A method and platform for detecting consistency of power batteries

Abstract

The application relates to a power battery consistency detection method and platform, the detection method comprising the following steps: acquiring vehicle battery system data, the vehicle battery system data comprising maximum voltage and minimum voltage, and battery system SOC, and obtaining a voltage difference value based on the maximum voltage and the minimum voltage; judging whether the data is in a charging and discharging platform period according to the SOC, and screening the vehicle battery system data in the charging and discharging platform period; calculating the cumulative proportion of the voltage difference value greater than a set pressure difference after screening and processing, and calculating a Delta SOC based on the relationship between the cumulative proportion and the Delta SOC; judging whether the Delta SOC is greater than a warning critical value, and if the Delta SOC is greater than or equal to the warning critical value, the battery consistency is poor. The detection method can solve the problem that in the prior art, the SOC deviation amount is difficult to calculate in the dynamic operation process of the battery system, thereby leading to the misjudgment of the battery consistency.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of vehicle batteries, and particularly relates to a power battery consistency detection method and platform. BACKGROUND

[0002] Currently, new energy vehicle manufacturers use the vehicle wireless data module to transmit vehicle information and battery information to the vehicle manufacturer monitoring platform after selling the vehicle. The monitoring platform identifies abnormal power battery conditions by analyzing and calculating the data. The battery system consistency warning is a key warning event. At present, for the lithium iron phosphate power battery system, the monitoring platform uses the highest and lowest voltage and current information reported by the vehicle. Generally, the OCV-SOC table is checked according to the highest and lowest voltage in the battery system after storage (usually 1-2 hours or more), the corresponding SOC of the highest and lowest voltage and the difference (denoted as ΔSOC) are calculated, and the vehicle information (vehicle identification number, single body position) of ΔSOC>ΔSOC critical value is reported, and the maintenance personnel are maintained synchronously.

[0003] By analyzing the discharge curve characteristics of the lithium iron phosphate battery (the discharge curve changes fast at both ends, and changes slowly in the middle, but there is a corner F in the slowly changing area), the discharge interval is divided into four intervals A, B, C and D (as shown in Figure 1 ). Among them, when the battery is in interval A or interval D, the voltage in this interval changes rapidly, and if the battery is in these two intervals, the system is more likely to produce a pressure difference, but the consistency may be normal (that is, the slight difference in SOC between different single bodies will amplify the single body pressure difference of the battery system, which may reach hundreds of millivolts), which is easy to cause misjudgment; interval B and interval C are voltage platform intervals. For single bodies in interval B or interval C, the voltage in this interval changes slowly and the SOC changes rapidly. When the difference in SOC between different single bodies is large, the voltage difference between the corresponding single bodies may be small, which is easy to cause errors in judgment, and interval D is the end of battery discharge, the cumulative proportion of high voltage difference will be larger, which is also easy to cause errors.

[0004] Most of the existing vehicles SOC use range is 20%-100% during operation, even higher range, and the SOC is above SOC1 plateau, the voltage difference of the lithium iron phosphate battery is small. Due to the characteristics of lithium iron phosphate battery, the single cell voltage is relatively flat in the charging and discharging platform period range (SOC1-SOC2), if the highest voltage and the lowest voltage after standby are used to obtain SOC by searching OCV-SOC table, there will be a large error problem, the battery system cannot accurately obtain △SOC value in this interval, and the battery consistency cannot be accurately warned. A small part of the vehicles will operate to 20% and below, and the vehicles operating below 20% and standing for more than 1-2h are even less, at this time, the battery system cannot accurately obtain the accurate △SOC value by searching the OCV-SOC table, and the vehicle consistency cannot be accurately warned, thereby causing the monitoring platform to miss the early warning of the large consistency of the vehicle. SUMMARY

[0005] The application provides a power battery consistency detection method and platform, which is used to solve the problem that the state of charge deviation is difficult to calculate in the battery dynamic operation process in the prior art, thereby causing the battery consistency to be misjudged.

[0006] To solve the above technical problems, the application provides a power battery consistency detection method, which comprises:

[0007] 1) Obtain vehicle battery system data, the vehicle battery system data comprising the highest voltage and the lowest voltage, and the battery system SOC, and obtain the voltage difference based on the highest voltage and the lowest voltage;

[0008] 2) Determine whether it is charging and discharging platform period data according to the SOC, and screen the vehicle battery system data in the charging and discharging platform period;

[0009] 3) After screening and processing, calculate the cumulative proportion of the voltage difference greater than the set pressure difference, and obtain the △SOC based on the relationship between the cumulative proportion and the △SOC;

[0010] 4) Determine whether the △SOC is greater than the early warning critical value, if greater than or equal to the early warning critical value, the battery consistency is poor.

