A battery pack inconsistency analysis and correction method, system and storage medium

Abstract

The present application proposes a battery PACK inconsistency analysis and correction method, system and storage medium, the method comprising: including several PACKs in any battery cluster to be tested, and any PACK contains several battery cell parameters; obtaining the standard deviation and range of any battery cell parameter at each moment within a preset time period, and calculating the maximum value of the range, the minimum value of the range and the range of the range; then determining the threshold judgment interval based on these range values, and then determining the dynamic correction coefficient at each moment; then calculating the corrected standard deviation based on the standard deviation and the dynamic correction coefficient; finally completing the battery PACK inconsistency analysis based on the corrected standard deviation. The present application highlights the analysis of the inconsistency analysis of battery cell parameters in the battery cluster through the dynamic correction coefficient, promptly discovers PACKs with obvious inconsistencies, and improves system reliability and safety.

Description

Technical Field

[0001] The present application belongs to the field of battery technology, and in particular, relates to a battery PACK inconsistency analysis and correction method, system and storage medium. Background Art

[0002] In large-scale energy storage systems, the consistency of PACKs within a battery cluster is an important factor affecting system performance and reliability. When performing consistency analysis on PACKs within a battery cluster, it is usually necessary to select a time period, also known as the "window time", to ensure the time consistency of the analysis. Generally, the standard deviation of a parameter of the battery cell within the PACK at the same time is selected as the characteristic parameter. If the standard deviation of the selected parameter is the same, if the standard deviation of a parameter of two PACKs at a certain time is the same, then their distribution may be diverse, but since the discrete degree values ​​of the two are the same, if the window time is too small, the analysis results may be affected by accidental factors, such as the discrete curves are intertwined, making it difficult to distinguish and output intuitive discrete images for inconsistency analysis, thus failing to accurately reflect the actual situation of the PACK with obvious inconsistency within the selected characteristic parameter cluster. Summary of the invention

[0003] In response to the defects of the above-mentioned prior art, the present application provides a battery PACK inconsistency analysis and correction method, system and storage medium, which corrects the selected characteristic parameters used to highlight the inconsistency to ensure that the PACKs with obvious inconsistencies and more worthy of attention can be clearly highlighted, so as to facilitate timely detection and intervention of PACKs with obvious inconsistencies, thereby improving system reliability and safety.

[0004] To achieve the above-mentioned purpose, the present application provides a battery PACK inconsistency analysis and correction method, wherein any battery cluster to be tested includes several PACKs, and any PACK includes several battery cell parameters; the standard deviation and range of any battery cell parameter in any PACK at each moment are obtained within a preset time period, and the maximum value of the range, the minimum value of the range and the range of the range are respectively obtained according to the range of any battery cell parameter; the method comprises:

[0005] S100: obtaining a threshold determination interval according to the maximum value of the range, the minimum value of the range and the range of the range, and determining a dynamic correction coefficient of any cell parameter at each moment in a preset time period according to a preset rule based on the threshold determination interval.

[0006] S200: Calculating a corrected standard deviation of any cell parameter at any time within a preset time period according to the standard deviation of any cell parameter and a dynamic correction coefficient.

[0007] S300: completing battery PACK inconsistency analysis according to the corrected standard deviation of any battery cell parameter.

[0008] In the present application, the threshold determination interval is obtained according to the maximum value of the range, the minimum value of the range and the range of the range, specifically:

[0009] The threshold range of the threshold determination interval is set to be not less than the minimum value of the extreme difference and not greater than the maximum value of the extreme difference; wherein the threshold determination interval sequentially includes a plurality of continuous determination ranges.

[0010] The threshold range setting of any judgment range at least includes: not less than a first value, and less than a second value; wherein the first value is greater than the minimum value of the range, and the second value is less than the maximum value of the range; the first value is calculated by multiplying the range of the range by a preset parameter n, and adding the result to the minimum value of the range; the second value is calculated by multiplying the range of the range by a preset parameter t, and adding the result to the minimum value of the range; wherein n refers to a constant greater than 0 but less than 1, and t refers to a constant greater than n but less than 1.

