New energy vehicle power battery power supply monitoring method and system

Abstract

The invention relates to the technical field of vehicle-mounted power supply monitoring, in particular to a new energy vehicle power battery power supply monitoring method and system. The method comprises the following steps: acquiring a neighborhood attenuation degree according to an electrical parameter change degree of a battery at each moment and an adjacent moment in a monitoring period and an abnormal degree of an abnormal moment; according to the difference between the similarity degree and the attenuation degree of the electrical parameter change trends of any two batteries in the monitoring period, obtaining a distance adjustment coefficient of the corresponding two batteries, adjusting the difference between the neighborhood attenuation degrees of the corresponding two batteries in the monitoring period by using the distance adjustment coefficient, and obtaining a corrected attenuation distance of the corresponding two batteries in the monitoring period; and the batteries in the battery pack are classified in the monitoring period, so that the power battery pack of the new energy vehicle is monitored. The performance difference of different batteries is accurately measured through the attenuation correction distance, the classification effect of the batteries in the battery pack is improved, and the accuracy of monitoring the power supply of the new energy vehicle power battery is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle power supply monitoring, and in particular to a method and system for monitoring power supply of a power battery of a new energy vehicle. Background Art

[0002] Common problems with power batteries for new energy vehicles are abnormal voltage of single cells, including undervoltage, overvoltage, and excessive voltage differential. Undervoltage may not provide the required voltage to the motor, resulting in insufficient power when the vehicle accelerates. Overvoltage reduces the battery's charging efficiency, causing the battery management system to frequently shut down, affecting user experience and reducing driving range. Continuous excessive voltage differential may damage the balance of the battery pack, exacerbating the overall performance degradation of the vehicle. Therefore, it is necessary to monitor the power supply of the vehicle's power battery to ensure the performance and safety of the vehicle.

[0003] The existing method divides the batteries in the battery pack into different performance categories by comparing the deviation of the electrical parameters of each single cell in the power battery pack with the mean electrical parameters of the batteries in the group; however, due to differences in the manufacturing level, usage and aging degree of different batteries in the battery pack, and the battery management system of new energy vehicles will transfer excess power from batteries with high power to batteries with low power through additional circuits, the electrical parameter differences of different batteries in the battery pack cannot accurately measure the performance differences of different batteries, which in turn causes errors in the classification of abnormal performance batteries, reducing the accuracy of power supply monitoring of new energy vehicle power batteries. Summary of the invention

[0004] In order to solve the technical problem that the difference in electrical parameters of different batteries in a battery pack cannot accurately measure the performance difference of different batteries, resulting in errors in the selection of abnormal performance batteries, the purpose of the present invention is to provide a new energy vehicle power battery power supply monitoring method and system, the technical scheme adopted is as follows: In a first aspect, an embodiment of the present invention provides a method for monitoring a power supply of a power battery of a new energy vehicle, the method comprising: Obtain the electrical parameters of each battery in the power battery pack of the new energy vehicle at each moment in the monitoring cycle; Obtaining the neighborhood attenuation of each battery at each moment in the monitoring cycle according to the degree of change of the electrical parameters of each battery at each moment in the monitoring cycle and its adjacent moments, and the degree of abnormality at the adjacent moments; According to the similarity of the electrical parameter change trends of any two batteries within the monitoring period and the difference in the attenuation degree, obtaining the distance adjustment coefficients corresponding to the two batteries; According to the distance adjustment coefficient of any two batteries, the difference between the neighborhood attenuation degrees of the corresponding two batteries within the monitoring cycle is adjusted to obtain the corrected attenuation distance between the corresponding two batteries between the monitoring cycles; based on the corrected attenuation distance, the batteries in the battery pack are classified during the monitoring cycle, and the power battery pack of the new energy vehicle is monitored.

[0005] Furthermore, the obtaining of the neighborhood attenuation of each battery at each moment in the monitoring period includes: The ratio of the difference between the electrical parameters of each battery at each moment and the next moment during the monitoring period to the time interval between the two corresponding moments is recorded as the instantaneous discharge rate at each moment; Record the instantaneous discharge rate and electrical parameters as analysis indicators, calculate the absolute value of the difference between the analysis indicator at each moment and the average value of the analysis indicator at its adjacent moments, and record the absolute values ​​of the difference corresponding to the instantaneous discharge rate and electrical parameters as the adjacent rate difference and adjacent parameter difference at each moment in turn; and take the ratio of the adjacent parameter difference, the adjacent rate difference and the sum of a preset positive number at each moment of each battery within the monitoring period as the attenuation indicator; The abnormal moment is selected based on the electrical parameters; and the neighborhood attenuation degree of each battery at each moment in the monitoring period is obtained according to the number of abnormal moments in the neighborhood of each moment and the attenuation index.

