A method and system for detecting a sampling harness of a power battery

Abstract

The application relates to the technical field of data processing, in particular to a sampling harness detection method and system for a power battery. The method collects voltage data sequences of each sampling harness at a preset initial sampling frequency; determines an instability index according to fluctuation amplitude characteristics and change rate characteristics of the voltage data sequences; calculates an adjustment coefficient if the instability index exceeds a preset adjustment threshold; adjusts the initial sampling frequency to a target sampling frequency according to the adjustment coefficient; collects test voltage data sequences at the target sampling frequency, and determines a sampling redundancy index according to the frequency of repeated voltage values; corrects the target sampling frequency to an optimal sampling frequency based on the sampling redundancy index if the sampling redundancy index is not within a preset threshold range; collects voltage data of all sampling harnesses at the optimal sampling frequency, and then determines an abnormal probability; and determines that the sampling harness is abnormal if the abnormal probability exceeds a preset abnormal threshold, thereby improving the accuracy of the sampling harness detection result.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a sampling harness detection method and system for power battery. BACKGROUND

[0002] The sampling harness of the power battery, as a signal transmission channel of the battery management system, is responsible for real-time transmission of key parameters such as voltage and temperature, and directly affects the judgment accuracy of safety risks such as overcharge, overdischarge and thermal runaway. If signal abnormalities are caused by insulation failure, poor contact or mechanical damage, it may lead to misjudgment of BMS. Therefore, strict detection of the sampling harness can identify potential hazards in advance and reduce the risk of accidents.

[0003] At present, in the process of detecting the sampling harness of the power battery, the voltage signal of the sampling harness is usually collected at a fixed sampling frequency to detect faults of the sampling harness. However, this method cannot timely respond to sudden faults of the sampling harness, such as transient voltage fluctuations caused by poor contact, and if the collected signal changes rapidly, the large sampling frequency interval will cause loss of key features, ultimately affecting the authenticity of the sampling harness detection result. SUMMARY

[0004] In order to solve the technical problem of key data loss caused by inappropriate sampling frequency and affect the accuracy of the sampling harness detection result, the present application provides a sampling harness detection method and system for power battery, and the technical solution is as follows:

[0005] The present application provides a sampling harness detection method for power battery, which comprises the following steps:

[0006] Real-time collection of voltage data sequences of each sampling harness at a preset initial sampling frequency, wherein the voltage data sequence is composed of voltage values arranged in time sequence;

[0007] For each sampling harness, determine the instability index of the sampling harness according to the fluctuation amplitude feature and the change rate feature of the voltage data sequence;

[0008] If the instability index exceeds the preset adjustment threshold, determine the adjustment coefficient for adjusting the sampling frequency according to the absolute difference between the instability index and the adjacent voltage value; adjust the initial sampling frequency to the target sampling frequency according to the adjustment coefficient and the preset upper limit of the sampling frequency;

[0009] collecting a test voltage data sequence at a target sampling frequency, determining a sampling redundancy index for verifying effectiveness of the target sampling frequency according to frequencies of repeated voltage values in the test voltage data sequence; if the sampling redundancy index is not within a preset threshold range, correcting the target sampling frequency to an optimal sampling frequency based on the sampling redundancy index;

[0010] synchronously collecting voltage data of all sampling harnesses at the optimal sampling frequency, determining an abnormality probability according to differences between voltage values at the same time in the voltage data of all sampling harnesses; if the abnormality probability exceeds a preset abnormality threshold, determining that the sampling harness is abnormal.

[0011] Further, the instability index determination process comprises:

[0012] identifying a steady-state switching turning point in the voltage data sequence, wherein the steady-state switching turning point is used to indicate a first data point at which a continuous preset number of voltage values change from satisfying a steady-state condition to not satisfying the steady-state condition;

[0013] extracting non-steady-state segment voltage data from the steady-state switching turning point to a current time from the voltage data sequence;

[0014] determining a change index of the sampling harness according to difference characteristics between voltage values in the non-steady-state segment voltage data;

[0015] obtaining a duration from the steady-state switching turning point to the current time;

[0016] normalizing the voltage value of the sampling harness at the current time, the change index and the duration to obtain an instability index.