[0011] In the present application, the dynamic correction coefficient of any cell parameter at each moment in a preset time period is determined according to the threshold determination interval according to a preset rule, specifically:

[0012] When the range of any of the battery cell parameters satisfies any of the determination ranges, the dynamic correction coefficient of any of the battery cell parameters at each moment within a preset time period is determined according to the preset rule; wherein the preset rule means that the dynamic correction coefficient is positively correlated with the range of any of the battery cell parameters.

[0013] In this application, step S200 is specifically:

[0014] The standard deviation of any battery cell parameter is multiplied by the dynamic correction coefficient to calculate the corrected standard deviation of any battery cell parameter at any time within the preset time period.

[0015] In this application, the battery PACK inconsistency analysis at least includes:

[0016] Within the preset time period, the target parameter value of the corrected standard deviation of any battery cell parameter at each moment is calculated based on the corrected standard deviation of any battery cell parameter, the minimum value of the corrected standard deviation of any battery cell parameter, and the maximum value of the corrected standard deviation of any battery cell parameter; and a discrete image of the battery PACK inconsistency analysis is output based on the changing trend of the target parameter value at each moment within the preset time period.

[0017] Furthermore, the target parameter value of the corrected standard deviation of any cell parameter at each moment is calculated as follows:

[0018] Within the preset time period, the difference between the corrected standard deviation of any battery cell parameter and the minimum value of the corrected standard deviation of any battery cell parameter is divided by the difference between the maximum value of the corrected standard deviation of any battery cell parameter and the minimum value of the corrected standard deviation of any battery cell parameter, to calculate the target parameter value of the corrected standard deviation of any battery cell parameter at each moment.

[0019] To achieve the above objectives, the present application also provides a battery PACK inconsistency analysis and correction system, the system comprising:

[0020] A first processing unit, a second processing unit, and a third processing unit.

[0021] Among them, the first processing unit is used to obtain a threshold judgment interval according to the maximum value of the range, the minimum value of the range and the range of the range, and determine the dynamic correction coefficient of any battery cell parameter at each moment in a preset time period according to preset rules based on the threshold judgment interval.

[0022] The second processing unit is used to calculate the corrected standard deviation of any battery cell parameter at any time within a preset time period according to the standard deviation of any battery cell parameter and the dynamic correction coefficient.

[0023] And, the third processing unit is used to complete the battery PACK inconsistency analysis according to the corrected standard deviation of any battery cell parameter.

[0024] To achieve the above objectives, the present application also provides a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements any of the battery PACK inconsistency analysis and correction methods described above.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The present application proposes a battery PACK inconsistency analysis and correction method, system and storage medium. By setting and using a dynamic correction coefficient, the selected battery cell parameters in the battery cluster are corrected within a preset time period, and then the battery PACK inconsistency analysis is completed using the corrected standard deviation of the selected battery cell parameters, ensuring that the PACK with obvious inconsistency and more worthy of attention can be clearly highlighted, so that the PACK with obvious inconsistency can be discovered and intervened in time when no obvious abnormality occurs in the battery cluster or in the early testing stage, thereby reducing unnecessary losses and improving system reliability and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Flow chart of a battery PACK inconsistency analysis and correction method in one embodiment of the present application.

[0028] Figure 2 This is a timing diagram of the standard deviation of PACK voltage within a cluster with a smaller window time being preferred in the prior art.

[0029] Figure 3 The present invention is a preferred embodiment of the present invention which selects a timing diagram of the standard deviation of voltage parameters within a continuous window time.

[0030] Figure 4 The present invention is a timing diagram of a standard deviation of a PACK voltage within the entire window time cluster before correction, which is preferred in the prior art.

[0031] Figure 5 4 is a timing diagram of the PACK voltage standard deviation in the entire window time cluster after correction in this embodiment.

[0032] Figure 6 This is a timing diagram of the standard deviation of the voltage parameter within the continuous window time after correction in this embodiment.

[0033] Figure 7 It is a block diagram of a battery PACK inconsistency analysis and correction system in one embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme will be clearly and completely described below in conjunction with the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than 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.