[0006] Furthermore, the method for obtaining the distance adjustment coefficient includes: Calculate the cumulative sum of the absolute values ​​of the differences in the neighborhood attenuation degrees of any two batteries at the same position during the monitoring period as the overall attenuation difference of the corresponding two batteries during the monitoring period; Arrange the electrical parameters of each battery at all times during the monitoring period in time sequence to obtain an electrical parameter sequence; According to the DTW values ​​of the electrical parameter sequences of any two batteries and the overall attenuation difference, the distance adjustment coefficients of the corresponding two batteries in the monitoring period are obtained, and the DTW value and the overall attenuation difference are both positively correlated with the distance adjustment coefficient.

[0007] Furthermore, the method for obtaining the corrected attenuation distance includes: Based on the difference between the neighborhood attenuation degrees of any two batteries within a monitoring period, obtaining the attenuation distance between the corresponding two batteries between the monitoring periods; Any battery is selected as a sample battery, and any battery in the k-neighborhood of the sample battery is selected as an analysis battery. The absolute value of the difference between the distance adjustment coefficient between the sample battery and the analysis battery and the mean of the distance adjustment coefficient between the sample battery and all the batteries in its k-neighborhood are used as the numerator, and the mean of the distance adjustment coefficient between the sample battery and all the batteries in its k-neighborhood are used as the denominator to obtain the ratio, and the abnormality of the sample battery and the analysis battery is obtained; Determine whether the abnormality of the example battery and the analysis battery is greater than the preset abnormality threshold. If so, use the sum of the abnormality and constant 1 to weight the attenuation distance between the example battery and the analysis battery between the monitoring cycles to obtain a corrected attenuation distance; if not, use the attenuation distance between the example battery and the analysis battery between the monitoring cycles as the corrected attenuation distance.

[0008] Furthermore, the classifying of batteries in the battery pack during the monitoring period based on the corrected attenuation distance includes: Based on the attenuation distance between any two batteries during the monitoring cycle, all batteries in the battery pack are clustered during the monitoring cycle to obtain two clusters; the batteries in the cluster with the largest number of batteries are recorded as suspected normal batteries, and the batteries in the other cluster are recorded as suspected abnormal batteries; Select the k batteries corresponding to the largest corrected attenuation distances from the example battery and the remaining batteries during the monitoring period, and count the total number of suspected normal batteries and the total number of suspected abnormal batteries; if the total number of suspected normal batteries is the largest, the example battery is a normal battery during the monitoring period; if the total number of suspected abnormal batteries is the largest, the example battery is an abnormal battery during the monitoring period.

[0009] Furthermore, the attenuation distance between the two batteries during the monitoring period is the absolute value of the difference between the neighborhood attenuation mean values ​​of the two batteries at all times during the monitoring period.

[0010] Furthermore, the number of abnormal moments in the neighboring moments of each moment and the attenuation index are both positively correlated with the neighborhood attenuation degree.

[0011] Furthermore, the electrical parameters at the abnormal moment exceed a preset standard range.

[0012] Furthermore, the method for clustering all batteries in the battery pack during the monitoring period is a K-means clustering algorithm.

[0013] In a second aspect, another embodiment of the present invention provides a new energy vehicle power battery power monitoring system, the system comprising: A data acquisition module is used to obtain the electrical parameters of each battery in the power battery pack of the new energy vehicle at each moment in the monitoring cycle; An attenuation analysis module, used to obtain the neighborhood attenuation degree of each battery at each moment in the monitoring cycle according to the degree of change of the electrical parameters of each battery at each moment in the monitoring cycle and its adjacent moments, and the degree of abnormality of the adjacent moments; A distance adjustment analysis module, used to obtain the distance adjustment coefficients of the corresponding two batteries according to the similarity of the electrical parameter change trends of any two batteries within a monitoring period and the difference in the attenuation degree; The battery classification module is used to adjust the difference between the neighborhood attenuation degrees of the corresponding two batteries during the monitoring period according to the distance adjustment coefficient of any two batteries, and obtain the corrected attenuation distance between the corresponding two batteries during the monitoring period; classify the batteries in the battery pack during the monitoring period based on the corrected attenuation distance, and monitor the power battery pack of the new energy vehicle.

[0014] The present invention has the following beneficial effects: First, considering the differences in manufacturing levels, usage and aging of different batteries, the analysis of battery performance differences based on the differences in electrical parameters of different batteries in the battery pack has little reference value for battery performance classification. This solution is based on the fact that the electrical parameters of the battery will show a downward trend as the power is consumed during vehicle driving. The neighborhood attenuation is obtained by comparing the degree of change in the electrical parameters of the battery at each moment in the monitoring cycle with its adjacent moments and the degree of abnormality at the adjacent moments, thus presenting the performance status of the battery at a local time.