[0011] The beneficial effects of the above technical solution are: the cumulative proportion greater than the set pressure difference is obtained by using the voltage difference of the obtained highest voltage and the lowest voltage of the battery system, and the △SOC is obtained based on the cumulative proportion. In this case, the problem that the highest voltage and the lowest voltage corresponding to the SOC cannot be accurately obtained by using the table lookup method when the obtained vehicle battery system data is in the charging and discharging platform period with small voltage change, and the calculated △SOC is inaccurate, is avoided, the misjudgment probability of the battery consistency is reduced, and the accuracy of the battery consistency judgment is improved.

[0012] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection method, further comprising that in step 3), the cumulative proportion and the SOC are in a linear relationship.

[0013] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection method, further comprising that the linear relationship determination method comprises: obtaining vehicle battery system data of a plurality of vehicles, obtaining a voltage difference value based on the highest voltage and the lowest voltage, and obtaining a SOC based on the highest voltage and the lowest voltage; the voltage difference value is statistically grouped, and the cumulative proportion of the voltage difference value in different groups is calculated; the SOC and the cumulative proportion in different groups are fitted to obtain a linear relationship formula of different groups, and a group with the highest linear correlation is determined from the linear relationship formula of each group, and the voltage difference value corresponding to the group is taken as a set voltage difference, and the linear relationship formula of the group is taken as a final linear relationship formula.

[0014] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection method, further comprising a cleaning process, and the cleaning process comprises cleaning vehicle battery system data obtained at a set temperature.

[0015] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection method, further comprising that in step 1), the obtained vehicle battery system data is operation data.

[0016] The application further provides a power battery consistency detection platform, comprising an acquisition module and a processing module; the acquisition module is used for acquiring vehicle battery system data, and the vehicle battery system data comprises a highest voltage, a lowest voltage and a battery system SOC; the processing module obtains a voltage difference value based on the obtained highest voltage and the lowest voltage, judges whether the data is in a charging and discharging platform period according to the SOC, and screens vehicle battery system data in the charging and discharging platform period; after the screening process, the cumulative proportion of the voltage difference value greater than a set voltage difference is calculated, and a SOC is calculated based on the relationship between the cumulative proportion and the SOC; it is judged whether the SOC is greater than a warning critical value, if greater than or equal to the warning critical value, the battery consistency is poor.

[0017] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection platform, further comprising that in the processing module, the cumulative proportion and the SOC are in a linear relationship.

[0018] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection platform, which further comprises a processing module, and the determination method of the linear relationship comprises: obtaining vehicle battery system data of a plurality of vehicles, obtaining a voltage difference value based on the highest voltage and the lowest voltage, and obtaining a SOC based on the highest voltage and the lowest voltage; grouping the voltage difference values, calculating the cumulative proportion of the voltage difference values in different groups; fitting the SOC and the cumulative proportion in different groups to obtain a linear relationship formula of different groups, determining a group with the highest linear correlation from the linear relationship formulas of the groups, taking the voltage difference value of the group as a set voltage difference, and taking the linear relationship formula of the group as a final linear relationship formula.

[0019] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection platform, which further comprises a processing module, and the determination method of the linear relationship comprises: obtaining vehicle battery system data of a plurality of vehicles, obtaining a voltage difference value based on the highest voltage and the lowest voltage, and obtaining a SOC based on the highest voltage and the lowest voltage; grouping the voltage difference values, calculating the cumulative proportion of the voltage difference values in different groups; fitting the SOC and the cumulative proportion in different groups to obtain a linear relationship formula of different groups, determining a group with the highest linear correlation from the linear relationship formulas of the groups, taking the voltage difference value of the group as a set voltage difference, and taking the linear relationship formula of the group as a final linear relationship formula.

