] The above polarization voltage drop component is and polarization voltage drop component The formula is as follows: ; ; In the formula, is the polarization voltage drop component of the first cell at the current sampling moment, is the polarization voltage drop component of the first cell at the previous sampling moment, is an exponential function with the natural constant e as base. and are the resistance and capacitance values ​​in the equivalent circuit model of the first cell, It is the battery pack current value sampled this time. is the polarization voltage drop component of the second cell at the current sampling moment, is the polarization voltage drop component of the second cell at the previous sampling moment, and are the resistance and capacitance of the equivalent circuit model of the second battery cell respectively.

[0052] Step S42: When it is determined that the change in the net power of the battery pack is greater than a preset change, the pure ohmic voltage drop is less than a first threshold, and the polarization voltage drop component is less than a second threshold, the corresponding data sampling point is determined to be a valid sampling point.

[0053] In the embodiment of the present application, the change in the net charge of the battery pack is the change in the net charge of the battery pack relative to the net charge of the battery pack at the last valid sampling point. Among them, the valid sampling points transmitted to the cloud include the timestamp of the current sampling moment, the battery pack voltage, the battery pack current, the net charge of the battery pack, the pure ohmic voltage drop, each polarization voltage drop component, each cell voltage and the cumulative balanced charge of each cell. Among them, the cumulative balanced charge of the cell is the cumulative charge released when the cell is balanced. When the battery management unit finds that the voltage consistency of each cell in the battery pack is poor, it can control the cell with a higher voltage to discharge and balance.

[0054] In some embodiments, the effective sampling points include the cell voltage, the cell accumulated balanced power, the battery pack net power, the pure ohmic voltage drop and the polarization voltage drop component, please refer to Figure 5 The above step S34 may further include the following steps: Step S51: Screen and remove valid sampling points in the valid sampling point set that are within a preset SOC value range.

[0055] In the embodiment of the present application, the battery pack SOC value corresponding to each valid sampling point in the valid sampling point set can be defined as , define the effective sampling point concentration The maximum value of , The minimum value of ,according to Define a high SOC threshold, such as , and according to Define a low SOC threshold, such as The preset SOC value range may be from a low SOC threshold to a high SOC threshold, thereby reducing the amount of computing in the cloud.

[0056] Furthermore, the cloud can also define higher The valid sampling point corresponding to the battery pack SOC value is the high SOC data point, and the definition is below The effective sampling point corresponding to the battery pack SOC value is the low SOC data point, and the high SOC data point and the adjacent low SOC data point in the effective sampling point set are combined into a data group for subsequent calculations.

[0057] Step S52: Calculate the maximum difference value of the battery cell SOC of each valid sampling point set according to the battery cell voltage.

[0058] In the embodiment of the present application, in order to further reduce the amount of computing in the cloud and save computing resources in the cloud, the cloud can also calculate the maximum difference value of the battery cell SOC of each valid sampling point set based on the battery cell voltage in the valid sampling points. It can be understood that a battery pack with a smaller maximum difference value of the battery cell SOC has no risk of inconsistent battery cell capacity.

[0059] The calculation method of the maximum difference value of the cell SOC includes: defining the maximum cell voltage of the valid sampling point set as , the minimum cell voltage is The number of cells in a battery pack is defined as , Maximum OCV voltage of the battery cell , minimum OCV voltage of the battery cell . To retain the sampling point concentration The pure ohmic voltage drop at the effective sampling point is To retain the sampling point concentration The first polarization voltage drop component of the effective sampling point, To retain the sampling point concentration The second polarization voltage drop component of the effective sampling point.

[0060] The OCV-SOC mapping curve of the battery cell is calculated using a function Indicates that the cell SOC value is defined as , , then the maximum difference value of SOC of each cell in the valid sampling point set is It can be calculated by the following formula: .

[0061] Step S53: Screen and eliminate the valid sampling point set whose maximum cell SOC difference value is less than the third threshold value to obtain a reserved sampling point set.

[0062] In an embodiment of the present application, after calculating the maximum difference value of the battery cell SOC corresponding to each valid sampling point set, the cloud can eliminate the valid sampling point set whose maximum difference value of the battery cell SOC is less than the third threshold, that is, eliminate the valid sampling point set with no risk of inconsistent battery cell capacity of the battery pack, and retain the valid sampling point set with the risk of inconsistent battery cell capacity as the above-mentioned retained sampling point set, thereby reducing the amount of calculation when the cloud executes subsequent steps.