[0017] Further, the change index determination process comprises:

[0018] obtaining a maximum voltage value and a minimum voltage value in the non-steady-state segment voltage data;

[0019] calculating a difference between the maximum voltage value and the minimum voltage value as a first difference;

[0020] calculating absolute differences between each pair of adjacent voltage values in the non-steady-state segment voltage data as second differences;

[0021] performing an arithmetic average calculation on all second differences to obtain a first average value;

[0022] calculating a product of the first difference and the first average value as the change index.

[0023] Further, the adjustment coefficient determination process comprises:

[0024] calculating absolute difference values of voltage values of adjacent data points in the voltage data sequence as third difference values; for each third difference value, dividing the third difference value by a time interval between the corresponding adjacent data points to obtain a change rate;

[0025] performing an arithmetic average calculation on all the change rates to obtain an average change rate;

[0026] multiplying the average change rate by the instability index and performing normalization processing to obtain an adjustment coefficient.

[0027] Further, according to the adjustment coefficient and a preset upper limit of a sampling frequency, the initial sampling frequency is adjusted to a target sampling frequency, including:

[0028] Based on the difference between the initial sampling frequency and the preset upper limit of the sampling frequency, the target sampling frequency is obtained by linear interpolation calculation through the adjustment coefficient.

[0029] Further, the sampling redundancy index determination process includes:

[0030] calculating a frequency ratio of data points of repeatedly occurring voltage values in the test voltage data sequence to all data points; and calculating a proportion value of a sum of the repeatedly occurring voltage values in the test voltage data sequence to a total sum of all voltage values;

[0031] calculating a product of the frequency ratio and the proportion value as a sampling redundancy index.

[0032] Further, a sampling harness detection method of a power battery includes:

[0033] If the sampling redundancy index is within a preset threshold range, the target sampling frequency is directly taken as the optimal sampling frequency.

[0034] Further, if the sampling redundancy index is not within the preset threshold range, it is divided into two cases, the first case is that the sampling redundancy index is higher than the upper limit of the preset threshold range, and the second case is that the sampling redundancy index is lower than the lower limit of the preset threshold range; and if the sampling redundancy index is not within the preset threshold range, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index, including:

[0035] If the sampling redundancy index is not within the preset threshold range and belongs to the first case, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index through a preset first frequency correction function;

[0036] If the sampling redundancy index is not within the preset threshold range and belongs to the second case, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index through a preset second frequency correction function.

[0037] Further, the abnormal probability determination process includes:

[0038] The voltage values at the same time in the voltage data of all sampling harnesses are arithmetically averaged to obtain a voltage reference value;

[0039] The sum of the absolute differences between the voltage values at the same time in the voltage data of all sampling harnesses and the corresponding voltage reference values is normalized to obtain an abnormal probability.

[0040] A sampling harness detection system of a power battery, the system comprises a memory, a processor and a computer program stored in the memory and running on the processor, and the processor implements the steps of a sampling harness detection method of a power battery when executing the computer program.

[0041] The present application has the following beneficial effects:

[0042] The present application determines the instability index by analyzing the fluctuation amplitude feature and the change rate feature of the voltage data sequence, and adjusts the sampling frequency dynamically through the instability index, so that the transient features in the voltage data can be accurately captured, and the transient signals can be ensured to be recorded completely. Secondly, in order to collect different stages of the voltage signal, the appropriate sampling frequency can be determined, the adjustment coefficient of the sampling frequency is determined by analyzing the difference between the instability index and the adjacent voltage value, so that the change of the sampling harness can be responded in real time, and the sampling harness can be detected with a more effective sampling frequency. Then, after determining the target sampling frequency, it can also be verified whether the target sampling frequency will produce redundant voltage data amount, whether there is redundant data amount in the test voltage data is explored through the sampling redundancy index, if there is, the target sampling frequency is corrected in time through the sampling redundancy index to obtain the best sampling frequency. Finally, through the best sampling frequency, the redundant data amount in the collected voltage data is reduced, the power consumption is reduced, and the voltage data collected at the best sampling frequency is compared with the voltage difference of multiple sampling harnesses at the same time, and then the abnormal probability is used to detect whether the sampling harness has a fault, and the accuracy of the sampling harness detection result is improved. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art and the advantages thereof, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0044] Figure 1 A flow chart of a sampling harness detection method of a power battery provided by an embodiment of the present application;

[0045] Figure 2 An example of non-steady-state segment voltage data provided by one embodiment of the present application is shown in the following table. DETAILED DESCRIPTION

[0046] In order to further clarify the technical means and effects taken by the present application to achieve the predetermined inventive purpose, the following describes in detail the specific implementation, structure, features and effects of a sampling harness detection method for a power battery according to the present application, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0048] The following describes in detail the specific scheme of a sampling harness detection method for a power battery provided by the present application.