[0020] Further, in order to better improve the accuracy of battery consistency judgment, the application provides a power battery consistency detection platform, which further comprises a processing module, and the determination method of the linear relationship comprises: obtaining vehicle battery system data of a plurality of vehicles, obtaining a voltage difference value based on the highest voltage and the lowest voltage, and obtaining a SOC based on the highest voltage and the lowest voltage; grouping the voltage difference values, calculating the cumulative proportion of the voltage difference values in different groups; fitting the SOC and the cumulative proportion in different groups to obtain a linear relationship formula of different groups, determining a group with the highest linear correlation from the linear relationship formulas of the groups, taking the voltage difference value of the group as a set voltage difference, and taking the linear relationship formula of the group as a final linear relationship formula. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 is a discharge curve when the battery is in a discharging process;

[0022] Figure 2 is a linear relationship diagram of the SOC and P1 in a partial interval SOC segment of the application;

[0023] Figure 3 is a flowchart of the power battery consistency detection method of the application;

[0024] Figure 4 is a discharge curve diagram of a certain vehicle on a certain day in the nth week;

[0025] Figure 5 is a discharge curve diagram of a certain vehicle on a certain day in the n+1th week;

[0026] Figure 6 is a discharge curve diagram of a certain vehicle on a certain day in the n+2th week;

[0027] Figure 7 is a comparison curve diagram of voltage difference statistics grouping of a certain vehicle for three consecutive weeks;

[0028] Figure 8 is a change diagram of the SOC of a certain vehicle for three consecutive weeks. DETAILED DESCRIPTION

[0029] The basic idea of the present application is that the cumulative proportion greater than the set pressure difference is obtained by using the voltage difference of the obtained maximum voltage and minimum voltage of the battery system, the SOC is obtained based on the cumulative proportion, in this case, the problem that the highest voltage and the lowest voltage corresponding SOC cannot be accurately obtained by using the table lookup method when the obtained vehicle battery system data is in the charge and discharge platform period with little voltage change, and the calculated SOC is inaccurate is avoided, and the accuracy of the battery consistency judgment is improved.

[0030] In order to make the purpose, technical scheme and technical effect of the present application more clear and obvious, the present application will be further described in detail below in combination with the drawings and specific embodiments.

[0031] Power battery consistency detection method embodiment:

[0032] Figure 1 is the discharge curve when the battery is in the discharging process; Figure 2 is the linear relationship diagram of the SOC in the partial interval SOC segment and P1 of the present application; Figure 3 is the flow chart of the power battery consistency detection method of the present application.

[0033] Step one: obtaining vehicle battery system data, obtaining the voltage difference based on the highest voltage and the lowest voltage of the vehicle battery system data.

[0034] In the running process of the pure electric vehicle or the hybrid electric vehicle, the related data of the battery system is actively uploaded, and the related data mainly includes the highest single battery voltage, the lowest single battery voltage, the average voltage, the temperature and the battery system SOC (battery system state of charge) of the battery system, wherein the highest single battery voltage is referred to as the highest voltage (Vmax). The lowest single battery voltage is referred to as the lowest voltage (Vmin). The battery system SOC includes the SOC corresponding to the highest voltage and the lowest voltage.

[0035] In step one, as shown in Figure 3 , the vehicle battery system data also includes the single position corresponding to the highest voltage and the lowest voltage.

[0036] In step one, as shown in Figure 3 , the voltage difference (△V) is obtained based on the obtained highest voltage and lowest voltage, that is, △V=Vmax-Vmin, and the calculated voltage difference is stored.

[0037] In step one, the obtained vehicle battery system data is the operation data of the battery, which can be dynamic data or SOC interval segment data, and the judgment range is wide.

[0038] In the embodiment, the number of vehicles is multiple, and thus the step one also needs to acquire an identification number for identifying the vehicle identity information. The identification number is, for example, a license plate number. In this way, the subsequent alarm signal can be sent to the corresponding vehicle according to the identification number of the vehicle.

[0039] Step two: screening the vehicle battery system data in the charging and discharging platform period.

[0040] In step two, it is determined whether the acquired SOC is the charging and discharging platform period data, and the vehicle battery system data in the charging and discharging platform period is screened. Specifically, the interval range of the charging and discharging platform period is SOC1-SOC2, wherein SOC1 is the lower limit of the charging and discharging platform period interval, and SOC2 is the upper limit of the charging and discharging platform period interval. It is compared whether the acquired SOC is in SOC1-SOC2, and the SOC in SOC1-SOC2 is screened and retained, and the data whose SOC is higher than SOC2 or lower than SOC1 is cleared.