[0015] The second aspect: Considering that the battery management system of new energy vehicles will perform power balancing adjustments during vehicle driving to weaken the battery electrical parameter attenuation trend, the performance degradation of the two batteries is analyzed according to the consistency of the voltage attenuation trends of the two batteries during the monitoring period, and the difference in the attenuation trends of the two batteries is adjusted to obtain the distance adjustment coefficient. The similarity of the electrical parameter change trends of the two batteries during the monitoring period and the difference in attenuation are analyzed from the overall and local perspectives to analyze the consistency of the electrical parameter attenuation trends of the corresponding batteries during the monitoring period. Comprehensive analysis can improve the accuracy of the analysis of the consistency of the electrical parameter attenuation trends of the two batteries.

[0016] The third aspect: the difference between the attenuation degrees of different batteries in the neighborhood during the monitoring period measures the attenuation distance between different batteries; by correcting the attenuation distance to classify the batteries in the battery pack during the monitoring period, it is possible to dynamically remove the interference of the battery management system's power balancing management on the attenuation trend of the electrical parameters, quantify the actual performance differences between batteries, classify the batteries more accurately, and improve the accuracy of power supply monitoring of new energy vehicles' power batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flowchart of a method for monitoring a power battery of a new energy vehicle provided by an embodiment of the present invention; Figure 2 A system structure diagram of a power battery power monitoring system for a new energy vehicle provided by an embodiment of the present invention; Figure 3 A schematic diagram of a computer device of a new energy vehicle power battery power monitoring device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a new energy vehicle power battery power monitoring method and system proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0020] Unless defined otherwise, 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 invention belongs.

[0021] The specific scheme of a power battery power monitoring method and system for new energy vehicles provided by the present invention is described in detail below with reference to the accompanying drawings.

[0022] Embodiment 1: The present invention proposes a method for monitoring the power supply of a power battery of a new energy vehicle. Figure 1 , which shows a flow chart of steps of a method for monitoring a power battery power supply of a new energy vehicle provided by an embodiment of the present invention, the method comprising: Step S1: Obtain the electrical parameters of each battery in the power battery pack of the new energy vehicle at each moment in the monitoring cycle.

[0023] An electrical sensor is installed on each battery in the power battery pack of a new energy vehicle. During the driving of the vehicle, the voltage of each battery in the battery pack at each moment in the monitoring cycle is collected by the electrical sensor and recorded as electrical parameters. The electrical parameters of the battery pack are transmitted to the cloud platform using a data transmission device connected to the electrical sensor, thereby monitoring the power supply of the vehicle's power battery.

[0024] In an implementation of the embodiment of the present invention, the data collection frequency of the electrical sensor is set to once every 5 seconds; and the duration of the monitoring cycle is set to 10 minutes.

[0025] It should be noted that the data collection frequency of the electrical sensors on all batteries in the battery pack is equal.

[0026] Step S2: Obtain the neighborhood attenuation of each battery at each moment in the monitoring cycle according to the degree of change of the electrical parameters of each battery at each moment in the monitoring cycle and its adjacent moments, and the degree of abnormality at the adjacent moments.

[0027] Because the manufacturing level, usage and aging of different batteries in a battery pack are different, the power of the batteries in the battery pack may be inconsistent, and the battery may amplify the power difference of the batteries in the battery pack after multiple charge and discharge cycles, long-term use, overcharge, over-discharge, etc. The battery voltage can be used to judge its power status. From the perspective of battery life, the performance of the battery will decline after a normal charge and discharge cycle, but the performance change of the battery will be significantly different after overcharge and over-discharge. Therefore, the analysis of battery performance differences based on the differences in electrical parameters of different batteries in a battery pack has little reference value for battery performance classification.

[0028] During the driving process of new energy vehicles, the battery is mainly in a discharge state. The battery voltage will show a downward trend as the power is consumed, and the battery performance degradation will cause the voltage to drop more sharply. The overall change trend of the battery voltage data is mainly affected by the battery performance degradation, and the local changes are affected by external factors of the battery such as the environment and user driving behavior. The degree of change of the electrical parameters at each moment and its adjacent moments can reflect the intensity of the battery voltage change in the local time. The voltage change intensity shows the degree of voltage attenuation in the neighborhood period of each moment. The abnormal degree of the battery at the adjacent moments of each moment indicates the degree of performance degradation of the battery at that moment; the above two factors are combined to analyze the battery voltage attenuation at each moment, and the neighborhood attenuation degree is obtained. The neighborhood attenuation degree shows the battery performance status of the battery at the local time.