[0063] Step S54: Calculate the cell capacity of each cell in the retained sampling point set according to the accumulated balanced power of the cell, the net power of the battery pack, the pure ohmic voltage drop and the polarization voltage drop components.

[0064] Step S55: Obtain cell consistency parameters according to the cell capacity.

[0065] In an embodiment of the present application, the cloud can extract the accumulated balanced power of the battery cells, the net power of the battery pack, the pure ohmic voltage drop, and the polarization voltage drop components in the retained sampling point set to calculate the cell capacity of each battery cell in the retained sampling point set.

[0066] In some embodiments, please refer to Figure 6 The above step S54 may further include the following steps: Step S61: Calculate the cell SOC value corresponding to the retained sampling point set according to the pure ohmic voltage drop and the polarization voltage drop components.

[0067] Step S62: Calculate the cell power change value corresponding to the retained sampling point set according to the cell SOC value, the cell accumulated balanced power and the battery pack net power.

[0068] In the embodiment of the present application, the net power of the whole packet of the high SOC data point of the kth data group in the above step S51 is defined as , define the accumulated balanced charge of the ith cell at the high SOC data point of the kth data group as , the net power of the whole package of the low SOC data point of the kth data group is defined as , define the cell cumulative balanced power of the low SOC data point of the kth data group as . Then the change value of the battery capacity of the ith battery cell in the k data group is It can be calculated by the following formula: ; It can be understood that this solution takes the change in the amount of electricity generated by cell balancing into account in the change in cell capacity, which can further improve the credibility of the judgment of the consistency of the cell capacity.

[0069] Step S63: Calculate the cell capacity of each cell in the reserved sampling point set according to the cell power change value and the cell SOC value.

[0070] In the embodiment of the present application, the SOC value of the i-th battery cell at the high SOC data point of the k-th data group is defined as , define the SOC value of the i-th battery cell at the low SOC data point of the k-th data group as , define the SOC change value of the i-th battery cell in the k-th data group as , the center value of the normal distribution is Expressed as variance express, Calculated by the following formula: ; definition The probability distribution form is ,in, - , . for The center value of the normal distribution, for The center value of the normal distribution, for The variance of the normal distribution of for The variance of the normal distribution.

[0071] Define the i-th cell capacity of the k-th data group as ,but It can be calculated by the following formula: ; Define the reserved sampling point set The SOC value of the i-th cell at the valid sampling point is , The probability distribution of is shown as follows: ,in, , . for The center value of the normal distribution, for The variance of the normal distribution.

[0072] Furthermore, assuming that the total number of the above data sets is Q, the final capacity of the i-th battery cell is , The cell capacity calculated from each data group is weighted. The calculation formula is as follows: ; It can be understood that the smaller the variance of the cell capacity calculated by the data group, the higher the credibility of the obtained cell capacity value, and the more reliable the final capacity is. The higher the weight in the calculation, the more accurate the final capacity of the battery cell can be obtained.

[0073] In some embodiments, please refer to Figure 7 The above step S61 may further include the following steps: Step S71: Calculate the cell open circuit voltage of each cell in the retained sampling point set according to the pure ohmic voltage drop and the polarization voltage drop component.

[0074] In the embodiment of the present application, the first The voltage of the ith cell at a valid sampling point is , the pure ohmic voltage drop and polarization voltage drop components are , , , the open circuit voltage of the i-th cell is Since the above voltages actually have certain errors, the probability distribution form can more accurately describe the voltages. Assume that, , , , , All of them conform to the normal distribution, and the central value of the normal distribution is Expressed as variance If it is expressed, then: ; ; ; ; ; In the formula, is the voltage of the i-th battery cell transmitted from the vehicle to the cloud, It is the pure ohmic voltage drop transmitted from the vehicle to the cloud. is the polarization voltage drop component 1 transmitted from the vehicle to the cloud. is the polarization voltage drop component 2 transmitted from the vehicle to the cloud. The value is determined by the accuracy of the battery voltage detection sensor. It can be calculated by the following formula: ; In the formula, yes hour The basic variance of The variance is The coefficient increases as the absolute value of increases. Similarly, , They can be calculated by the following formulas respectively.