[0041] In step two, since the data uploaded by the vehicle under low temperature state cannot truly reflect the state of the battery system, the vehicle battery system data acquired under the set temperature (T ℃) needs to be cleared. In this case, the acquired vehicle battery system data can truly reflect the state of the battery system, thereby better improving the accuracy of the battery consistency judgment. For the embodiment, Figure 4 is the discharge curve diagram of a certain vehicle on a certain day in the nth week. The horizontal coordinate is time, and the vertical coordinate is voltage. Based on the discharge curve diagram, it can be seen that the system has a certain deviation at the box position, because at this time the battery system cell (i.e. single body) is in Figure 4 the middle interval A, and the small consistency deviation between the cells will cause a large pressure difference, so the data in the SOC range corresponding to the curve of the box position needs to be cleared. Figure 1

[0042] In step two, as shown in Figure 3 , before screening, it also includes counting the cumulative number of charging and discharging cycles of the vehicle in a week (i.e. the number of times of cumulative discharge consumption SOC or cumulative charging SOC), and determining whether the cumulative number of charging and discharging cycles in a week is greater than or equal to n. If yes, the screening process is performed, and if no, the determination is exited. Wherein n≥2, thereby ensuring that the vehicle is in a running state rather than a long-term idle state after charging and discharging.

[0043] Step three: calculating the cumulative proportion of the voltage difference greater than the set pressure difference after the screening process, and calculating the △SOC based on the relationship between the cumulative proportion and the △SOC.

[0044] Specifically, for example, the pressure difference in a week is counted and grouped, and the cumulative pressure difference proportion P1 when △V>X is calculated. According to the expression of the relationship between the state of charge deviation (△SOC) of the battery system and P1, the battery system △SOC is calculated.​

[0045] Before obtaining the expression of the relationship between △SOC and P1, the relationship between △SOC and P1 is analyzed. Figure 5 is the discharge curve diagram of a certain car on a certain day in the n+1th week; Figure 6 is the discharge curve diagram of a certain car on a certain day in the n+2th week;

[0046] Figure 7 is the comparison curve diagram of the pressure difference statistics grouping of a certain car for three consecutive weeks; Figure 8 is the △SOC change diagram of a certain car for three consecutive weeks. Figure 5 and Figure 6 The horizontal coordinates of and are time, and the vertical coordinates are voltage. Figure 7 The horizontal coordinate of is the voltage difference, and the vertical coordinate is the voltage difference ratio, Figure 8 The horizontal coordinate of is time (unit: week), and the vertical coordinates are all △SOC.

[0047] Based on Figure 5 It can be seen that there is a certain pressure difference in the box position of the system in the figure, and at this time most of the battery system is in interval B, and a small part is in interval C. Based on Figure 6 It can be seen that there is a certain degree of deviation throughout the discharge process. Most of the battery system is in interval A, and a small part is in interval B; most of the battery system is in interval B, and a small part is in interval C; most of the battery system is in interval C, and a small part is in interval D, so there is a certain degree of pressure difference throughout the process. Based on Figure 7 It can be seen that in the n th week, the pressure difference is mostly concentrated within 0-X mV (because the battery is in interval A or interval B or interval C at the same time); in the n+1th week, the pressure difference ratio within 0-X mV decreases, but the ratio in the >X mV interval increases (the battery system has interval difference); in the n+2th week, the pressure difference ratio within 0-X mV is very low, but the ratio in the >X mV interval increases greatly (the battery system has always existed interval difference). Based on Figure 8 It can be seen that in the n th week, the battery system has a low △SOC, which is within the normal range; in the n+1th week, the △SOC increases rapidly and is abnormal; in the n+2th week, the △SOC continues to increase, and the consistency continues to deteriorate.

[0048] Based on Figure 5 and Figure 8It can be seen that interval B and interval C are voltage platform intervals, and the voltage difference between the single bodies is relatively small, but when the SOC of a single body is lower than that of other single bodies, the voltage difference will expand. For example, when most of the single bodies are in interval B, a single body is in interval C within a certain range, at this time the battery system will produce a certain voltage difference; when most of the single bodies are in interval C and a small part of the single bodies are in interval D, the battery system will also produce a certain voltage difference, and the cumulative voltage difference ratio P1 of the battery system at the same time when the voltage difference is greater than the set voltage difference X will increase; according to the relationship between SOC change and voltage difference change, it can be seen that the cumulative ratio P1 and the SOC are in a linear relationship. That is, the relationship expression of the cumulative ratio P1 and the SOC is a linear expression. As shown in Figure 2 , the linear expression satisfies:

[0049] ΔSOC = K*P1 + b

[0050] Wherein, K represents the cumulative ratio coefficient of the voltage difference, b represents the cumulative ratio parameter of the voltage difference, and P1 represents the cumulative voltage difference ratio of the system voltage difference (i.e. the voltage difference) ΔV>X within the SOC1-SOC2 range.

