CN117706387B

CN117706387B - Battery health state monitoring method and device, electronic equipment and medium

Info

Publication number: CN117706387B
Application number: CN202311731064.4A
Authority: CN
Inventors: 李文利; 鞠昌斌; 蒋仁龙; 童伟杨; 薛宏升; 黎耀鹏; 伍尚剑; 王帅
Original assignee: Foshan Shugang Technology Co ltd
Current assignee: Foshan Shugang Technology Co ltd
Priority date: 2023-12-15
Filing date: 2023-12-15
Publication date: 2024-08-09
Anticipated expiration: 2043-12-15
Also published as: CN117706387A

Abstract

The application relates to the technical field of data processing, and provides a battery health state monitoring method, a device, electronic equipment and a medium, wherein the method comprises the following steps: determining a discharge voltage curve and a historical internal resistance curve of a target lead-acid storage battery; detecting abnormal discharge voltage of the target lead-acid storage battery based on the discharge voltage curve to obtain a first monitoring result; detecting abnormal internal resistance of the target lead-acid storage battery based on the historical internal resistance curve to obtain a second monitoring result; determining a target monitoring result of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result; and if the target monitoring result is that the target lead-acid storage battery is abnormal, determining an abnormal alarm level of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result. According to the application, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional detection mode combining the abnormal factors of the battery.

Description

Battery health state monitoring method and device, electronic equipment and medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method and apparatus for monitoring a battery health status, an electronic device, and a medium.

Background

A data center is a facility that centrally stores, manages, and processes large amounts of data. It is typically made up of a large number of servers, network devices, storage devices, and other related devices. Data centers are used to support the information technology requirements of large-scale organizations such as businesses, internet service providers, etc., for example, storing and processing large amounts of data, providing web services, running applications, and supporting business such as electronic commerce.

The storage battery plays a very important role in an uninterruptible power supply (Uninterruptible Power Supply, UPS) power supply system of a data center, and is a guarantee for the operation of the whole system when power supply fails. In the failure related to the UPS power supply system of the data center, the cause related to the battery accounts for more than thirty percent. Therefore, a reasonable and effective storage battery monitoring system has very important practical significance. At present, the main stream storage battery type of the data center in the market is a lead-acid storage battery, and compared with other types of storage batteries, the lead-acid storage battery has the advantages of stable performance and high technical maturity. The state of health of the lead-acid battery is relevant for reliable operation of the UPS power supply system. In actual use, the lead-acid storage battery has the conditions of capacity attenuation, internal resistance increase, residual life reduction, open circuit of the storage battery, short circuit fault and the like, the storage batteries generally operate in a series connection mode, if any storage battery fails, the power supply continuity of the UPS power supply system is directly determined, any storage battery is degraded to cause the accelerated degradation of other storage batteries, thus the whole storage battery is scrapped, and any storage battery is opened to cause the voltage loss of the bus of the whole storage battery. Often resulting in failure of the UPS's power supply to provide stable power or complete failure of the UPS's power supply, thereby affecting the stability and reliability of the data center power supply system.

The current method for evaluating the state of health of the lead-acid storage battery in the data center is to detect the internal resistance of the lead-acid storage battery periodically (generally once a week), and judge that the lead-acid storage battery is in an unhealthy state when the ohmic resistance of the internal resistance exceeds a certain threshold value. However, the state of health of the storage battery cannot be accurately judged only by the ohmic resistance of the internal resistance of the lead-acid storage battery.

Disclosure of Invention

The present application is directed to solving at least one of the technical problems existing in the related art. Therefore, the application provides a battery health state monitoring method which can accurately judge the health state of the storage battery.

The application also provides a battery health state monitoring device, electronic equipment and a medium.

According to an embodiment of the first aspect of the application, a battery health status monitoring method includes:

Determining a discharge voltage curve and a historical internal resistance curve of a target lead-acid storage battery;

Detecting abnormal discharge voltage of the target lead-acid storage battery based on the discharge voltage curve to obtain a first monitoring result;

Detecting abnormal internal resistance of the target lead-acid storage battery based on the historical internal resistance curve to obtain a second monitoring result;

Determining a target monitoring result of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result;

And if the target monitoring result is that the target lead-acid storage battery is abnormal, determining an abnormal alarm level of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result.

According to the battery health state monitoring method provided by the embodiment of the application, through determining the discharge voltage curve and the historical internal resistance curve of the target lead-acid storage battery, abnormal discharge voltage detection can be carried out on the target lead-acid storage battery according to the discharge voltage curve, abnormal internal resistance detection can be carried out on the target lead-acid storage battery according to the historical internal resistance curve, finally, whether the target lead-acid storage battery is abnormal or not can be accurately determined according to the detection result of the discharge voltage and/or the internal resistance detection result, and when the target monitoring result is abnormal, the abnormal alarm grade of the battery is determined according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

According to an embodiment of the present application, the detecting the abnormal discharge voltage of the target lead-acid storage battery based on the discharge voltage curve, to obtain a first monitoring result, includes:

determining a first upper boundary and a first lower boundary of the discharge voltage curve respectively, and if any data in the discharge voltage curve is located outside the first upper boundary and the first lower boundary, determining that the discharge curve of the target lead-acid storage battery is abnormal;

Determining a voltage threshold, and if any data in the discharge voltage curve is smaller than or equal to the voltage threshold, determining that the target lead-acid storage battery has voltage abnormality; the voltage threshold at least comprises a preset voltage threshold and a dynamic voltage threshold; the dynamic voltage threshold is determined according to the voltage average value of the target lead-acid storage battery and the lead-acid storage batteries in the same group and a preset voltage weight.