[0035] Embodiment 1:

[0036] As attached Figure 1 As shown, in order to solve the above technical problems, the present application provides a battery PACK inconsistency analysis and correction method, in which any battery cluster to be tested includes several PACKs, and any PACK contains several battery cell parameters; the standard deviation and range of any battery cell parameter in any PACK at each moment are obtained within a preset time period, and the maximum value of the range, the minimum value of the range and the range of the range are respectively obtained according to the range of any battery cell parameter.

[0037] It should be noted that the cell parameters may include at least the cell voltage or the cell temperature, but are not limited thereto. The above-mentioned preset time period may be referred to as the window time in this embodiment, and the average level within the window time is calculated to represent the overall level of this period, and multiple consecutive window times are calculated to reflect the time series changes of the cell parameters.

[0038] Preferably, if the cell parameter is the cell voltage, the preset time period should at least include one complete battery charge and discharge cycle.

[0039] Among them, the battery exhibits different characteristics at different stages of the charge and discharge cycle. Including a complete cycle can ensure the comprehensiveness of the data analysis, reflect the inconsistency of the battery in various states, and comprehensively consider the performance changes of the battery throughout the entire working cycle.

[0040] It should be noted that in this embodiment, the method for calculating the standard deviation and the range of the battery cell parameters at each moment in the preset time period is not specifically limited, and any method can be used to accurately calculate the standard deviation and the range.

[0041] Preferably, the standard deviation is an indicator to measure the degree of data dispersion. For any selected battery cell parameters, the standard deviation is calculated as follows:

[0042]

[0043] Among them, σ is the standard deviation, N is the number of battery cell parameters, and x i is the parameter of each battery cell, and μ is the average value of all battery cell parameters.

[0044] Furthermore, the calculation of the range can be: the range is the difference between the maximum and minimum values ​​in the data, which can highlight inconsistent outliers. In order to more comprehensively understand the fluctuation of the data, the range of the range needs to be calculated in this embodiment, that is, the difference between the maximum and minimum values ​​of all ranges.

[0045] In practice, these calculations can usually be implemented through software tools or programming languages, such as Python or MATLAB, to facilitate processing of large amounts of data and complex data analysis.

[0046] In other embodiments, weights can be taken according to the actual loop path of the battery, and combined with the interpolation operation method, smoother temperature data of the temperature measuring points can be calculated to accurately reflect the actual temperature of each battery cell and reduce the error caused by the asymmetric arrangement of the temperature measuring points, thereby providing a reliable and accurate data basis for the screening of inconsistent temperature analysis of the battery cells in the battery cluster in this embodiment.

[0047] In this embodiment, the method mainly includes:

[0048] S100: obtaining a threshold determination interval according to the maximum value of the range, the minimum value of the range and the range of the range, and determining a dynamic correction coefficient of any cell parameter at each moment in a preset time period according to a preset rule based on the threshold determination interval.

[0049] It should be noted that in this embodiment, the dynamic correction coefficient is recorded as k, because in the prior art, it is not intuitive to observe the dispersion of the selected characteristic parameters of the cells in the PACK only by the standard deviation of the selected parameters at the same time. Figure 2 As shown in the figure, it is a timing diagram of the standard deviation of the voltage of five PACKs in a cluster under a small window time of a certain charging condition. In which, a battery cluster includes 5 PACKs, each PACK includes 48 battery cells, the horizontal axis is time, and the vertical axis is the standard deviation of the voltage parameter of the battery. Figure 2 It can be observed that the discrete curves of each PACK in the second half are intertwined and difficult to distinguish.

[0050] As attached Figure 3 As shown in the figure, it is a time series image of the single window time mean of the voltage parameter when the continuous window time is selected for the 5 PACKs of a power station. It can be seen from the image discrete curve that due to the short operation time of the battery cluster, the attached Figure 3 The data before November 23, 2023 is almost difficult to distinguish, and it is difficult to obtain accurate and reliable analysis results. Based on this, this embodiment introduces a suitable and flexible dynamic correction coefficient k for analysis and correction, which can highlight the PACK that deserves more attention, so as to find problems in time.

[0051] Among them, the dynamic correction coefficient k in this embodiment depends on the range of the selected parameters of a single PACK at each moment and the maximum value of the range of all PACKs in the cluster at that moment. Calculating the k value does not directly implement the intervention of the PACK with obvious inconsistency in the battery cluster. k is used to correct the standard deviation of the selected battery cell parameters at this moment, and the purpose is to remind the user to perform manual intervention.