[0051] The determination method of the linear relationship includes: obtaining vehicle battery system data of a plurality of vehicles, obtaining a voltage difference based on the highest voltage and the lowest voltage, and obtaining a ΔSOC based on the SOC corresponding to the highest voltage and the lowest voltage; grouping the voltage difference, calculating the cumulative ratio of the voltage difference in different groups; fitting the ΔSOC and the cumulative ratio in different groups in the charging and discharging platform period interval, obtaining the linear relationship of different groups, determining a group with the highest linear correlation from the linear relationship of each group, taking the voltage difference corresponding to the group as the set voltage difference, and taking the linear relationship of the group as the final linear relationship. For example Figure 2 2 , the linear correlation of the linear relationship is R 2 =0.9926, the linear correlation of the group is the highest, the voltage difference X corresponding to the group is taken as the set voltage difference, and the linear relationship of the group is taken as the final linear relationship of the cumulative ratio P1 and the SOC.

[0052] Step four: determining whether the ΔSOC is greater than a warning critical value, if greater than or equal to the warning critical value, the battery consistency is poor.

[0053] In step four, the warning critical value is represented by M, if the ΔSOC≥M, it is determined that the consistency is abnormal, and a warning is given. If the ΔSOC

[0054] In step four, the vehicle identification number, vehicle location, minimum / abnormal cell position and other related information can also be reported, and the related information is synchronized to the after-sales maintenance personnel, so that timely maintenance processing can be performed before the vehicle breaks down, thereby greatly reducing the degree of customer complaints.

[0055] Based on the power battery consistency detection method of the embodiment, the cumulative proportion of the voltage difference greater than the set pressure difference is obtained by using the obtained highest voltage and lowest voltage of the battery system, and the SOC is obtained based on the cumulative proportion, in which case, the problem that the highest voltage and the lowest voltage corresponding SOC cannot be accurately obtained by using the table lookup method when the obtained vehicle battery system data is in the charging and discharging platform period with little voltage change, and the SOC is not accurate, is avoided, the false judgment probability of the battery consistency is reduced, and the accuracy of the battery consistency judgment is improved. The detection method of the embodiment is applied to the power battery big data monitoring platform, the most commonly used SOC interval of the vehicle is used for statistical judgment, the judgment range is wide, the SOC greater than the warning critical value is taken as the alarm condition, the vehicle with consistency problems can be accurately identified and warned in advance, the present application combines the statistical method and the electrochemical characteristics of the cell, the vehicle identification number, the vehicle location, the minimum cell position and other related information are accurately reported by using the platform difference, and the related information is synchronized to the maintenance personnel, so that the vehicle can be processed before it breaks down. Not only can the battery reliability and durability be increased, but also the customer satisfaction can be improved.

[0056] Power battery consistency detection platform embodiment:

[0057] The embodiment provides a power battery consistency detection platform. The power battery consistency detection platform comprises an acquisition module and a processing module. The acquisition module is connected with the processing module.

[0058] In the embodiment, the acquisition module is used for acquiring the battery system data uploaded by the vehicle, and the vehicle battery system data comprises the highest voltage, the lowest voltage, the average voltage, the temperature, the battery system SOC, the single cell position corresponding to the highest voltage and the lowest voltage and the identification number.

[0059] In the embodiment, the processing module obtains the voltage difference based on the obtained highest voltage and lowest voltage, judges whether it is the charging and discharging platform period data according to the SOC, and screens the vehicle battery system data in the charging and discharging platform period; after the screening and processing, the cumulative proportion of the voltage difference greater than the set pressure difference is calculated, and the SOC is calculated based on the linear relationship between the cumulative proportion and the SOC; whether the SOC is greater than the warning critical value is judged, and if greater than or equal to the warning critical value, the battery consistency is poor. That is, the processing module is based on the vehicle battery system data obtained to realize the power battery consistency detection method in the method embodiment of the present application. The power battery consistency detection method has been described in detail in the above method embodiment, and will not be repeated here.