[0049] Please refer to Figure 1 which shows a flowchart of a sampling harness detection method for a power battery provided by one embodiment of the present application. The method comprises:

[0050] S101: Real-time collection of voltage data sequences of each sampling harness at a preset initial sampling frequency, wherein the voltage data sequence is composed of voltage values arranged in time sequence.

[0051] It should be noted that at each collection time, each sampling harness corresponds to an independent voltage signal, i.e. a voltage value.

[0052] It should be noted that the specific value of the preset initial sampling frequency is determined according to actual needs, and the present embodiment does not make specific limitations. For example, when the power battery is normally charged and discharged, the voltage fluctuates slowly. At this time, in order to capture the steady-state fluctuation of the voltage signal, the preset initial sampling frequency can be set to 50 Hz (50 voltage values are collected per second).

[0053] It should be understood that before real-time collection of voltage data sequences of each sampling harness, some preparations can be made to avoid interference of other external factors on the voltage signal, such as cleaning the terminals of the sampling harness to ensure that the contact surface has no oxide layer, fixing the position of the sampling harness to reduce contact noise caused by mechanical vibration, selecting a high-precision, wide-range voltage sensor, configuring a multi-channel data acquisition card, and arranging sampling points at key nodes (such as harness connector interfaces) of the power battery module.

[0054] For example, for the sampling beam k, assuming that the voltage values have been collected in real time for a period of time at a sampling frequency of 50 Hz, the total number of time points in the voltage data sequence can be represented by t, t being a positive integer, and the voltage data sequence of the sampling beam k can be represented as , wherein, represents the voltage value of the sampling beam k collected at the 1st collection time point, represents the voltage value of the sampling beam k collected at the 2nd collection time point; represents the voltage value of the sampling beam k collected at the tth collection time point.

[0055] S102: For each sampling beam, the instability index of the sampling beam is determined according to the fluctuation amplitude feature and the change rate feature of the voltage data sequence.

[0056] It should be understood that if no abnormal condition occurs in the sampling beam, the collected voltage data should be relatively stable, and therefore, whether the voltage data sequence is stable can be preliminarily analyzed by analyzing the fluctuation amplitude of the voltage value and the change of the voltage value, and then whether the sampling beam has an abnormality can be detected.

[0057] In this embodiment, a steady-state switching turning point in the voltage data sequence is identified, wherein the steady-state switching turning point is used to indicate the first data point at which the continuous preset number of voltage values changes from satisfying the steady-state condition to not satisfying the steady-state condition starting from the 1st data point; the non-steady-state segment voltage data from the steady-state switching turning point to the current time point is extracted from the voltage data sequence; the change index of the sampling beam is determined according to the difference feature between the voltage values of the non-steady-state segment voltage data; the duration from the steady-state switching turning point to the current time point is obtained; and the voltage value of the sampling beam at the current time point, the change index and the duration are multiplied and then normalized to obtain the instability index.

[0058] It should be noted that the steady-state condition includes that the fluctuation amplitude of the voltage value is less than a stable threshold.

[0059] It should be noted that the specific values of the preset number and the stable threshold are determined according to actual requirements, and this embodiment does not make specific limitations, for example, the fluctuation amplitude of the continuous preset number (100) of voltage values can be set to be less than the stable threshold (10 mv).

[0060] For example, taking the sampling beam k as an example, a non-steady-state segment voltage data example graph is shown in Figure 2 , wherein, Figure 2 The data point indicated in is the steady-state switching turning point, represents the corresponding collection time point (the s th collection time point).

[0061] Non-steady-state voltage data refers to the data in the voltage data sequence from the steady-state transition point to the last data point.

[0062] For example, suppose This is represented as the voltage value at the steady-state transition point. The data acquisition time is represented as the steady-state transition inflection point; therefore, the voltage data in the unsteady-state segment can be represented as... ,but It can also be expressed as ,in, Corresponding to , and The recorded acquisition time and voltage value are the same. This represents the voltage value of sampling line bundle k collected at the first acquisition time in the unsteady-state voltage data; Corresponding to , and The recorded acquisition time and voltage value are the same. This represents the voltage data in the unsteady-state segment at the [number]th [period]. The voltage value of sampling harness k collected at each sampling time.