[0052] Further, in the embodiment of the present application, the threshold determination interval is obtained according to the maximum value of the range, the minimum value of the range and the range of the range, specifically:

[0053] The threshold range of the threshold determination interval is set to be not less than the minimum value of the extreme difference and not greater than the maximum value of the extreme difference; wherein the threshold determination interval sequentially includes a plurality of continuous determination ranges.

[0054] It should be noted that in order to widen the gap in standard deviation when the extreme values ​​of the battery cell parameters selected by different PACKs are different, the present embodiment can divide the threshold determination interval into several continuous determination ranges in sequence, wherein the number of determination ranges can be manually set and arbitrarily adjusted according to actual conditions, for example, 2, 3, 4, 5 or 7, but not limited thereto.

[0055] The threshold range setting of any judgment range at least includes: not less than a first value, and less than a second value; wherein the first value is greater than the minimum value of the range, and the second value is less than the maximum value of the range; the first value is calculated by multiplying the range of the range by a preset parameter n, and adding the result to the minimum value of the range; the second value is calculated by multiplying the range of the range by a preset parameter t, and adding the result to the minimum value of the range; wherein n refers to a constant greater than 0 but less than 1, and t refers to a constant greater than n but less than 1.

[0056] It should be noted that the threshold range setting of any judgment range is not limited to including the first value and the second value, and can be flexibly added according to the specific division of the judgment range. For example, the first value can be added to include value A and value B, and the second value can be added to include value C and value D. Then, the threshold range setting of any judgment range can include: not less than value A, and less than value B; the continuous judgment ranges are: [minimum value of the range, value A), [value A, value B), [value B, value C), [value C, value D), [value D, maximum value of the range], which are not limited to this.

[0057] In addition, the number of preset parameters is 1 less than the number of set judgment ranges, and the values ​​of the preset parameters can be arbitrarily selected within the above-specified ranges, and are not limited thereto.

[0058] Preferably, in this embodiment, the threshold determination interval is divided into four continuous determination ranges in sequence. Then, a preset parameter f needs to be added. The specific implementation process is as follows:

[0059] The maximum value of the range of all PACK selected cell parameters in a single cluster at each moment is C r-max , the minimum value of the range is C r-min , the range of the extreme is C r-r , the preset parameter n can be selected as 0.2, then the first judgment range can be expressed as [C r-min ,C r-min +0.2C r-r ); The preset parameter t can be selected as 0.5, then the second determination interval can be expressed as [C r-min +0.2C r-r ,C r-min +0.5C r-r ); The preset parameter f can be selected as 0.8, then the third determination interval can be expressed as [C r-min +0.5C r-r ,C r-min +0.8C r-r ); Finally, the fourth decision interval can be expressed as [C r-min +0.8C r-r ,Cr-max ].

[0060] Furthermore, when the range of any battery cell parameter satisfies any of the judgment ranges, the dynamic correction coefficient of any battery cell parameter at each moment within a preset time period is determined according to the preset rule; wherein the preset rule means that the dynamic correction coefficient is positively correlated with the range of any battery cell parameter.

[0061] It should be noted that the dynamic correction coefficient can preferably be in the form of an exponential of the natural constant e, firstly because many common natural laws are related to natural constants; secondly because the exponential difference ratio is larger, which can more effectively widen the gap caused by inconsistency. However, the value form is not fixed. The purpose of this embodiment is only to widen the intuitive gap of the PACK inconsistency analysis, so it can also be expressed in the form of an exponential of other constants greater than 1, or set on the premise of satisfying the above preset rules, so that as long as the test value falls within the set different intervals, it can intuitively present the result of widening the obvious gap, that is, to ensure that the k value with a large extreme difference is large, and the k value with a small extreme difference is small, and the two are positively correlated, which is not limited to this.