[0029] In an implementation of the embodiment of the present invention, four moments that are adjacent to each moment respectively before and after each moment are recorded as adjacent moments of each moment.

[0030] Step S3: Obtain the distance adjustment coefficient for any two batteries according to the similarity of the change trends of the electrical parameters of the two batteries during the monitoring period and the difference in the attenuation degrees.

[0031] The battery management system of new energy vehicles will transfer the excess power from the battery with high power to the battery with low power through additional circuits such as battery swapping and energy transfer, etc., to improve the battery discharge efficiency and extend the battery life. However, the equalization adjustment of the battery power will weaken the power attenuation trend of a single battery, making the power difference caused by factors such as multiple charge and discharge cycles of the battery weaken. Therefore, the battery with an obvious voltage attenuation trend has a more accurate judgment performance, while the battery with an unobvious voltage attenuation trend has a larger error in judgment performance and needs further analysis.

[0032] Different batteries are regulated by the battery management system to different degrees, resulting in different voltage attenuation trends of different batteries during the monitoring period; if the voltage attenuation trends of two batteries are more inconsistent during the monitoring period, it indicates that there is an obvious attenuation trend difference between the two batteries after being regulated by the battery management system, and the difference in the performance degradation of the two batteries is more obvious, then the possibility of abnormal conditions occurring in the two batteries is greater. In order to improve the accuracy of battery performance classification, the difference in the attenuation trends of the two batteries, that is, the distance between the two batteries, should be increased. The similarity of the change trends of the electrical parameters of the two batteries and the difference in the attenuation degrees during the monitoring period are used to analyze the consistency of the voltage attenuation trends of the corresponding batteries from the overall and local perspectives in turn, so as to determine the adjustment of the distance between the two batteries and obtain the distance adjustment coefficient.

[0033] Step S4: Adjust the difference between the neighborhood attenuation degrees of any two batteries during the monitoring period according to the distance adjustment coefficient of the two batteries, and obtain the corrected attenuation distance between the two batteries during the monitoring period; classify the batteries in the battery pack during the monitoring period based on the corrected attenuation distance, and monitor the power battery pack of the new energy vehicle.

[0034] The neighborhood attenuation degree presents the battery performance status of the battery at a local time. The difference between the neighborhood attenuation degrees of different batteries in the monitoring cycle measures the attenuation distance between different batteries. By correcting the attenuation distance to classify the batteries in the battery pack during the monitoring cycle, it is possible to dynamically remove the interference of the battery management system's power balancing management on the electrical parameter attenuation trend, quantify the real performance difference between batteries, and classify the batteries more accurately to obtain abnormal performance batteries, that is, batteries with more significant electrical parameter attenuation, and normal performance batteries, that is, batteries with weak electrical parameter attenuation, to ensure the safety and reliability of new energy vehicles during use. Afterwards, the classified batteries are used to timely warn of abnormal conditions of the power battery pack of new energy vehicles during the monitoring cycle, and complete the real-time monitoring of the power supply operation status of the power battery of new energy vehicles. Among them, the warning method of the power battery pack of new energy vehicles is the same in all monitoring cycles.

[0035] Preferably, in some possible implementation modes of the embodiments of the present invention, the method for obtaining the neighborhood attenuation degree includes: recording the ratio of the difference in electrical parameters of each battery at each moment in the monitoring period and its next adjacent moment to the time interval between the corresponding two moments as the instantaneous discharge rate at each moment; recording the instantaneous discharge rate and electrical parameters as analysis indicators, calculating the absolute value of the difference between the analysis indicator at each moment and the average of the analysis indicator at its adjacent moments, and recording the absolute values ​​of the corresponding differences in the instantaneous discharge rate and electrical parameters as the adjacent rate difference and adjacent parameter difference at each moment respectively; taking the ratio of the adjacent parameter difference, the adjacent rate difference and the sum of a preset positive number of each battery at each moment in the monitoring period as the attenuation indicator; selecting abnormal moments based on electrical parameters; and obtaining the neighborhood attenuation degree of each battery at each moment in the monitoring period according to the number of abnormal moments in the adjacent moments of each moment and the attenuation indicator.