[0060] In the embodiment, the cumulative proportion in the processing module has a linear relationship with the △SOC, and the determination method of the linear relationship has been described in detail in the method embodiment, which will not be described here.

[0061] In the embodiment, the power battery consistency detection platform further comprises an alarm module. The alarm module is used to generate an alarm signal after the processing module determines that the battery consistency is poor, and the alarm signal is fed back to the corresponding vehicle.

[0062] The power battery consistency detection platform based on the embodiment can solve the problem that the state of charge deviation is difficult to calculate in the dynamic operation process of the battery in the prior art, thereby causing the misjudgment of the battery consistency.

Claims

1. A method for detecting consistency of a power battery, characterized in that: include: 1) Obtaining vehicle battery system data, including the maximum and minimum voltages, and the battery system SOC, and obtaining a voltage difference based on the maximum and minimum voltages; 2) Determine whether the data is in the charging and discharging plateau period based on the SOC, and filter the vehicle battery system data in the charging and discharging plateau period; 3) After the screening process, the cumulative proportion of voltage differences greater than the set voltage difference is calculated, and the ΔSOC is calculated based on the relationship between the cumulative proportion and the ΔSOC; 4) Determine whether ΔSOC is greater than the warning threshold. If it is greater than or equal to the warning threshold, the battery consistency is poor.

2. The power battery consistency detection method according to claim 1, characterized in that: In step 3), the cumulative proportion is linearly related to ΔSOC.

3. The power battery consistency detection method according to claim 2, characterized in that: Methods for determining a linear relationship include: Obtain vehicle battery system data for multiple vehicles, obtain a voltage difference based on the highest and lowest voltages during the charge and discharge plateau, and obtain a delta SOC based on the SOCs corresponding to the highest and lowest voltages; The voltage differences are statistically grouped and the cumulative proportion of voltage differences within different groups is calculated; The △SOC and cumulative proportion in different groups are fitted to obtain linear relationship expressions of different groups. The group with the highest linear correlation is determined from each group of linear relationship expressions, and the voltage difference corresponding to the group is used as the set voltage difference, and the linear relationship expression of the group is used as the final linear relationship expression.

4. The power battery consistency detection method according to claim 1, characterized in that: The system also includes a clearing process, which includes clearing vehicle battery system data acquired at a temperature lower than a set temperature.

5. The power battery consistency detection method according to claim 1, characterized in that: In step 1), the vehicle battery system data obtained is operation data.

6. A power battery consistency detection platform, characterized in that: include: Acquisition module and processing module; The acquisition module is used to obtain vehicle battery system data, including the maximum voltage and minimum voltage, as well as the battery system SOC; The processing module obtains the voltage difference based on the highest and lowest voltages obtained, determines whether it is the charge and discharge plateau data based on the SOC, and filters the vehicle battery system data in the charge and discharge plateau period; after the screening process, calculates the cumulative proportion of voltage differences greater than the set voltage difference, and calculates the △SOC based on the relationship between the cumulative proportion and the △SOC; determines whether the △SOC is greater than the warning critical value. If it is greater than or equal to the warning critical value, the battery consistency is poor.

7. The power battery consistency detection platform according to claim 6, characterized in that: In the processing module, the cumulative proportion is linearly related to △SOC.

8. The power battery consistency detection platform according to claim 7, characterized in that: In the processing module, the method for determining the linear relationship includes: obtaining vehicle battery system data of multiple vehicles, obtaining a voltage difference based on the highest voltage and the lowest voltage, and obtaining a △SOC based on the SOC corresponding to the highest voltage and the lowest voltage during the charge and discharge plateau period; statistically grouping the voltage difference, and calculating the cumulative proportion of the voltage difference in different groups; fitting the △SOC and the cumulative proportion in different groups to obtain linear relationship equations for different groups, determining the group with the highest linear correlation from each group of linear relationship equations, using the voltage difference corresponding to the group as the set voltage difference, and using the linear relationship equation of the group as the final linear relationship equation.

9. The power battery consistency detection platform according to claim 6, characterized in that: The processing module also includes a clearing process, which includes clearing the vehicle battery system data obtained at a temperature lower than a set temperature; in the acquisition module, the vehicle battery system data obtained is operating data.

10. The power battery consistency detection platform according to claim 6, characterized in that: It also includes an alarm module, which is used to generate an alarm signal and feed it back to the corresponding vehicle after the processing module determines that the battery consistency is poor.

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