According to one embodiment of the present application, the determining the first upper boundary and the first lower boundary of the discharge voltage curve respectively includes:

respectively determining an upper quartile and a lower quartile of data in the discharge voltage curve;

Determining a quartile distance based on the upper quartile and the lower quartile;

determining a first upper boundary of the discharge voltage curve based on the quartile distance and the upper quartile;

a first lower boundary of the discharge voltage curve is determined based on the quartile distance and the lower quartile.

According to an embodiment of the present application, the detecting abnormal internal resistance of the target lead-acid storage battery based on the historical internal resistance curve, to obtain a second monitoring result, includes:

Determining a second upper boundary and a second lower boundary of the historical internal resistance curve respectively, and if any data in the historical internal resistance curve is located outside the second upper boundary and the second lower boundary, determining that the internal resistance curve of the target lead-acid storage battery is abnormal;

Trend checking is carried out on the historical internal resistance curve based on a preset trend checking algorithm, and if the historical internal resistance curve has an ascending trend, the abnormal internal resistance trend of the target lead-acid storage battery is determined;

determining an internal resistance threshold, and if any data in the historical internal resistance curve is larger than the internal resistance threshold, determining that the target lead-acid storage battery has abnormal internal resistance.

According to one embodiment of the present application, the internal resistance threshold includes at least a preset internal resistance threshold and a dynamic internal resistance threshold; the dynamic internal resistance threshold is determined by:

acquiring the internal resistance average value of the target lead-acid storage battery and the lead-acid storage batteries in the same group;

Determining a dynamic internal resistance threshold based on a preset internal resistance weight and the internal resistance average value; the preset internal resistance weight is greater than 1.

According to one embodiment of the present application, the determining the abnormality alert level of the target lead-acid battery based on the first monitoring result and/or the second monitoring result includes:

if the reason for causing the abnormality of the target lead-acid storage battery comprises that any data in the discharge voltage curve is smaller than or equal to the preset voltage threshold value or any data in the historical internal resistance curve is larger than the dynamic internal resistance threshold value, determining that the abnormality alarm level of the target lead-acid storage battery is a high-level alarm;

if the reason for causing the abnormality of the target lead-acid storage battery comprises that any data in the discharge voltage curve is located outside the first upper boundary and the first lower boundary, determining that the abnormality warning level of the target lead-acid storage battery is a middle level warning;

And if the reason for causing the abnormality of the target lead-acid storage battery does not include any one of the discharge voltage curve, the historical internal resistance curve and the discharge voltage curve, wherein any one of the discharge voltage curve and the historical internal resistance curve is smaller than or equal to the preset voltage threshold, and any one of the discharge voltage curve and the historical internal resistance curve is larger than the dynamic internal resistance threshold, and any one of the discharge voltage curve and the data is located outside the first upper boundary and the first lower boundary, determining that the abnormality alarm level of the target lead-acid storage battery is a low-level alarm.

According to one embodiment of the present application, the determining the target monitoring result of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result includes:

And if the first monitoring result is any one of abnormal discharge curve and abnormal voltage of the target lead-acid storage battery and the second monitoring result is any one of abnormal internal resistance curve, abnormal internal resistance trend and abnormal internal resistance of the target lead-acid storage battery, determining that the target monitoring result of the target lead-acid storage battery is abnormal.

According to one embodiment of the present application, the determining the discharge voltage curve and the historical internal resistance curve of the target lead-acid storage battery includes:

acquiring discharge voltage data of a target lead-acid storage battery in a target time period and historical internal resistance measurement data of the target lead-acid storage battery;

Respectively carrying out data preprocessing on the discharge voltage data and the historical internal resistance measurement data to respectively obtain first intermediate data and second intermediate data;

And respectively drawing a discharge voltage curve and a historical internal resistance curve of the target lead-acid storage battery according to the first intermediate data and the second intermediate data.

According to one embodiment of the present application, the data preprocessing includes at least one of denoising processing, smoothing processing, and normalization processing.

A battery state of health monitoring device according to an embodiment of the second aspect of the present application includes:

The first determining module is used for determining a discharge voltage curve and a historical internal resistance curve of the target lead-acid storage battery;

The first detection module is used for detecting abnormal discharge voltage of the target lead-acid storage battery based on the discharge voltage curve to obtain a first monitoring result;

The second detection module is used for detecting abnormal internal resistance of the target lead-acid storage battery based on the historical internal resistance curve to obtain a second monitoring result;

the second determining module is used for determining a target monitoring result of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result;

and the third determining module is used for determining the abnormal alarm level of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result if the target monitoring result is that the target lead-acid storage battery is abnormal.

An electronic device according to an embodiment of the third aspect of the present application includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing any of the battery state of health monitoring methods described above when executing the program.

According to a fourth aspect of the present application, the medium is a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor implements a method of monitoring the state of health of a battery as described in any of the above.