[0062] Preferably, in the above example, when the range of the cell parameter selected by PACK falls within the interval [C r-min ,C r-min +0.2C r-r ), the dynamic correction coefficient can be determined as k = e -2 , where e is the base and -2 is the exponent; when the range of the cell parameters selected by PACK falls within the interval [C r-min +0.2C r-r ,C r-min +0.5C r-r ), the dynamic correction coefficient k = e -1.5 ; When the range of the cell parameters selected by PACK falls within the interval [C r-min +0.5C r-r ,C r-min +0.8C r-r ), the dynamic correction coefficient k = e -1 ; When the range of the cell parameters selected by PACK falls within the interval [C r-min +0.8C r-r ,C r-max ], the dynamic correction coefficient k = e 0 .

[0063] In summary, step S100 of this embodiment mainly introduces a dynamic correction coefficient k to make the discreteness of the cell parameters of different PACKs more intuitive, which is convenient for identifying PACKs with obvious inconsistencies; the dynamic correction coefficient is positively correlated with the range of the cell parameters. The larger the range, the larger the correction coefficient, so that the inconsistency can be captured more sensitively; by dividing the threshold judgment interval into multiple continuous judgment ranges, it can be flexibly adjusted according to actual conditions to meet different analysis needs; by setting preset parameters, the gap between standard deviations in different intervals can be further widened, making the inconsistency more obvious; the use of dynamic correction coefficients can reduce the intervention of PACKs with obvious inconsistencies in the battery cluster, thereby optimizing the analysis efficiency. This embodiment can adapt to different battery types and working conditions, because the division of the threshold judgment interval and the selection of preset parameters can be adjusted according to actual conditions, greatly improving the overall reliability and stability of the battery cluster.

[0064] S200: Calculating a corrected standard deviation of any cell parameter at any time within a preset time period according to the standard deviation of any cell parameter and a dynamic correction coefficient.

[0065] It should be noted that the corrected standard deviation can be calculated through the dynamic correction coefficient obtained above, and the corrected standard deviation is used to remind the user to perform manual intervention, such as re-grouping the PACK with obvious inconsistency or adjusting the charge and discharge strategy.

[0066] Further, in the embodiment of the present application, the step S200 is specifically as follows:

[0067] The standard deviation of any battery cell parameter is multiplied by the dynamic correction coefficient to calculate the corrected standard deviation of any battery cell parameter at any time within the preset time period.

[0068] Preferably, in this embodiment, k is multiplied by the standard deviation of each PACK at that moment, and then the image is plotted using the corrected standard deviation, so that a discrete image of the selected characteristic parameters with clear layers can be obtained. The PACK that is significantly higher than other PACKs in the image has the most obvious inconsistency.

[0069] S300: completing battery PACK inconsistency analysis according to the corrected standard deviation of any battery cell parameter.

[0070] In the embodiment of the present application, the battery PACK inconsistency analysis at least includes:

[0071] Within the preset time period, the target parameter value of the corrected standard deviation of any battery cell parameter at each moment is calculated based on the corrected standard deviation of any battery cell parameter, the minimum value of the corrected standard deviation of any battery cell parameter, and the maximum value of the corrected standard deviation of any battery cell parameter; and a discrete image of the battery PACK inconsistency analysis is output based on the changing trend of the target parameter value at each moment within the preset time period.

[0072] It should be noted that in order to highlight the intuitive gap of the above-mentioned PACK analysis inconsistency in this embodiment, the standard deviation of the selected battery cell parameters at each moment after multiplication by the dynamic correction coefficient k can also be normalized according to actual needs, and the target parameter value is calculated. The target parameter value refers to the standard deviation of the corrected and normalized battery cell parameters. Then, the average or maximum value of the corrected and normalized selected parameter standard deviation can be calculated, and the calculated result is called a discrete parameter. If there is a continuous window time, the trend of the discrete parameters of the PACK changing over time can be observed, and these changing trends can be output as discrete images of battery PACK inconsistency analysis. According to the discrete image, it is possible to further visually observe whether there are PACKs with obvious inconsistencies in the battery cluster. If so, human intervention can be carried out as appropriate, such as re-grouping of the PACKs in the cluster, to improve the overall reliability and stability of the system and reduce unnecessary losses.