[0063] To accurately determine the change index, one possible implementation is to determine the change index based on the maximum voltage difference and the absolute difference between adjacent voltage values ​​in the non-steady-state voltage data.

[0064] As an example, the maximum and minimum voltage values ​​in the unsteady-state voltage data are obtained; the difference between the maximum and minimum voltage values ​​is calculated as the first difference; the absolute difference between each pair of adjacent voltage values ​​in the unsteady-state voltage data is calculated as the second difference; the arithmetic mean of all the second differences is calculated to obtain the first average value; the product of the first difference and the first average value is calculated as the change index.

[0065] The first difference indicates the maximum voltage difference in the unsteady-state voltage data.

[0066] The first average value is used to reflect the overall change in voltage values ​​in the unsteady-state voltage data.

[0067] It should be noted that for each voltage value in the non-steady-state voltage data... (i=2,3,…, The corresponding preceding voltage value is located in the unsteady-state voltage data. Previous and adjacent voltage values , where i is the index number of the voltage value in the unsteady-state voltage data. Calculation with the absolute difference value | | of - | as the second difference value.

[0068] It should be noted that the previous adjacent is only for the forward order of time sequence in the non-steady-state voltage data and does not include cyclic backtracking (such as not associating the end voltage value with the starting voltage value in the non-steady-state voltage data).

[0069] Since the greater the difference between the maximum voltage value and the minimum voltage value in the non-steady-state voltage data, and the greater the difference between each adjacent voltage value, the more obvious and severe the change in the non-steady-state voltage data, reflecting that the voltage signal of the sampling harness is more unstable in the time period in which the non-steady-state voltage data is collected, therefore, the change index can be represented by the following formula:

[0070]

[0071] wherein, represents the change index of the sampling harness k; represents the first difference value of the sampling harness k; represents the voltage value of the sampling harness k collected at the i+1th time point in the non-steady-state voltage data; represents the voltage value of the sampling harness k collected at the ith time point in the non-steady-state voltage data; represents the total number of time points in the non-steady-state voltage data; ; represents the maximum voltage value in the non-steady-state voltage data of the sampling harness k; represents the minimum voltage value in the non-steady-state voltage data of the sampling harness k; | | represents taking the absolute value.

[0072] It should be noted that in actual working conditions, in order to explore whether the voltage signal of the sampling harness is stable, a certain amount of voltage data is required, therefore, in the process of obtaining the voltage data sequence, although the voltage value of the sampling harness is collected in real time, a certain amount of voltage data sequence containing a certain amount of voltage values is determined after a period of time (for example, 1 minute) of voltage value collection, then the data points in the voltage data sequence must exceed 1, and the total number of time points in the non-steady-state voltage data must exceed 1, which cannot be zero.

[0073] It should be understood that although there is unstable voltage data in the voltage data of the sampling harness, if the instability of the sampling harness is low, it may be due to interference factors (such as noise caused by electromagnetic interference). In this case, the sampling frequency does not need to be adjusted. Therefore, in order to avoid the influence of interference factors on the judgment result of whether the sampling frequency needs to be adjusted, and to detect the possible large changes in the voltage data of the sampling harness in time, and to avoid missing key voltage data, it is necessary to further analyze whether the sampling frequency needs to be adjusted.

[0074] Since the greater the change index, the more severe the voltage data fluctuation, and the longer the current time interval steady-state switching turning point, and the greater the voltage value collected at the current time, the more complex the internal situation of the sampling harness, and the more serious the instability of the voltage data, the initial sampling frequency needs to be adjusted at the current time, therefore, the instability index can be represented by the following formula:

[0075]

[0076] Wherein, represents the instability index of the sampling harness k at the tth time (i.e. the current time); represents the duration from the steady-state switching turning point to the current time; represents the change index; represents the voltage value of the sampling harness k at the tth time (i.e. the current time); represents the normalization function.

[0077] The current time refers to the last collection time of the voltage data sequence.