[0036] It should be noted that the instantaneous discharge rate can quantify the voltage change intensity of the battery per unit time and present the real-time status of the battery performance; the adjacent rate difference and the adjacent parameter difference can be regarded as the average of the absolute values ​​of the difference between the instantaneous discharge rate and the electrical parameters at each moment and all its adjacent moments, respectively. The ratio of the adjacent parameter difference, the adjacent rate difference and the sum of the preset positive numbers at each moment can measure the voltage change intensity of the battery at a unit discharge rate. The larger the ratio, that is, the attenuation index, the higher the degree of attenuation of the battery performance in the neighborhood period of each moment, and the greater the neighborhood attenuation. Among them, the role of the preset positive number is to prevent the denominator from being zero, which makes the ratio meaningless. In this embodiment, the preset positive number is set to 0.01, and the implementer can set it according to the specific situation. Battery performance degradation will cause the vehicle battery voltage to exceed the standard range for a longer period of time, and its impact is continuous and irreversible, while voltage anomalies caused by external battery factors such as the environment and driving behavior are mostly short-term or intermittent phenomena; the number of abnormal moments in the neighborhood of each moment reflects the degree of abnormality in the neighborhood of that moment. The more abnormal moments there are, the greater the degree of abnormality, the more serious the battery performance degradation at that moment, and the greater the neighborhood attenuation. Therefore, the number of abnormal moments in the neighborhood of each moment and the attenuation index are positively correlated with the neighborhood attenuation.

[0037] In the embodiment of the present invention, the product of the number of abnormal moments in the neighboring moments of each moment in the monitoring cycle of each battery and the attenuation index is normalized to obtain the neighborhood attenuation degree of each moment. It should be noted that in the embodiment of the present invention, the maximum and minimum normalization is used for normalization, and a normalization method such as function conversion and Norm function can also be selected.

[0038] In one implementation of the embodiment of the present invention, the abnormal moment is the moment when the electrical parameter exceeds the preset standard range. The preset standard range is the standard voltage range of the battery in the battery pack, which is obtained from the manual of the new energy vehicle. For example, if the standard voltage range of the power battery of Geely Emgrand EV450 is between 11 volts and 14 volts, the preset standard range of the battery is between 11 volts and 14 volts.

[0039] In another embodiment of the present invention, the electrical parameters of each battery at all times in the monitoring period are curve fitted to obtain a fitting curve, and the slope of the corresponding position on the fitting curve at each moment is used as the instantaneous discharge rate at each moment.

[0040] It should be noted that the instantaneous discharge rate of each battery in the last two moments of the monitoring cycle is the same; in the process of calculating the instantaneous discharge rate, the difference in electrical parameters between each moment and its next adjacent moment is equal to the absolute value of the difference in electrical parameters between the corresponding two moments.

[0041] Preferably, in some possible implementation manners of the embodiments of the present invention, the method for obtaining the distance adjustment coefficient includes: calculating the sum of the absolute values of the differences in the neighborhood attenuation degrees at the same position of any two batteries at the moments within the monitoring period as the overall attenuation difference between the corresponding two batteries within the monitoring period; arranging the electrical parameters of each battery at all moments within the monitoring period in chronological order to obtain an electrical parameter sequence; and obtaining the distance adjustment coefficient between the corresponding two batteries within the monitoring period according to the DTW value and the overall attenuation difference of the electrical parameter sequences of any two batteries. It should be noted that the moments at the same position of any two batteries within the monitoring period are respectively at the same positions within the corresponding monitoring period. The DTW value and the overall attenuation degree of the electrical parameter sequences of any two batteries analyze the consistency of the voltage attenuation trends of the two batteries within the monitoring period from the overall and local perspectives respectively. If both the DTW value and the overall attenuation degree are larger, it indicates that the voltage attenuation trends of the two batteries within the monitoring period are more inconsistent, and the possibility of abnormal conditions occurring in the two batteries is greater. It is necessary to increase the difference in the voltage attenuation trends of the two batteries to improve the accuracy of battery performance classification, so the distance adjustment coefficient is larger. Therefore, both the DTW value and the overall attenuation difference are positively correlated with the distance adjustment coefficient.

[0042] In the embodiments of the present invention, the product of the DTW value and the overall attenuation difference of the electrical parameter sequences of any two batteries within the monitoring period is normalized to obtain the distance adjustment coefficient between the corresponding two batteries within the monitoring period. It should be noted that in the embodiments of the present invention, the Norm function is used for normalization, and normalization methods such as function transformation and maximum-minimum normalization can also be selected.