The above technical solutions in the embodiments of the present application have at least one of the following technical effects:

By determining the discharge voltage curve and the historical internal resistance curve of the target lead-acid storage battery, abnormal discharge voltage detection can be performed on the target lead-acid storage battery according to the discharge voltage curve and abnormal internal resistance detection can be performed on the target lead-acid storage battery according to the historical internal resistance curve, finally, whether the target lead-acid storage battery is abnormal or not can be accurately determined according to the detection result of the discharge voltage and/or the internal resistance detection result, and when the target monitoring result is abnormal, the abnormal alarm grade of the battery is determined according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for those skilled in the art.

Fig. 1 is a schematic flow chart of a method for monitoring a battery state of health according to an embodiment of the present application;

fig. 2 is a schematic diagram of a scenario of a battery state of health monitoring method according to an embodiment of the present application;

Fig. 3 is a schematic structural diagram of a battery health status monitoring device according to an embodiment of the present application;

Fig. 4 is a schematic structural diagram of an electronic device provided by the present application.

Detailed Description

Embodiments of the present application are described in further detail below with reference to the accompanying drawings and examples. The following examples are illustrative of the application but are not intended to limit the scope of the application.

In the description of the embodiments of the present application, it should be noted that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the embodiments of the present application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

In describing embodiments of the present application, it should be noted that, unless explicitly stated and limited otherwise, the terms "coupled," "coupled," and "connected" should be construed broadly, and may be either a fixed connection, a removable connection, or an integral connection, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium. The specific meaning of the above terms in embodiments of the present application will be understood in detail by those of ordinary skill in the art.

In embodiments of the application, unless expressly specified and limited otherwise, a first feature "up" or "down" on a second feature may be that the first and second features are in direct contact, or that the first and second features are in indirect contact via an intervening medium. Moreover, a first feature being "above," "over" and "on" a second feature may be a first feature being directly above or obliquely above the second feature, or simply indicating that the first feature is level higher than the second feature. The first feature being "under", "below" and "beneath" the second feature may be the first feature being directly under or obliquely below the second feature, or simply indicating that the first feature is less level than the second feature.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

Fig. 1 is a flow chart of a method for monitoring a battery health status according to an embodiment of the present application, as shown in fig. 1, the method for monitoring a battery health status includes:

Step 110, determining a discharge voltage curve and a historical internal resistance curve of the target lead-acid storage battery.

It should be noted that, the execution body of the battery health status monitoring method provided in the embodiment of the present application may be a server, a computer device, such as a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted electronic device, a wearable device, an Ultra-Mobile Personal Computer (UMPC), a netbook, a Personal digital assistant (Personal DIGITAL ASSISTANT, PDA), or the like.

The execution body of the present application may be a monitoring system terminal in some embodiments, in which a battery health status monitoring device may be provided.

According to the application, the discharge voltage of each lead-acid storage battery in the UPS power supply system of the data center can be obtained in real time, and the internal resistance of each lead-acid storage battery can be measured at fixed time.

Thus, the present application can determine each lead-acid battery as a target lead-acid battery, respectively.

Further, a discharge voltage of the target lead-acid battery in a specified period of time is obtained to form discharge voltage data, and a historical internal resistance measurement value of the target lead-acid battery is obtained to form historical internal resistance measurement data.

Further, curve drawing can be performed based on the obtained discharge voltage data to obtain a discharge voltage curve of the target lead-acid storage battery, and curve drawing is performed based on the obtained historical internal resistance measurement data to obtain a historical internal resistance curve.

And 120, detecting abnormal discharge voltage of the target lead-acid storage battery based on the discharge voltage curve to obtain a first monitoring result.

The method can set a dynamic gradient threshold for the voltage of each lead-acid storage battery, wherein the dynamic gradient threshold of the voltage can be simply called a voltage threshold, and the dynamic gradient threshold at least comprises two thresholds.

The application can also respectively determine an upper boundary and a lower boundary aiming at the discharge voltage curve.

Based on the above, the application can compare the voltage data with the preset voltage threshold, the dynamic voltage threshold, the upper boundary and the lower boundary respectively aiming at each voltage data in the discharge voltage curve, so as to determine the magnitude relation between the voltage data and the preset voltage threshold, the dynamic voltage threshold, the upper boundary and the lower boundary respectively.

According to the magnitude relation between the voltage data and a preset voltage threshold, a dynamic voltage threshold and between an upper boundary and a lower boundary, whether the discharge voltage of the target lead-acid storage battery is abnormal or not can be determined, and therefore a first monitoring result is obtained.

And 130, detecting abnormal internal resistance of the target lead-acid storage battery based on the historical internal resistance curve to obtain a second monitoring result.

The application can set a dynamic gradient threshold value for the internal resistance of each lead-acid storage battery, wherein the dynamic gradient threshold value of the internal resistance can be called as an internal resistance threshold value for short, and the dynamic gradient threshold value at least comprises two threshold values.

The application can also respectively determine an upper boundary and a lower boundary aiming at the historical internal resistance curve.

Based on the above, the application can compare the internal resistance data with the preset internal resistance threshold, the dynamic internal resistance threshold, the upper boundary and the lower boundary respectively aiming at each internal resistance data in the historical internal resistance curve, so as to determine the magnitude relation between the internal resistance data and the preset internal resistance threshold, the dynamic internal resistance threshold, the upper boundary and the lower boundary respectively.