[0078] S103: If the instability index exceeds the preset adjustment threshold, determine the adjustment coefficient for adjusting the sampling frequency according to the absolute difference between the instability index and the adjacent voltage value; adjust the initial sampling frequency to the target sampling frequency according to the adjustment coefficient and the preset upper limit of the sampling frequency.

[0079] It should be noted that the preset adjustment threshold is determined according to actual needs, which is not limited in the embodiment. For example, the preset adjustment threshold is 0.4, which can obviously distinguish the instability of the voltage signal of the sampling harness. When the instability index exceeds the preset adjustment threshold (0.4), the instability of the voltage signal of the sampling harness is more severe.

[0080] In this embodiment, the absolute difference between voltage values ​​of adjacent data points in the voltage data sequence is calculated as the third difference; for each third difference, the third difference is divided by the time interval between the corresponding adjacent data points to obtain the rate of change; all rates of change are arithmetically averaged to obtain the average rate of change; the average rate of change is multiplied by the instability index and then normalized to obtain the adjustment coefficient.

[0081] In this context, it can be understood that a data point in the voltage data sequence refers to the voltage measurement value obtained at a specific acquisition time when the voltage signal of the sampling harness is discretized. Each data point contains timestamp information and the corresponding voltage value.

[0082] It should be noted that for each voltage value in the voltage data sequence (j=2, 3, ..., ), whose corresponding preceding adjacent voltage value is located in the voltage data sequence. Previous and adjacent voltage values , where j is the index number of the voltage value in the voltage data sequence. Calculate and absolute difference | - |

[0083] Since a large difference between adjacent voltage values ​​in a voltage data sequence indicates that many voltage values ​​were missed during the time period required to acquire the voltage data sequence, and the time interval between data points in the voltage data sequence is too long, it is necessary to increase the sampling frequency. Furthermore, a higher instability index indicates a more severe instability in the voltage signal of the sampling harness, requiring an even higher sampling frequency to avoid failing to capture critical voltage signals. Therefore, the adjustment coefficient can be expressed by the following formula:

[0084]

[0085] in, This represents the adjustment factor of the sampling harness k at time t (i.e., the current time); This represents the instability index of the sampling harness k at time t (i.e., the current time); This represents the voltage value at time j in the voltage data sequence of sampled harness k; Indicates and The voltage value of the preceding adjacent voltage at time j+1; express and The time interval between; represents the normalization function; | represents taking the absolute value.

[0086] It should be noted that, in actual working conditions, in order to explore whether the voltage signal of the sampling harness is stable, a certain amount of voltage data is needed, so in the process of obtaining the voltage data sequence, although the voltage value of the sampling harness is collected in real time, a certain amount of voltage data sequence is determined after a period of time (for example, 1 minute) of voltage value collection, so the number of data points in the voltage data sequence must be more than 1, and then It is impossible to be zero; and the time interval between adjacent data points, that is, the sampling time interval, in order to explore the change of the voltage value of the sampling harness, the sampling time interval cannot be set to zero, that is It is impossible to be zero.

[0087] In this embodiment, the target sampling frequency is obtained by linear interpolation calculation based on the difference between the initial sampling frequency and the preset upper limit of the sampling frequency, through the adjustment coefficient.

[0088] It should be noted that the specific value of the preset upper limit of the sampling frequency is determined according to the actual situation, and this embodiment does not make specific limitations, for example, in order to avoid increasing the burden of the power battery management system, the preset upper limit of the sampling frequency is usually 500Hz.

[0089] It should be noted that linear interpolation calculation is a commonly used mathematical method for estimating the value of unknown data points by constructing a straight line under the condition of given some known data points, which is a technical means familiar to those skilled in the art, and this embodiment will not be repeated, for example, the target sampling frequency = initial sampling frequency + (preset upper limit of the sampling frequency-initial sampling frequency) adjustment coefficient.

[0090] It should be noted that linear interpolation calculation makes the sampling frequency smooth transition, avoiding the data fault caused by step change.

[0091] S104: Collecting a test voltage data sequence at the target sampling frequency, determining a sampling redundancy index for verifying the effectiveness of the target sampling frequency according to the frequency of repeated voltage values in the test voltage data sequence; if the sampling redundancy index is not within the preset threshold range, modifying the target sampling frequency to the best sampling frequency based on the sampling redundancy index.