[0075] ; ; In the formula, yes hour The basic variance of yes hour The basic variance of . It is roughly assumed that the pure ohmic voltage drop and polarization voltage of each cell can be approximately equal to the voltage of the entire pack. Therefore, the pure ohmic voltage drop and polarization voltage drop components of each cell are , , ,but: ; ; ; The number of cells in the battery pack is indicated by letters. Said that The open circuit voltage of each cell at the effective sampling point is Indicates that Indicates the cell number. It can also be expressed by normal distribution: ; The open circuit voltage of the i-th cell It can be calculated using the following formula: ; The central value of Calculated by the following formula: ; in, yes The variance of The calculation formula is shown below: .

[0076] Step S72: Obtain the SOC value of the battery cell according to the open circuit voltage of the battery cell and the OCV-SOC characteristic curve.

[0077] In the embodiment of the present application, after obtaining the open circuit voltage of the battery at the effective sampling point, the SOC value of each battery cell can be obtained by transforming the battery OCV-SOC characteristic curve. The mapping relationship between OCV and SOC is expressed by the function Represents. Define the reserved sampling point set The SOC value of the i-th cell at the valid sampling point is , , it is approximately believed that It still conforms to the normal distribution, and we can get The probability distribution of is shown as follows: ; in, , , yes The derivative of .

[0078] It can be understood that after calculating the cell capacity of each cell in the battery pack, the cell consistency parameters are obtained based on the cell capacity, which can specifically include: calculating the cell capacity standard deviation, cell capacity extreme difference and cell capacity center difference as the cell consistency parameters based on all cell capacities of the retained sampling points.

[0079] Please refer to Figure 8 The above step S35 may specifically include the following steps: Step S81: Determine that the vehicle end corresponding to the cell capacity standard deviation being greater than the fourth threshold is an abnormal vehicle end with poor cell capacity consistency.

[0080] Step S82: Determine that the vehicle end corresponding to the cell capacity extreme difference being greater than the fifth threshold is an abnormal vehicle end with excessive cell capacity extreme difference.

[0081] Step S83: Determine that the vehicle end corresponding to the cell center difference being greater than the sixth threshold is an abnormal vehicle end with outliers in part of the cell capacity.

[0082] In the embodiment of the present application, the standard deviation of the cell capacity of the reserved sampling points is defined as The average capacity of all cells retaining the sampling points is , the range of the cell capacity at the retained sampling point is , the difference between the average and minimum values ​​of the cell capacity is the center difference of the cell capacity, express, and The ratio is the maximum outlier degree of the monomer capacity, If it means: ; ; ; ; .

[0083] An embodiment of the present application also provides a computer storage medium, which stores a computer program. When the computer program is executed by a processor, the processor executes the above-mentioned battery pack data sampling method or abnormal vehicle-side determination method.

[0084] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer storage medium or transmitted through the computer storage medium. The computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0085] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes. In the absence of conflict, the technical features in this embodiment and the implementation scheme can be combined arbitrarily.

[0086] The embodiments described above are merely preferred embodiments of the present application and are not intended to limit the scope of the present application. Without departing from the design spirit of the present application, various modifications and improvements made to the technical solutions of the present application by ordinary technicians in this field should fall within the protection scope determined by the claims of the present application.

Claims

1. A car-to-cloud system, characterized in that: It includes a vehicle end and a cloud end, wherein the vehicle end includes a plurality of battery packs, and the cloud end is communicatively connected with a plurality of the vehicle ends; The vehicle end is used for: Sampling the voltage data and current data of the battery pack in real time to obtain data sampling points; Determine data sampling points that meet preset conditions as valid sampling points, and transmit the valid sampling points and corresponding timestamps to the cloud in an associated manner; The cloud is used for: Calculate the battery pack SOC value corresponding to the effective sampling point; According to the timestamp, the battery pack SOC value and the preset extreme value, selecting valid sampling points within a preset time window to obtain a valid sampling point set, wherein the battery pack SOC value extreme value of the valid sampling point set is greater than the preset extreme value; Obtaining cell consistency parameters of the battery pack by calculation according to the valid sampling point set; The vehicle end with abnormal battery cell consistency is determined as an abnormal vehicle end according to the battery cell consistency parameter.

2. The vehicle-to-cloud system according to claim 1, characterized in that: The step of determining the data sampling points that meet the preset conditions as valid sampling points, and associating and transmitting the valid sampling points and corresponding timestamps to the cloud includes: Calculate the net power of the battery pack, the pure ohmic voltage drop, and the polarization voltage drop component at the data sampling point according to the voltage data and the current data; When it is determined that the change in the net power of the battery pack is greater than a preset change, when it is determined that the pure ohmic voltage drop is less than a first threshold, and when it is determined that the polarization voltage drop component is less than a second threshold, the corresponding data sampling point is determined to be the valid sampling point; The change in the net power of the battery pack is the change in the net power of the battery pack relative to the net power of the battery pack at the last valid sampling point.