[0073] Preferably, assuming that the window time is selected as a preset time period of 24 hours a day, then the result of calculating the daily average can widen the gap between the PACK discrete parameters with the most obvious inconsistency and the longest inconsistency time and other PACK discrete parameters every day, and calculating the maximum value can reflect the maximum discrete level of each PACK within the window time, which is not limited to this.

[0074] Furthermore, the target parameter value of the corrected standard deviation of any cell parameter at each moment is calculated as follows:

[0075] Within the preset time period, the difference between the corrected standard deviation of any battery cell parameter and the minimum value of the corrected standard deviation of any battery cell parameter is divided by the difference between the maximum value of the corrected standard deviation of any battery cell parameter and the minimum value of the corrected standard deviation of any battery cell parameter, to calculate the target parameter value of the corrected standard deviation of any battery cell parameter at each moment.

[0076] It should be noted that the calculation process of the target parameter value of the corrected standard deviation of any cell parameter at each moment in this embodiment can refer to the following:

[0077] For example, suppose that the inconsistency analysis when selecting continuous window time for 5 PACKs needs to be analyzed, then the normalization process can be implemented by the following formula:

[0078]

[0079] Among them, A PACKi represents the corrected standard deviation of PACKi before normalization, A PACKi ' represents the corrected standard deviation of the normalized PACKi, (A PACKi ) min and (A PACKi ) max Indicates the minimum and maximum standard deviation of the cluster before PACK normalization at that moment.

[0080] Preferably, as attached Figure 4 The standard deviation timing diagram of the standard deviation of the PACK voltage parameter in the entire window time cluster before correction is shown in the attached figure. Figure 5 As shown in the attached Figure 4 By correcting the standard deviation of the selected parameters of PACK based on the data, a discrete curve of the discrete parameters of PACK changing with time within a window time is obtained. From the comparison of the curves at the same time in the two figures, it can be seen that after the design scheme of the embodiment of the present application, the PACK with greater inconsistency problems at each moment can be more highlighted.

[0081] In addition, in this embodiment, the window time selection can be appropriately increased. When the amount of data frames is also large, the randomness in data analysis can be reduced. Even if multiple frames of data in a certain period are abnormal, it will not have a significant impact on the results, thereby improving the accuracy of the inconsistency analysis of PACKs within the cluster. The final discrete parameter curve can be clearly layered, and the PACKs with obvious inconsistencies can be intuitively highlighted on the discrete image, which is convenient for users to quickly locate the PACKs with obvious inconsistencies within the cluster and discover problems in a timely manner.

[0082] In another preferred embodiment, as shown in the attached Figure 6 As shown, for Figure 3 The discrete parameter time series diagram of the continuous window time in which the standard deviation of the original data at each moment is corrected and then normalized to find the average. By comparison, it can be seen that when the single window time is selected as one day, the discrete parameters PACK3 and PACK4 of the corrected selected feature parameters are significantly higher than other PACKs in the cluster in the early stage, and there is an obvious stratification phenomenon. In the later stage, the discrete parameters of PACK4 are higher than PACK3, which can reflect that the embodiment of the present application has played an obvious and effective role in correcting the standard deviation, and has achieved more valuable inconsistency problems. For example, although the standard deviation of the above PACK4 is smaller than that of PACK3, its range is larger at most times, so after correction, the attached Figure 6 The discrete parameters are located at the top. Figure 6PACK2 and PACK5 in the figure can also reflect the effect of the correction. Before the correction, the two are almost close together. After the correction, PACK2 is significantly higher than PACK5, which means that the standard deviations of the two are almost the same, but the range of PACK2 is greater than that of PACK5 at most times.

[0083] In summary, the embodiment of the present application corrects the selected parameters of different battery clusters by defining a dynamic correction coefficient; uses the standard deviation to measure the degree of data dispersion, and combines the range correction and normalization to take the mean or maximum value as a discrete parameter to judge the inconsistency of the PACK in the battery cluster, further widening the gap between the PACK with obvious inconsistency and other PACKs, thereby more intuitively highlighting the problematic PACK, and achieving timely discovery and intervention of the PACK with obvious inconsistency before obvious abnormality occurs in the battery cluster or in the early testing stage, thereby reducing unnecessary losses and improving system reliability and safety.