[0092] It should be noted that the most suitable sampling frequency should meet the condition that more fluctuation data can be collected in the non-steady state voltage data, and there is no large range of repeated data in the non-steady state voltage data, so when the target sampling frequency is determined, if the target sampling frequency is high, more repeated data will be generated; if the target sampling frequency is still low, part of the characteristic data will still be lost, so it is necessary to further test whether the target sampling frequency is suitable.

[0093] It should be noted that, in order to ensure the reliability of the test voltage data sequence, so as to more accurately test whether the target sampling frequency is effective, that is, to judge whether the voltage data collected at the target sampling frequency can achieve the effect of neither missing key voltage signals nor excessive repeated data, the test voltage data sequence can be analyzed after a certain collection time (such as 5 seconds).

[0094] In this embodiment, the frequency proportion of the repeated voltage value data points in the test voltage data sequence to the total data points is calculated; the proportion value of the sum of the repeated voltage values in the test voltage data sequence to the total sum of the voltage values is calculated; and the product of the frequency proportion and the proportion value is taken as the sampling redundancy index.

[0095] Since the greater the frequency proportion, the higher the proportion of the repeated voltage value data points in the test voltage data sequence, that is, the higher the frequency of the repeated voltage values, the more the proportion of the repeated voltage values in the test voltage data sequence, and the greater the amount of repeated data, it means that the more repeated data in the test voltage data sequence, and the higher the redundancy of the voltage data collected at the target sampling frequency. Therefore, the sampling redundancy index can be represented by the following formula:

[0096]

[0097] wherein, represents the sampling redundancy index of the sampling harness k; represents the number of repeated voltage value data points in the test voltage data sequence of the sampling harness k; represents the number of all data points in the test voltage data sequence of the sampling harness k; represents the sum of the repeated voltage values in the test voltage data sequence of the sampling harness k; represents the total sum of the voltage values in the test voltage data sequence of the sampling harness k.

[0098] It should be noted that, in actual working conditions, in order to ensure the reliability of the test voltage data sequence, the test voltage data sequence needs to contain a certain amount of data points, so that and cannot be zero.

[0099] It should be noted that, in order to eliminate the influence of different characteristic factors of dimension (unit) and value range difference, the sampling redundancy index, i.e. needs to be normalized.

[0100] It should be understood that the optimal sampling frequency should ensure that all voltage data values can be collected on the basis of reducing repeated data as much as possible to reduce system power consumption, therefore, in the case of too high target sampling frequency, the repetition rate of the collected voltage data will be too high, in this case, the target sampling frequency needs to be reduced; in the case of too low target sampling frequency, key voltage data is easily missed, in this case, the target sampling frequency needs to be increased.

[0101] It should be noted that the sampling redundancy index is divided into two cases if it is not within the preset threshold range, the first case is that the sampling redundancy index is higher than the upper limit of the preset threshold range, and the second case is that the sampling redundancy index is lower than the lower limit of the preset threshold range.

[0102] In this embodiment, if the sampling redundancy index does not belong to the first case within the preset threshold range, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index by using a preset first frequency correction function; if the sampling redundancy index does not belong to the second case within the preset threshold range, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index by using a preset second frequency correction function.

[0103] Since the target sampling frequency needs to be reduced if the sampling redundancy index is higher than the upper limit of the preset threshold range, in the first case, the optimal sampling frequency can be represented by the following preset first frequency correction function:

[0104]

[0105] Since the target sampling frequency needs to be increased if the sampling redundancy index is lower than the upper limit of the preset threshold range, in the second case, the optimal sampling frequency can be represented by the following preset second frequency correction function:

[0106]

[0107] wherein, f k represents the target sampling frequency of the sampling harness k; f k represents the optimal sampling frequency of the sampling harness k; f k represents the sampling redundancy index of the sampling harness k.

[0108] It should be noted that if the sampling redundancy index is within the preset threshold range, the target sampling frequency is directly used as the optimal sampling frequency.

[0109] It should be noted that the specific value range of the preset threshold range is determined according to the actual situation, and this embodiment does not make specific limitations, for example, the preset threshold range can be valued as It can be found that is At this time, the voltage data collected at the target sampling frequency, the data repetition rate will not be too high, and the key voltage data will not be missed.

[0110] It should be noted that the upper limit of the preset threshold range indicates the maximum threshold in the preset threshold range (for example, 0.3 in the preset threshold range in the embodiment). The lower limit of the preset threshold range indicates the minimum threshold in the preset threshold range (for example, 0.1 in the preset threshold range in the embodiment).