The application can also analyze the trend of the historical internal resistance curve, thereby determining the internal resistance change trend of the target lead-acid storage battery.

According to the magnitude relation between the internal resistance data and a preset internal resistance threshold, a dynamic internal resistance threshold, an upper boundary and a lower boundary and the internal resistance change trend of the target lead-acid storage battery, whether the internal resistance of the target lead-acid storage battery is abnormal or not can be determined, and therefore a second monitoring result is obtained.

And 140, determining a target monitoring result of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result.

The target monitoring result of the target lead-acid storage battery in the application can comprise the presence abnormality of the target lead-acid storage battery and the absence of the abnormality of the target lead-acid storage battery.

According to the application, in some cases, whether the target lead-acid storage battery is abnormal can be determined only according to the first monitoring result. In some cases, whether the target lead-acid storage battery is abnormal or not can be determined according to the second monitoring result.

In some cases, it is necessary to combine the first monitoring result and the second detection result to determine whether the target lead-acid storage battery is abnormal.

And 150, if the target monitoring result is that the target lead-acid storage battery is abnormal, determining an abnormal alarm level of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result.

If the target monitoring result is determined to be that the target lead-acid storage battery is abnormal and the abnormality is determined only according to the first monitoring result, the abnormal alarm level of the target lead-acid storage battery can be determined according to the first monitoring result.

If the target monitoring result is determined to be that the target lead-acid storage battery is abnormal and the abnormality is determined only according to the second monitoring result, the abnormal alarm level of the target lead-acid storage battery can be determined according to the second monitoring result.

If the target monitoring result is determined to be abnormal, and the abnormality is determined according to the first monitoring result and the second monitoring result, determining an abnormal alarm level of the target lead-acid storage battery according to the first monitoring result and the second monitoring result.

The abnormal alarm levels of the target lead-acid battery of the present application may include, but are not limited to, high-level alarms, medium-level alarms and low-level alarms.

According to the battery health state monitoring method provided by the embodiment of the application, through determining the discharge voltage curve and the historical internal resistance curve of the target lead-acid storage battery, abnormal discharge voltage detection can be carried out on the target lead-acid storage battery according to the discharge voltage curve and abnormal internal resistance detection can be carried out on the target lead-acid storage battery according to the historical internal resistance curve, finally, whether the target lead-acid storage battery is abnormal or not can be accurately determined according to the detection result of the discharge voltage and/or the internal resistance detection result, and when the target monitoring result is abnormal, the abnormal alarm grade of the battery is determined according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

Based on the above embodiment, the step 110 may include:

Step 111, obtaining discharge voltage data of a target lead-acid storage battery in a target time period and historical internal resistance measurement data of the target lead-acid storage battery;

step 112, respectively carrying out data preprocessing on the discharge voltage data and the historical internal resistance measurement data to respectively obtain first intermediate data and second intermediate data;

And 113, respectively drawing a discharge voltage curve and a historical internal resistance curve of the target lead-acid storage battery according to the first intermediate data and the second intermediate data.

The application can acquire the discharge voltage data of the target lead-acid storage battery in the appointed target time period, and form the discharge voltage data by each voltage data.

And acquiring each internal resistance data of the target lead-acid storage battery in a history measurement mode, and forming the history internal resistance measurement data by each internal resistance data.

Further, the present application may perform data preprocessing on the discharge voltage data, wherein the data preprocessing may include at least one of denoising, smoothing, and normalizing.

In the application, denoising, smoothing and normalizing can be sequentially carried out on the discharge voltage data, and the first intermediate data is obtained after the treatment is completed.

The application can be realized by the following steps when denoising the discharge voltage data:

A sliding window W with an odd number of pixels is selected. For example, windows of 3x3, 5x5, 7x7, etc. size are used.

Applying median filtering to each of the discharge voltage data: a sliding window W is placed over each voltage data and the values of all the voltage data in the window are acquired.

Calculating a median: the voltage values in the sliding window are sorted to find the value thereof (i.e. the value located in the middle of the sorted sequence).

The median value is assigned to the voltage data: taking the median value as the voltage value of the voltage data, and completing the filtering operation when each voltage data in the discharge voltage data is filtered.

The smoothing process in the present application may be implemented by moving average, exponential smoothing, or the like.

The normalization processing in the application is realized by methods such as maximum-minimum normalization, Z-score normalization and the like.

In the application, denoising, smoothing and normalizing can be sequentially carried out on the historical internal resistance measurement data, and second intermediate data can be obtained after the processing is completed.

Further, the application can draw a curve according to the voltage data in the first intermediate data, thereby obtaining a discharge voltage curve of the target lead-acid storage battery; and drawing a curve according to the internal resistance data in the second intermediate data, thereby obtaining a historical internal resistance curve of the target lead-acid storage battery.

According to the embodiment, through denoising, smoothing and normalizing the acquired data, the interference of abnormal data can be reduced, the accuracy of the data is improved, the obtained discharge voltage curve and the historical internal resistance curve are more accurate, the detection result based on the discharge voltage curve and the historical internal resistance curve is more accurate, and finally the accuracy of judging the health state of the storage battery can be improved.