[0084] Embodiment 2:

[0085] As attached Figure 7 As shown, in order to solve the above technical problems, the present application also proposes a battery PACK inconsistency analysis and correction system, the system comprising:

[0086] A first processing unit, a second processing unit, and a third processing unit.

[0087] Among them, the first processing unit is used to obtain a threshold judgment interval according to the maximum value of the range, the minimum value of the range and the range of the range, and determine the dynamic correction coefficient of any battery cell parameter at each moment in a preset time period according to preset rules based on the threshold judgment interval.

[0088] It should be noted that the unit is responsible for determining the threshold judgment interval according to the maximum value, minimum value and range of the range, and calculating the dynamic correction coefficient at each moment according to the preset rules based on this information. This embodiment can more accurately reflect the inconsistency of PACK in the battery cluster by introducing the dynamic correction coefficient, making the PACK with obvious inconsistency more prominent.

[0089] The second processing unit is used to calculate the corrected standard deviation of any battery cell parameter at any time within a preset time period according to the standard deviation of any battery cell parameter and the dynamic correction coefficient.

[0090] It should be noted that the unit uses the dynamic correction coefficient calculated by the first processing unit and the standard deviation of the cell parameter to calculate the corrected standard deviation. This embodiment can more intuitively display the inconsistency of the PACK through the corrected standard deviation, making it easier to identify the PACK with obvious inconsistency.

[0091] And, the third processing unit is used to complete the battery PACK inconsistency analysis according to the corrected standard deviation of any battery cell parameter.

[0092] It should be noted that the unit completes the battery PACK inconsistency analysis based on the corrected standard deviation. This embodiment completes the battery PACK inconsistency analysis by analyzing the corrected standard deviation to obtain discrete parameters and draw discrete curves, which can more intuitively and timely discover PACKs with obvious inconsistencies, so as to take measures to intervene and improve the reliability and safety of the system.

[0093] In summary, the design of the entire system in the second embodiment aims to improve the accuracy and intuitiveness of the PACK inconsistency analysis in the battery cluster by introducing a dynamic correction coefficient, so that the PACK with obvious inconsistency can be discovered and intervened before the battery cluster has obvious abnormalities or in the early test stage, thereby reducing unnecessary losses and improving system reliability and safety. The specific implementation process and principle have been introduced in detail in the first embodiment and will not be repeated in this embodiment.

[0094] Embodiment three:

[0095] The present application also provides a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the battery PACK inconsistency analysis and correction method as described above is implemented.

[0096] It should be noted that the storage medium in this embodiment may refer to a physical or virtual device for storing data, such as a hard disk, a solid state disk, an optical disk, a USB flash drive, etc. It includes computer programs, which, when executed on a processor, can implement the battery PACK inconsistency analysis and correction method described above.

[0097] Preferably, in this embodiment, the corresponding computer program code can be obtained according to the steps of the battery PACK inconsistency analysis and correction method. These codes will include data collection, calculation of standard deviation and range, calculation of dynamic correction coefficient, determination of threshold judgment interval, calculation of corrected standard deviation and inconsistency analysis. Then, the written program will be stored on a computer-readable storage medium, such as a USB flash drive or a hard disk on a server. When the analysis needs to be performed, the user will connect the storage medium to the computer and start the program. The computer processor will read the program code on the storage medium and execute the analysis process according to the instructions of the code. The program will automatically collect the data of the battery cluster, calculate the standard deviation and range, determine the dynamic correction coefficient, calculate the corrected standard deviation, and complete the inconsistency analysis based on these data.

[0098] Finally, after the inconsistency analysis is completed, the program will output the analysis results, which may include the identification of PACKs with obvious inconsistencies, recommended measures that require user intervention, etc. These results can be used to guide the management and maintenance of battery clusters, greatly improving the overall reliability and stability of the battery system.

[0099] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The memory is used to store an operating system, an application program, a boot loader, data, and other programs, such as the program code of the computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

[0100] In several embodiments provided in the present application, it is understood that each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved.