[0111] S105: Collect voltage data of all sampling beams synchronously at the optimal sampling frequency, determine the abnormal probability according to the difference between the voltage values at the same time in the voltage data of all sampling beams; if the abnormal probability exceeds the preset abnormal threshold, it is determined that the sampling beam is abnormal.

[0112] It should be noted that since each sampling beam is independently adjusted, in order to ensure the uniformity of the collected voltage data and facilitate the determination of whether the sampling beam is abnormal, the average value of the optimal sampling frequencies of all sampling beams can be taken as the uniform optimal sampling frequency for synchronous collection, to ensure synchronization.

[0113] It should be noted that the voltage data collected under each sampling beam is independent of each other, and under normal circumstances, the voltage data detected by multiple sampling beams at the same time is not much different. If the voltage data detected at the same time is significantly different, it indicates that the sampling beam has a problem.

[0114] It should be noted that in order to better analyze the difference between the voltage data detected by different sampling beams at the same time, the voltage data curves of each sampling beam can be constructed based on the collected voltage data, and then the multiple voltage data curves can be expressed in the same coordinate system, so as to quickly obtain the voltage values at the same time in the voltage data of multiple sampling beams.

[0115] It should be noted that the specific method of constructing the voltage data curve is a technology familiar to those skilled in the art, and will not be described in detail in the embodiment.

[0116] It should be noted that the voltage data curves of each sampling beam are displayed in a two-dimensional rectangular coordinate system, where the horizontal axis is time (unit: s) and the vertical axis is voltage value (unit: V). The voltage data curves of each sampling beam are distinguished by different line types and markers (for example, sampling beam 1 is represented by a solid line and sampling beam 2 is represented by a dashed line). Expressing multiple voltage data curves in the same two-dimensional rectangular coordinate system is a technology familiar to those skilled in the art, and will not be described in detail in the embodiment.

[0117] ​In the embodiment, the voltage values of the voltage data of all the sampling harnesses at the same time are arithmetically averaged to obtain a voltage reference value; and the sum of the absolute differences between the voltage values of the voltage data of all the sampling harnesses at the same time and the corresponding voltage reference values is normalized to obtain an abnormal probability.

[0118] It should be noted that, in order to avoid abnormal data interfering with the voltage reference value, the data with the largest deviation of the voltage value can be removed before the voltage reference value is calculated.

[0119] It should be noted that the corresponding relationship between the voltage value and the voltage reference value is used to indicate that the voltage value and the voltage reference value are at the same time.

[0120] It should be understood that if the voltage values of the multiple sampling harnesses at the same time are greatly different, the voltage data of the multiple sampling harnesses as a whole also have great differences, which indicates that the voltage stability of each harness is poor and the deviation degree of the overall trend is also high, and the possibility of the abnormality of the sampling harness is also large, and the abnormal probability is also large.

[0121] It should be noted that the specific value of the preset abnormal threshold is determined according to actual needs, and the embodiment does not make specific limitations, for example, the preset abnormal threshold is 0.2, which can well distinguish the abnormal problems of the sampling harness.

[0122] It should be noted that if the abnormal probability is not greater than the preset abnormal threshold, it is determined that the sampling harness does not have an abnormal problem.

[0123] An embodiment of the present application provides a sampling harness detection system of a power battery, the sampling harness detection system of the power battery comprises a memory, a processor and a computer program stored in the memory and running on the processor, and the processor implements the steps of a sampling harness detection method of a power battery when executing the computer program.

[0124] It should be noted that the above-mentioned embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or can be advantageous.

[0125] Each embodiment in the specification is described in a progressive manner, and the same and similar parts of each embodiment can be referred to each other, and each embodiment mainly describes the differences from other embodiments.