Based on the above embodiment, the step 120 may include:

Step 121, determining a first upper boundary and a first lower boundary of a discharge voltage curve respectively, and if any data in the discharge voltage curve is located outside the first upper boundary and the first lower boundary, determining that the discharge curve of the target lead-acid storage battery is abnormal;

Step 122, determining a voltage threshold, and if any data in the discharge voltage curve is smaller than or equal to the voltage threshold, determining that the target lead-acid storage battery has voltage abnormality; the voltage threshold at least comprises a preset voltage threshold and a dynamic voltage threshold; the dynamic voltage threshold is determined according to the voltage average value of the target lead-acid storage battery and the lead-acid storage batteries in the same group and the preset voltage weight.

According to the application, data in the discharge voltage curve can be divided, the upper boundary of the discharge voltage curve is respectively determined as the first upper boundary according to the divided data information, and the lower boundary of the discharge voltage curve is determined as the first lower boundary.

Further, each voltage data on the discharge voltage curve is compared with the first upper boundary and the first lower boundary, respectively, thereby determining a magnitude relation between each voltage data and the first upper boundary and the first lower boundary.

Further, if any voltage data in the discharge voltage curve is determined to be greater than the first upper boundary or less than the first lower boundary through comparison, it is determined that the voltage data in the discharge voltage curve is located outside the first upper boundary and the first lower boundary, and therefore the condition that the discharge curve of the target lead-acid storage battery is abnormal can be determined.

In the application, a dynamic gradient threshold value can be set for the discharge voltage of the target lead-acid storage battery, wherein the number of the threshold values in the dynamic gradient threshold value can be set according to actual requirements, for example, 2 threshold values can be set in the application, one threshold value is a preset voltage threshold value, and the threshold value can be represented by the discharge termination voltage of the target lead-acid storage battery; the other is a dynamic voltage threshold value, which can be obtained by carrying out product operation on the voltage average value of the target lead-acid storage battery and the lead-acid storage batteries in the same group and the voltage weight preset for the target lead-acid storage battery. The voltage weight previously set for the target lead-acid battery may be greater than 1 or less than 1, for example, in one embodiment of the present application, the voltage weight previously set for the target lead-acid battery may be 0.9 or 1.1.

Further, each voltage data in the discharge voltage curve may be compared with a preset weight threshold and a dynamic weight threshold, respectively, so as to obtain a magnitude relation between each voltage data and the preset weight threshold and the dynamic weight threshold.

After the comparison, if any data in the discharge voltage curve is less than or equal to a voltage threshold (less than or equal to a preset voltage threshold or a dynamic voltage threshold), determining that the target lead-acid storage battery has voltage abnormality.

Further, the step 121 may include:

step 1211, determining an upper quartile and a lower quartile of the data in the discharge voltage curve, respectively;

step 1212, determining a quartile distance based on the upper quartile and the lower quartile;

step 1213, determining a first upper boundary of the discharge voltage curve based on the quartile distance and the upper quartile;

In step 1214, a first lower boundary of the discharge voltage curve is determined based on the quartile distance and the lower quartile.

The application can divide the voltage data in the discharge voltage curve into a minimum observed value, an upper quartile, a median, a lower quartile and a maximum observed value.

Further, the upper quartile and the lower quartile are subjected to difference operation to obtain a quartile distance.

Further, the upper quartile and 1.5 times of the quartile distance are added to obtain a first upper boundary of the discharge voltage curve.

And subtracting the lower quartile from 1.5 times of the quartile distance to obtain a first lower boundary of the discharge voltage curve.

According to the embodiment, whether the target lead-acid storage battery is abnormal or not can be determined from multiple angles by comparing the data on the discharge voltage curve with the first upper boundary, the first lower boundary and the dynamic gradient threshold value of the discharge voltage curve, so that whether the target lead-acid storage battery is abnormal or not can be accurately determined according to the monitoring result or the monitoring result of the monitoring result and the internal resistance. And when the abnormality is determined to exist, determining the abnormality warning level of the battery according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

Based on the above embodiment, the step 130 may include:

Step 131, determining a second upper boundary and a second lower boundary of the historical internal resistance curve respectively, and if any data in the historical internal resistance curve is located outside the second upper boundary and the second lower boundary, determining that the internal resistance curve of the target lead-acid storage battery is abnormal;

step 132, carrying out trend test on the historical internal resistance curve based on a preset trend test algorithm, and if the historical internal resistance curve has an ascending trend, determining that the internal resistance trend of the target lead-acid storage battery is abnormal;

and 133, determining an internal resistance threshold, and if any data in the historical internal resistance curve is larger than the internal resistance threshold, determining that the internal resistance of the target lead-acid storage battery is abnormal.

The internal resistance threshold at least comprises a preset internal resistance threshold and a dynamic internal resistance threshold; the dynamic internal resistance threshold is determined by:

obtaining target lead-acid storage battery internal resistance average value of lead-acid storage batteries in the same group;

determining a dynamic internal resistance threshold based on a preset internal resistance weight and an internal resistance average value; the preset internal resistance weight is greater than 1.

According to the method, data in the historical internal resistance curve can be divided, the upper boundary of the historical internal resistance curve is respectively determined to be used as the second upper boundary according to the divided data information, and the lower boundary of the historical internal resistance curve is determined to be used as the second lower boundary.