[0101] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0102] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A battery PACK inconsistency analysis and correction method, wherein any battery cluster to be tested includes several PACKs, and any PACK contains several battery cell parameters; the standard deviation and range of any battery cell parameter in any PACK at each moment are obtained within a preset time period, and the maximum value of the range, the minimum value of the range and the range of the range are obtained according to the range of any battery cell parameter; characterized in that, The method comprises: S100: obtaining a threshold determination interval according to the maximum value of the range, the minimum value of the range and the range of the range, and determining a dynamic correction coefficient of any cell parameter at each moment in a preset time period according to a preset rule based on the threshold determination interval; S200: calculating a corrected standard deviation of any cell parameter at any moment in a preset time period according to the standard deviation of any cell parameter and the dynamic correction coefficient; S300: completing battery PACK inconsistency analysis according to the corrected standard deviation of any battery cell parameter.

2. A battery PACK inconsistency analysis and correction method according to claim 1, characterized in that: The threshold determination interval is obtained according to the maximum value of the range, the minimum value of the range and the range of the range, specifically: The threshold range of the threshold determination interval is set to be not less than the minimum value of the range and not greater than the maximum value of the range; wherein the threshold determination interval sequentially includes a plurality of continuous determination ranges; The threshold range setting of any determination range includes at least: not less than a first value and less than a second value; Wherein, the first value is greater than the minimum value of the range, and the second value is less than the maximum value of the range; The first value is calculated by multiplying the range of the range and the preset parameter n, and adding the minimum value of the range; The second value is calculated by multiplying the range of the range and the preset parameter t, and adding the minimum value of the range; Here, n is a constant greater than 0 but less than 1, and t is a constant greater than n but less than 1.

3. A battery PACK inconsistency analysis and correction method according to claim 2, characterized in that: The dynamic correction coefficient of any cell parameter at each moment in a preset time period is determined according to the threshold determination interval according to a preset rule, specifically: When the extreme difference of any of the battery cell parameters satisfies any of the determination ranges, determining the dynamic correction coefficient of any of the battery cell parameters at each moment within a preset time period according to the preset rule; The preset rule means that the dynamic correction coefficient is positively correlated with the extreme value of any battery cell parameter.

4. A battery PACK inconsistency analysis and correction method according to claim 1, characterized in that: The step S200 is specifically as follows: The standard deviation of any battery cell parameter is multiplied by the dynamic correction coefficient to calculate the corrected standard deviation of any battery cell parameter at any time within the preset time period.

5. A battery PACK inconsistency analysis and correction method according to claim 1, characterized in that: The battery PACK inconsistency analysis at least includes: In the preset time period, according to the corrected standard deviation of any battery cell parameter, the minimum value of the corrected standard deviation of any battery cell parameter, and the maximum value of the corrected standard deviation of any battery cell parameter, a target parameter value of the corrected standard deviation of any battery cell parameter at each moment is calculated; According to the changing trend of the target parameter value at each moment within the preset time period, a discrete image of battery PACK inconsistency analysis is output.

6. A battery PACK inconsistency analysis and correction method according to claim 5, characterized in that: The target parameter value for calculating the corrected standard deviation of any cell parameter at each moment is specifically: Within the preset time period, the difference between the corrected standard deviation of any battery cell parameter and the minimum value of the corrected standard deviation of any battery cell parameter is divided by the difference between the maximum value of the corrected standard deviation of any battery cell parameter and the minimum value of the corrected standard deviation of any battery cell parameter, to calculate the target parameter value of the corrected standard deviation of any battery cell parameter at each moment.

7. A system for analyzing and correcting battery PACK inconsistency according to any one of claims 1 to 6, characterized in that: include: a first processing unit, a second processing unit, and a third processing unit; The first processing unit is used to obtain a threshold determination interval according to the maximum value of the range, the minimum value of the range and the range of the range, and determine a dynamic correction coefficient of any battery cell parameter at each moment in a preset time period according to a preset rule based on the threshold determination interval; The second processing unit is used to calculate the corrected standard deviation of any battery cell parameter at any time within a preset time period according to the standard deviation of any battery cell parameter and the dynamic correction coefficient; And, the third processing unit is used to complete the battery PACK inconsistency analysis according to the corrected standard deviation of any battery cell parameter.

8. A storage medium, which is a computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the battery PACK inconsistency analysis and correction method according to any one of claims 1 to 6 is implemented.

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