Claims

1. A method for detecting a sampling harness of a power battery, characterized in that, The method comprises: Real-time collection of voltage data sequences of each sampling beam at a preset initial sampling frequency, wherein the voltage data sequence is composed of voltage values arranged in time sequence; For each sampling beam, an instability index of the sampling beam is determined according to fluctuation amplitude characteristics and change rate characteristics of the voltage data sequence; If the instability index exceeds a preset adjustment threshold, an adjustment coefficient for adjusting the sampling frequency is determined according to the instability index and an absolute difference value between adjacent voltage values; the initial sampling frequency is adjusted to a target sampling frequency according to the adjustment coefficient and a preset upper limit value of the sampling frequency; Collection of test voltage data sequences at the target sampling frequency, and determination of a sampling redundancy index for verifying effectiveness of the target sampling frequency according to a frequency of occurrence of repeated voltage values in the test voltage data sequences; if the sampling redundancy index is not within a preset threshold range, the target sampling frequency is corrected to an optimal sampling frequency based on the sampling redundancy index; Synchronous collection of voltage data of all sampling beams at the optimal sampling frequency, and determination of an abnormality probability according to difference characteristics between voltage values at the same time in the voltage data of all sampling beams; if the abnormality probability exceeds a preset abnormality threshold, it is determined that the sampling beam is abnormal. The instability index determination process comprises: Identifying a steady-state switching turning point in the voltage data sequence, wherein the steady-state switching turning point is used to indicate a first data point from which a continuous preset number of voltage values change from satisfying a steady-state condition to not satisfying the steady-state condition; Extracting non-steady-state segment voltage data from the steady-state switching turning point to the current time from the voltage data sequence; Determining a change index of the sampling beam according to difference characteristics between voltage values in the non-steady-state segment voltage data; Obtaining a duration from the steady-state switching turning point to the current time; Normalizing the product of the voltage value of the sampling beam at the current time, the change index and the duration to obtain the instability index.

2. The method of claim 1, wherein, The change index determination process comprises: Obtaining a maximum voltage value and a minimum voltage value in the non-steady-state segment voltage data; Calculating a difference value between the maximum voltage value and the minimum voltage value as a first difference value; Calculating absolute difference values between each pair of adjacent voltage values in the non-steady-state segment voltage data as second difference values; Performing arithmetic average calculation on all second difference values to obtain a first average value; Calculating the product of the first difference value and the first average value as the change index.

3. The method of claim 1, wherein, The adjustment coefficient determination process comprises: Calculating absolute difference values of adjacent data point voltage values in the voltage data sequence as third difference values; for each third difference value, dividing the third difference value by a time interval between the corresponding adjacent data points to obtain a change rate; Performing arithmetic average calculation on all change rates to obtain an average change rate; Normalizing the product of the average change rate and the instability index to obtain the adjustment coefficient.

4. The method of claim 3, wherein, The adjustment of the initial sampling frequency to the target sampling frequency according to the adjustment coefficient and the preset upper limit value of the sampling frequency comprises: Linear interpolation calculation based on a difference value between the initial sampling frequency and the preset upper limit value of the sampling frequency through the adjustment coefficient to obtain the target sampling frequency.

5. The method of claim 1, wherein, The sampling redundancy index determination process comprises: The frequency proportion of the voltage value data points repeatedly occurring in the test voltage data sequence in all data points is calculated, and the proportion value of the voltage value sum repeatedly occurring in the test voltage data sequence in all voltage value sums is calculated; The product of the frequency proportion and the proportion value is calculated as a sampling redundancy index.

6. The method of claim 1, wherein, The method further comprises: If the sampling redundancy index is within a preset threshold range, the target sampling frequency is directly taken as the optimal sampling frequency.

7. The method of claim 1, wherein, The sampling redundancy index is not within the preset threshold range, which is divided into two cases, the first case is that the sampling redundancy index is higher than the upper limit of the preset threshold range, and the second case is that the sampling redundancy index is lower than the lower limit of the preset threshold range; If the sampling redundancy index is not within the preset threshold range, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index, which comprises: If the sampling redundancy index is not within the preset threshold range and belongs to the first case, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index by a preset first frequency correction function; If the sampling redundancy index is not within the preset threshold range and belongs to the second case, the target sampling frequency is corrected to the optimal sampling frequency based on the sampling redundancy index by a preset second frequency correction function.

8. The method of claim 1, wherein, The abnormal probability determination process comprises: The voltage values at the same time in the voltage data of all sampling harnesses are arithmetically averaged to obtain a voltage reference value; The sum of the absolute differences between the voltage values at the same time in the voltage data of all sampling harnesses and the corresponding voltage reference values is normalized to obtain the abnormal probability.

9. A sampling harness detection system for a power battery, characterized in that, The system comprises a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the method according to any one of claims 1-8 when executing the computer program.

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