3. The vehicle-to-cloud system according to claim 1, characterized in that: The effective sampling points include cell voltage, cell accumulated balanced power, battery pack net power, pure ohmic voltage drop and polarization voltage drop components; The step of calculating and obtaining the cell consistency parameter of the battery pack according to the valid sampling point set includes: Calculate the maximum difference value of the battery cell SOC of each of the valid sampling point sets according to the battery cell voltage; Screening and eliminating the valid sampling point set whose maximum cell SOC difference value is less than a third threshold value to obtain a retained sampling point set; Calculate the cell capacity of each cell in the reserved sampling point set according to the accumulated balanced power of the cell, the net power of the battery pack, the pure ohmic voltage drop and the polarization voltage drop component; The battery cell consistency parameter is obtained according to the battery cell capacity.

4. The vehicle-to-cloud system according to claim 3, characterized in that: The step of calculating and obtaining the cell consistency parameter of the battery pack according to the valid sampling point set further includes: The valid sampling points in the valid sampling point set that are within a preset SOC value range are screened and eliminated.

5. The vehicle-to-cloud system according to claim 3, characterized in that: The calculating the cell capacity of each cell in the reserved sampling point set includes: Calculating the cell SOC value corresponding to the reserved sampling point set according to the pure ohmic voltage drop and the polarization voltage drop component; Calculate the cell power change value corresponding to the reserved sampling point set according to the cell SOC value, the cell accumulated balanced power and the battery pack net power; The cell capacity of each cell in the reserved sampling point set is calculated according to the cell power change value and the cell SOC value.

6. The vehicle-to-cloud system according to claim 5, characterized in that: The calculating the cell SOC value corresponding to the reserved sampling point set includes: Calculating the cell open circuit voltage of each cell in the retained sampling point set according to the pure ohmic voltage drop and the polarization voltage drop component; The SOC value of the battery cell is obtained according to the open circuit voltage of the battery cell and the OCV-SOC characteristic curve.

7. The vehicle-to-cloud system according to claim 3, characterized in that: The obtaining the cell consistency parameter according to the cell capacity includes: According to the capacities of all the cells at the reserved sampling points, the standard deviation of the cell capacity, the extreme difference of the cell capacity and the center difference of the cell capacity are calculated as the cell consistency parameters.

8. The vehicle-to-cloud system according to claim 7, characterized in that: The determining, according to the battery cell consistency parameter, that the vehicle end with abnormal battery cell consistency is an abnormal vehicle end includes: Determine that the vehicle end corresponding to the battery cell capacity standard deviation being greater than a fourth threshold is the abnormal vehicle end with poor battery cell capacity consistency; Determine that the vehicle end corresponding to the battery cell capacity extreme difference being greater than the fifth threshold is the abnormal vehicle end with excessive battery cell capacity extreme difference; It is determined that the vehicle end corresponding to the cell center difference being greater than a sixth threshold is the abnormal vehicle end in which the capacity of some cells is outliers.

9. A battery pack data sampling method, characterized in that: Applied to a vehicle side, the vehicle side includes a plurality of battery packs, and the vehicle side is connected to the cloud for communication; The battery pack data sampling method comprises: Sampling the voltage data and current data of the battery pack in real time to obtain data sampling points; The data sampling points that meet the preset conditions are determined to be valid sampling points, and the valid sampling points and corresponding timestamps are associated and transmitted to the cloud.

10. A method for determining an abnormal vehicle end, characterized in that: Applied to the cloud, the cloud is communicatively connected with the plurality of vehicle terminals; The abnormal vehicle-side determination method comprises: Receive the valid sampling points and corresponding timestamps transmitted by the vehicle end; Calculate the battery pack SOC value corresponding to the effective sampling point; According to the timestamp, the battery pack SOC value and the preset extreme value, selecting valid sampling points within a preset time window to obtain a valid sampling point set, wherein the battery pack SOC value extreme value of the valid sampling point set is greater than the preset extreme value; Obtaining cell consistency parameters of the battery pack by calculation according to the valid sampling point set; The vehicle end with abnormal battery cell consistency is determined as an abnormal vehicle end according to the battery cell consistency parameter.

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