[0043] Preferably, in some possible implementation manners of the embodiments of the present invention, the method for obtaining the corrected attenuation distance includes: obtaining the attenuation distance between the corresponding two batteries within the monitoring period based on the difference in the neighborhood attenuation degrees between any two batteries within the monitoring period; arbitrarily selecting one battery as the example battery, and arbitrarily selecting one battery from the k-neighborhood of the example battery as the analysis battery, and normalizing the ratio with the absolute value of the difference between the distance adjustment coefficient between the example battery and the analysis battery and the average value of the distance adjustment coefficients between the example battery and all batteries within its k-neighborhood as the numerator and the average value of the distance adjustment coefficients between the example battery and all batteries within its k-neighborhood as the denominator to obtain the abnormality degree between the example battery and the analysis battery; determining whether the abnormality degree between the example battery and the analysis battery is greater than a preset abnormality threshold. If so, weighting the attenuation distance between the example battery and the analysis battery within the monitoring period with the sum of the abnormality degree and the constant 1 to obtain the corrected attenuation distance; if not, using the attenuation distance between the example battery and the analysis battery within the monitoring period as the corrected attenuation distance.

[0044] It should be noted that the batteries within the k-neighborhood of the sample battery are the batteries corresponding to the k largest attenuation distances among the attenuation distances between the sample battery and all the other batteries during the monitoring period. Since the average neighborhood attenuation degree of the battery at all times during the monitoring period presents the overall performance status of the battery during the monitoring period, the absolute value of the difference between the average neighborhood attenuation degrees of two batteries at all times during the monitoring period is used as the attenuation distance between the two batteries during the monitoring period. The abnormality degree between the sample battery and the analysis battery measures the deviation degree of the distance adjustment coefficient between the sample battery and the analysis battery relative to the overall level of the distance adjustment coefficient between the sample battery and the batteries within its k-neighborhood. If the abnormality degree is larger, it indicates that the distance adjustment coefficient between the sample battery and the analysis battery is more inconsistent with the above overall level, and the greater the possibility that the voltage attenuation trends of the sample battery and the analysis battery are abnormal. In this embodiment, it is considered that the abnormality degree greater than the preset abnormality threshold corresponds to the abnormal voltage attenuation trends of the two batteries, and then it is necessary to increase the attenuation distance between the two batteries corresponding to the abnormality degree greater than the preset abnormality threshold. The larger the obtained corrected attenuation distance is. In the embodiment of the present invention, the Norm function is used for normalization processing, and other normalization methods can also be selected, which are not limited herein.

[0045] In an implementation manner of the embodiment of the present invention, k is set to 21.

[0046] In an implementation manner of the embodiment of the present invention, the K-means clustering algorithm is selected to cluster all the batteries in the battery pack during the monitoring period, where K is equal to 2.

[0047] In an implementation manner of the embodiment of the present invention, the preset abnormality threshold is set to 0.92.

[0048] It should be noted that the method for obtaining the corrected attenuation distance between every two batteries in the battery pack during the monitoring period is the same as the method for obtaining the corrected attenuation distance between the sample battery and the analysis battery during the monitoring period.

[0049] Preferably, in some possible implementations of the embodiments of the present invention, the battery classification method includes: based on the attenuation distance between any two batteries in the monitoring cycle, clustering all batteries in the battery pack in the monitoring cycle to obtain two cluster clusters; recording the batteries in the cluster with the largest number of batteries in the cluster as suspected normal batteries, and recording the batteries in the other cluster cluster as suspected abnormal batteries; selecting the largest k corrected attenuation distance corresponding batteries from the corrected attenuation distances between the example battery and the remaining batteries in the monitoring cycle, and counting the total number of suspected normal batteries and the total number of suspected abnormal batteries; if the total number of suspected normal batteries is the largest, the example battery is a normal battery in the monitoring cycle; if the total number of suspected abnormal batteries is the largest, the example battery is an abnormal battery in the monitoring cycle. It should be noted that in actual situations, the performance of most batteries in the driving process of new energy vehicles is normal, and the performance of some batteries is abnormal. Batteries with suspected normal and abnormal performance can be preliminarily divided based on the number of batteries in the cluster. Based on the corrected attenuation distances between the example battery and the remaining batteries, the batteries in the k neighborhood of the example battery are re-determined, and the k nearest neighbor classification algorithm is used to finally determine whether the example battery is an abnormal battery or a normal battery.

[0050] Preferably, in some possible implementations of the embodiments of the present invention, the method for monitoring the power battery pack of a new energy vehicle includes: recording the proportion of abnormal batteries in the battery pack during the monitoring period as the power abnormality; judging whether the power abnormality is greater than a preset power abnormality threshold, if so, the battery power of the new energy vehicle during the monitoring period is abnormal, otherwise, the battery power of the new energy vehicle during the monitoring period is normal. It should be noted that the greater the number of abnormal batteries in the battery pack, the greater the possibility that the new energy vehicle will have battery power abnormality during the monitoring period, and the greater the power abnormality, the battery power condition of the new energy vehicle during the monitoring period is determined by the power abnormality and the preset power abnormality threshold.