The application can divide the internal resistance data in the history internal resistance curve into the minimum observed value, the upper quartile, the median, the lower quartile and the maximum observed value.

Further, adding the upper quartile to 1.5 times of the quartile distance to obtain a second upper boundary of the historical internal resistance curve.

And subtracting the lower quartile from 1.5 times of the quartile distance to obtain a second lower boundary of the historical internal resistance curve.

Further, each internal resistance data on the historical internal resistance curve is compared with a second upper boundary and a second lower boundary respectively, so that the magnitude relation between each internal resistance data and the second upper boundary and the second lower boundary is determined.

Further, if any one of the internal resistance data in the historical internal resistance curve is determined to be larger than the second upper boundary or smaller than the second lower boundary through comparison, the fact that the internal resistance data in the historical internal resistance curve is located outside the second upper boundary and the second lower boundary is determined, and therefore the condition that the internal resistance curve of the target lead-acid storage battery is abnormal can be determined.

The application can also set dynamic gradient threshold values for the internal resistance of the target lead-acid storage battery, wherein the number of the threshold values in the dynamic gradient threshold values can be set according to actual demands, for example, the number of the threshold values in the dynamic gradient threshold values can be set to 2, one of the threshold values is a preset internal resistance threshold value, and the threshold values can be specifically represented by the internal resistance value of the lead-acid storage battery which reaches the replacement condition; the other is a dynamic internal resistance threshold value, which can be obtained by carrying out product operation on the internal resistance average value of the target lead-acid storage battery and the lead-acid storage batteries in the same group and the internal resistance weight preset for the target lead-acid storage battery. The internal resistance weight previously set for the target lead-acid battery may be greater than 1, for example, in one embodiment of the present application, the voltage weight previously set for the target lead-acid battery may be 1.2.

Further, each internal resistance data in the historical internal resistance curve can be compared with a preset weight threshold and a dynamic weight threshold respectively, so that the magnitude relation between each internal resistance data and the preset weight threshold and the dynamic weight threshold is obtained.

After the comparison, if any data in the historical internal resistance curve is determined to be greater than or equal to an internal resistance threshold value (greater than or equal to a preset voltage threshold value or a dynamic voltage threshold value), determining that the internal resistance of the target lead-acid storage battery is abnormal.

According to the method, the historical internal resistance curve can be subjected to trend test according to a preset Mann-Kendall trend test algorithm, so that whether the internal resistance of the target lead-acid storage battery is in a trend of rising or not is determined. The Mann-Kendall trend test algorithm is a non-parametric statistical method commonly used to analyze time series data to detect trend changes in the data. The method is proposed by h.mann and d.r. kendall in 1945 for determining whether there is a trend change, such as an upward trend, a downward trend, or no trend, in the time series data.

If the historical internal resistance curve is determined to have the ascending trend in any time period, determining that the internal resistance trend of the target lead-acid storage battery is abnormal.

The embodiment can compare the data on the historical internal resistance curve with the second upper boundary, the second lower boundary and the dynamic gradient threshold value of the historical internal resistance curve, and further perform trend test on the historical internal resistance curve, so that whether the target lead-acid storage battery has abnormal internal resistance or not can be determined from multiple angles, and whether the target lead-acid storage battery has abnormal conditions or not can be accurately determined according to the monitoring result or the monitoring result of the monitoring result and the discharging voltage. And when the abnormality is determined to exist, determining the abnormality warning level of the battery according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

Based on the above embodiment, the step 140 may include:

Step 141, if the first monitoring result is any one of abnormal discharge curve and abnormal voltage of the target lead-acid storage battery, and the second monitoring result is any one of abnormal internal resistance curve, abnormal internal resistance trend and abnormal internal resistance of the target lead-acid storage battery, determining that the target monitoring result of the target lead-acid storage battery is abnormal.

Further, if the first monitoring result is determined to be any one of abnormal discharge curve and abnormal voltage of the target lead-acid storage battery, and the second monitoring result is determined to be any one of abnormal internal resistance curve, abnormal internal resistance trend and abnormal internal resistance of the target lead-acid storage battery, the target monitoring result of the target lead-acid storage battery can be determined to be abnormal of the target lead-acid storage battery.

It should be noted that, in the present application, whether the target lead-acid storage battery is abnormal may also be directly determined according to the first monitoring result.

Specifically, if the first monitoring result indicates that the target lead-acid storage battery has abnormal voltage, and the reason for the abnormal voltage is that any data in a discharge voltage curve is smaller than or equal to a preset voltage threshold value, the abnormal condition of the target lead-acid storage battery is directly determined.

According to the application, whether the target lead-acid storage battery is abnormal or not can be directly determined according to the second monitoring result.

Specifically, if the second monitoring result indicates that the target lead-acid storage battery has abnormal internal resistance, and the reason for the abnormal internal resistance is that any data in the historical internal resistance curve is larger than a dynamic internal resistance threshold value, the abnormal condition of the target lead-acid storage battery is directly determined.