[0051] In an implementation of the embodiment of the present invention, the preset power supply abnormality threshold is set to 0.3.

[0052] So far, the present invention is completed.

[0053] Embodiment 2: The present invention proposes a new energy vehicle power battery power monitoring system, please refer to Figure 2 , which shows a system structure diagram of a new energy vehicle power battery power monitoring system provided by an embodiment of the present invention, the system comprising: The data acquisition module 510 is used for the data acquisition module to obtain the electrical parameters of each battery in the power battery pack of the new energy vehicle at each moment in the monitoring cycle; The attenuation analysis module 520 is used to obtain the neighborhood attenuation degree of each battery at each moment in the monitoring cycle according to the degree of change of the electrical parameters of each battery at each moment in the monitoring cycle and its adjacent moments, as well as the degree of abnormality at the adjacent moments; The distance adjustment analysis module 530 is used to obtain the distance adjustment coefficients of the corresponding two batteries according to the similarity of the electrical parameter change trends of any two batteries within the monitoring period and the difference in attenuation; The battery classification module 540 is used to adjust the difference between the neighborhood attenuation degrees of the corresponding two batteries within the monitoring period according to the distance adjustment coefficient of any two batteries, and obtain the corrected attenuation distance between the corresponding two batteries during the monitoring period; classify the batteries in the battery pack during the monitoring period based on the corrected attenuation distance, and monitor the power battery pack of the new energy vehicle.

[0054] It should be noted that the device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, the new energy vehicle power battery power monitoring system and the new energy vehicle power battery power monitoring method embodiment provided in the above embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0055] Embodiment 3: Figure 3 A schematic diagram of a computer device for monitoring a power battery power supply of a new energy vehicle provided by an embodiment of the present invention. For example, Figure 3 As shown, the computer device includes: a memory 601, a processor 602, and a computer program 603 stored in the memory 601 and running on the processor 602, wherein when the processor 602 executes the computer program 603, the computer device can execute any one of the new energy vehicle power battery power monitoring methods introduced above.

[0056] In addition, an embodiment of the present application also protects a device, which may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to execute a new energy vehicle power battery power monitoring method provided in an embodiment of the present application.

[0057] In this embodiment, the functional modules of the device can be divided according to the above method example. For example, each functional module can be corresponded, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0058] It should be understood that the device provided in this embodiment is used to execute the above-mentioned method for monitoring the power supply of a power battery of a new energy vehicle, and thus can achieve the same effect as the above-mentioned implementation method.

[0059] In the case of an integrated unit, the device may include a processing module and a storage module. When the device is applied to a device, the processing module may be used to control and manage the actions of the device. The storage module may be used to support the device to execute mutual program codes, etc.

[0060] The processing module may be a processor or a controller, which may implement or execute various exemplary logic blocks, modules and circuits included in the disclosure of this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module may be a memory.

[0061] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying 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 also possible or may be advantageous.

[0062] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0063] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for monitoring power supply of a power battery of a new energy vehicle, characterized in that: The method includes: Obtain the electrical parameters of each battery in the power battery pack of the new energy vehicle at each moment in the monitoring cycle; Obtaining the neighborhood attenuation of each battery at each moment in the monitoring cycle according to the degree of change of the electrical parameters of each battery at each moment in the monitoring cycle and its adjacent moments, and the degree of abnormality at the adjacent moments; According to the similarity of the electrical parameter change trends of any two batteries within the monitoring period and the difference in the attenuation degree, obtaining the distance adjustment coefficients corresponding to the two batteries; According to the distance adjustment coefficient of any two batteries, the difference between the neighborhood attenuation degrees of the corresponding two batteries within the monitoring cycle is adjusted to obtain the corrected attenuation distance between the corresponding two batteries between the monitoring cycles; based on the corrected attenuation distance, the batteries in the battery pack are classified during the monitoring cycle, and the power battery pack of the new energy vehicle is monitored.

2. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 1, characterized in that: The obtaining of the neighborhood attenuation of each battery at each moment in the monitoring period includes: The ratio of the difference between the electrical parameters of each battery at each moment and the next adjacent moment in the monitoring cycle to the time interval between the two corresponding moments is recorded as the instantaneous discharge rate at each moment; Record the instantaneous discharge rate and electrical parameters as analysis indicators, calculate the absolute value of the difference between the analysis indicator at each moment and the average value of the analysis indicator at its adjacent moments, and record the absolute values ​​of the difference corresponding to the instantaneous discharge rate and electrical parameters as the adjacent rate difference and adjacent parameter difference at each moment in turn; and take the ratio of the adjacent parameter difference, the adjacent rate difference and the sum of a preset positive number at each moment of each battery within the monitoring period as the attenuation indicator; The abnormal moment is selected based on the electrical parameters; and the neighborhood attenuation degree of each battery at each moment in the monitoring period is obtained according to the number of abnormal moments in the neighborhood of each moment and the attenuation index.

3. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 1, characterized in that: The method for obtaining the distance adjustment coefficient includes: Calculate the cumulative sum of the absolute values ​​of the differences in the neighborhood attenuation degrees of any two batteries at the same position during the monitoring period as the overall attenuation difference of the corresponding two batteries during the monitoring period; Arrange the electrical parameters of each battery at all times during the monitoring period in time sequence to obtain an electrical parameter sequence; According to the DTW values ​​of the electrical parameter sequences of any two batteries and the overall attenuation difference, the distance adjustment coefficients of the corresponding two batteries in the monitoring period are obtained, and the DTW value and the overall attenuation difference are both positively correlated with the distance adjustment coefficient.

4. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 1, characterized in that: The method for obtaining the corrected attenuation distance includes: Based on the difference between the neighborhood attenuation degrees of any two batteries within a monitoring period, obtaining the attenuation distance between the corresponding two batteries between the monitoring periods; Any battery is selected as a sample battery, and any battery in the k-neighborhood of the sample battery is selected as an analysis battery. The absolute value of the difference between the distance adjustment coefficient between the sample battery and the analysis battery and the mean of the distance adjustment coefficient between the sample battery and all the batteries in its k-neighborhood are used as the numerator, and the mean of the distance adjustment coefficient between the sample battery and all the batteries in its k-neighborhood are used as the denominator to obtain the ratio, and the abnormality of the sample battery and the analysis battery is obtained; Determine whether the abnormality of the example battery and the analysis battery is greater than the preset abnormality threshold. If so, use the sum of the abnormality and constant 1 to weight the attenuation distance between the example battery and the analysis battery between the monitoring cycles to obtain a corrected attenuation distance; if not, use the attenuation distance between the example battery and the analysis battery between the monitoring cycles as the corrected attenuation distance.

5. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 4, characterized in that: The classifying the batteries in the battery pack during the monitoring period based on the corrected attenuation distance includes: Based on the attenuation distance between any two batteries during the monitoring cycle, all batteries in the battery pack are clustered during the monitoring cycle to obtain two clusters; the batteries in the cluster with the largest number of batteries are recorded as suspected normal batteries, and the batteries in the other cluster are recorded as suspected abnormal batteries; Select the k batteries corresponding to the largest corrected attenuation distances from the example battery and the remaining batteries during the monitoring period, and count the total number of suspected normal batteries and the total number of suspected abnormal batteries; if the total number of suspected normal batteries is the largest, the example battery is a normal battery during the monitoring period; if the total number of suspected abnormal batteries is the largest, the example battery is an abnormal battery during the monitoring period.

6. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 4, characterized in that: The attenuation distance between the two batteries during the monitoring period is the absolute value of the difference between the neighborhood attenuation mean values ​​of the two batteries at all times during the monitoring period.

7. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 2, characterized in that: The number of abnormal moments in the adjacent moments of each moment and the attenuation index are both positively correlated with the neighborhood attenuation degree.

8. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 2, characterized in that: The electrical parameters at the abnormal moment exceed the preset standard range.

9. A method for monitoring power supply of a power battery of a new energy vehicle according to claim 5, characterized in that: The method for clustering all batteries in the battery pack during the monitoring period is a K-means clustering algorithm.

10. A new energy vehicle power battery power monitoring system, characterized in that: The system includes: A data acquisition module is used to obtain the electrical parameters of each battery in the power battery pack of the new energy vehicle at each moment in the monitoring cycle; An attenuation analysis module, used to obtain the neighborhood attenuation degree of each battery at each moment in the monitoring cycle according to the degree of change of the electrical parameters of each battery at each moment in the monitoring cycle and its adjacent moments, and the degree of abnormality of the adjacent moments; A distance adjustment analysis module, used to obtain the distance adjustment coefficients of the corresponding two batteries according to the similarity of the electrical parameter change trends of any two batteries within a monitoring period and the difference in the attenuation degree; The battery classification module is used to adjust the difference between the neighborhood attenuation degrees of the corresponding two batteries during the monitoring period according to the distance adjustment coefficient of any two batteries, and obtain the corrected attenuation distance between the corresponding two batteries during the monitoring period; classify the batteries in the battery pack during the monitoring period based on the corrected attenuation distance, and monitor the power battery pack of the new energy vehicle.

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