For example: if any data in the discharge voltage curve is smaller than or equal to a preset voltage threshold value, determining that the target lead-acid storage battery is abnormal;

If any data in the historical internal resistance curve is greater than or equal to the dynamic internal resistance threshold value, determining that the target lead-acid storage battery is abnormal;

if any data in the discharge voltage curve is smaller than or equal to the dynamic voltage threshold value and any data in the historical internal resistance curve is larger than or equal to the dynamic internal resistance threshold value, determining that the target lead-acid storage battery is abnormal;

if any data in the discharge voltage curve is smaller than or equal to the dynamic voltage threshold value and the discharge curve of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal;

if any data in the discharge voltage curve is smaller than or equal to the dynamic voltage threshold value and the internal resistance curve of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal;

If any data in the discharge voltage curve is smaller than or equal to the dynamic voltage threshold value and the internal resistance trend of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal;

If any data in the historical internal resistance curve is greater than or equal to the dynamic internal resistance threshold value and the internal resistance curve of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal;

if any data in the historical internal resistance curve is greater than or equal to a dynamic internal resistance threshold value and the internal resistance trend of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal;

If the discharge curve of the target lead-acid storage battery is abnormal and the internal resistance curve of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal;

If the discharge curve of the target lead-acid storage battery is abnormal and the internal resistance trend of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal;

if the internal resistance curve of the target lead-acid storage battery is abnormal and the internal resistance trend of the target lead-acid storage battery is abnormal, determining that the target lead-acid storage battery is abnormal.

According to the embodiment, whether the target lead-acid storage battery is abnormal or not can be determined according to the first monitoring result or whether the target lead-acid storage battery is abnormal or not can be determined according to the second monitoring result or whether the target lead-acid storage battery is abnormal or not can be determined according to the first monitoring result and the second monitoring result, so that whether the target lead-acid storage battery is abnormal or not can be accurately determined, and when the abnormality is determined, the abnormal alarm level of the battery can be determined according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

Based on the above embodiment, the step 150 may include:

step 151, if the reason for causing the abnormality of the target lead-acid storage battery includes that any data in the discharge voltage curve is smaller than or equal to a preset voltage threshold, or any data in the historical internal resistance curve is larger than a dynamic internal resistance threshold, determining that the abnormality alarm level of the target lead-acid storage battery is a high-level alarm;

step 152, if the cause of the abnormality of the target lead-acid battery includes that any data in the discharge voltage curve is located outside the first upper boundary and the first lower boundary, determining that the abnormality warning level of the target lead-acid battery is a middle level warning;

step 153, if the cause of the abnormality of the target lead-acid battery does not include any one of the discharge voltage curve having any data smaller than or equal to the preset voltage threshold, the historical internal resistance curve having any data greater than the dynamic internal resistance threshold, and the discharge voltage curve having any data located outside the first upper boundary and the first lower boundary, determining that the abnormality alarm level of the target lead-acid battery is a low-level alarm.

In the application, the high-level warning is defined for the lead-acid storage battery which is lower than the preset voltage threshold and higher than the dynamic internal resistance threshold and is required to be replaced, so that if any data in a discharge voltage curve is smaller than or equal to the preset voltage threshold or any data in a historical internal resistance curve is larger than the dynamic internal resistance threshold, the abnormal warning level of the target lead-acid storage battery is determined to be the high-level warning so as to remind operation and maintenance personnel of a data center to replace the lead-acid storage battery in the first time.

In the application, the abnormal storage battery containing the abnormal discharge curve is marked as a middle-level alarm, so that if any data in the discharge voltage curve is located outside the first upper boundary and the first lower boundary, the abnormal alarm level of the target lead-acid storage battery is determined to be the middle-level alarm so as to prompt the operation and maintenance personnel of the data center that the lead-acid storage battery needs to be comprehensively checked.

The application adopts low-level alarms except high-level alarms and medium-level alarms, so that if the reason for causing the abnormality of the target lead-acid storage battery does not include any data in a discharge voltage curve which is smaller than or equal to a preset voltage threshold value, any data in a history internal resistance curve which is larger than a dynamic internal resistance threshold value and any data in the discharge voltage curve which is positioned outside a first upper boundary and a first lower boundary, the abnormal alarm level of the target lead-acid storage battery is determined to be the low-level alarm, so that the lead-acid storage battery needs to be focused.

According to the embodiment, when the target monitoring result is abnormal, the abnormal alarm level of the battery can be accurately determined according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

Fig. 2 is a schematic diagram of a scenario of a battery state of health monitoring method according to an embodiment of the present application, as shown in fig. 2, in some embodiments, the present application may collect and store discharge voltage data and historical internal resistance data of each lead-acid battery in a specified period of time through a monitoring system terminal of the battery. And respectively preprocessing (denoising, smoothing and normalizing) the internal resistance data and the discharge voltage data to generate a discharge voltage curve and an internal resistance curve of each lead-acid storage battery.

Further, carrying out abnormal analysis on the discharge voltage curve and the internal resistance curve, and selecting abnormal data and a lead-acid storage battery of the curve; trend analysis is carried out on the internal resistance curve by using a trend test algorithm, and a lead-acid storage battery with abnormal trend of the internal resistance curve is selected; and setting a dynamic gradient threshold value of the voltage and the internal resistance of the storage battery through the storage battery monitoring terminal. And comprehensively predicting and evaluating the health state of the lead-acid storage battery through Boolean operation. And finally, giving out alarms of different levels (such as a first level alarm, a second level alarm, an Nth level alarm and the like) to the lead-acid storage battery comprehensively evaluating the abnormality in the monitoring system terminal, and clicking the alarms to check specific abnormal data and/or curves.

Fig. 3 is a schematic structural diagram of a battery health status monitoring device according to an embodiment of the present application, as shown in fig. 3, where the battery health status monitoring device includes:

a first determining module 310 configured to determine a discharge voltage curve and a historical internal resistance curve of the target lead-acid battery;

the first detection module 320 is configured to detect an abnormal discharge voltage of the target lead-acid battery based on the discharge voltage curve, so as to obtain a first monitoring result;

a second detection module 330, configured to detect abnormal internal resistance of the target lead-acid battery based on the historical internal resistance curve, so as to obtain a second monitoring result;

a second determining module 340, configured to determine a target monitoring result of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result;

and a third determining module 350, configured to determine an abnormal alarm level of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result if the target monitoring result is that the target lead-acid storage battery is abnormal.

According to the battery health state monitoring device provided by the embodiment of the application, through determining the discharge voltage curve and the historical internal resistance curve of the target lead-acid storage battery, abnormal discharge voltage detection can be carried out on the target lead-acid storage battery according to the discharge voltage curve, abnormal internal resistance detection can be carried out on the target lead-acid storage battery according to the historical internal resistance curve, finally, whether the target lead-acid storage battery is abnormal or not can be accurately determined according to the detection result of the discharge voltage and/or the internal resistance detection result, and when the target monitoring result is abnormal, the abnormal alarm grade of the battery is determined according to the voltage detection result and/or the internal resistance detection result. Therefore, the accuracy of judging the health state of the storage battery can be improved by a multi-dimensional battery abnormal factor combined detection mode.

Based on any of the above embodiments, the first determining module 310 is specifically configured to:

Based on any of the above embodiments, the first detection module 320 is specifically configured to:

Based on any of the above embodiments, the first detection module 320 includes a determining unit configured to:

Based on any of the above embodiments, the second detection module 330 is specifically configured to:

Based on any of the above embodiments, the second determining module 340 is specifically configured to:

Based on any of the above embodiments, the third determining module 350 is specifically configured to:

Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include: processor 410, communication interface (Communications Interface) 420, memory 430, and communication bus 440, wherein processor 410, communication interface 420, and memory 430 communicate with each other via communication bus 440. The processor 410 may call logic instructions in the memory 430 to perform the following method: determining a discharge voltage curve and a historical internal resistance curve of a target lead-acid storage battery;

Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the related art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

In yet another aspect, embodiments of the present application further provide a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the method provided by the above embodiments, for example, comprising: determining a discharge voltage curve and a historical internal resistance curve of a target lead-acid storage battery;

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on such understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the related art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the method described in the respective embodiments or some parts of the embodiments.

Finally, it should be noted that the above-mentioned embodiments are merely illustrative of the application, and not limiting. While the application has been described in detail with reference to the embodiments, those skilled in the art will appreciate that various combinations, modifications, or equivalent substitutions can be made to the technical solutions of the present application without departing from the spirit and scope of the technical solutions of the present application, and it is intended to be covered by the scope of the claims of the present application.

Claims

1. A method for monitoring the state of health of a battery, comprising:

if the target monitoring result is that the target lead-acid storage battery is abnormal, determining an abnormal alarm level of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result;

The abnormal discharge voltage detection is carried out on the target lead-acid storage battery based on the discharge voltage curve to obtain a first monitoring result, and the abnormal discharge voltage detection comprises the following steps:

Determining a voltage threshold, and if any data in the discharge voltage curve is smaller than or equal to the voltage threshold, determining that the target lead-acid storage battery has voltage abnormality; the voltage threshold at least comprises a preset voltage threshold and a dynamic voltage threshold; the dynamic voltage threshold is determined according to the voltage average value of the target lead-acid storage battery and the lead-acid storage batteries in the same group and a preset voltage weight;

The detecting of abnormal internal resistance of the target lead-acid storage battery based on the historical internal resistance curve to obtain a second monitoring result comprises the following steps:

Determining an internal resistance threshold, and if any data in the historical internal resistance curve is larger than the internal resistance threshold, determining that the target lead-acid storage battery has abnormal internal resistance;

Determining a dynamic internal resistance threshold based on a preset internal resistance weight and the internal resistance average value; the preset internal resistance weight is greater than 1;

the determining the abnormal alarm level of the target lead-acid storage battery based on the first monitoring result and/or the second monitoring result comprises the following steps:

2. The method of claim 1, wherein determining the first upper and lower boundaries of the discharge voltage curve, respectively, comprises:

3. The battery state of health monitoring method of claim 1, wherein said determining a target monitoring result of the target lead-acid battery based on the first monitoring result and/or the second monitoring result comprises:

4. The method of claim 1, wherein determining a discharge voltage profile and a historical internal resistance profile of the target lead-acid battery comprises:

5. The battery state of health monitoring method of claim 4, wherein said data preprocessing comprises at least one of denoising, smoothing and normalizing.

6. A battery state of health monitoring apparatus using the battery state of health monitoring method of claim 1, comprising:

7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the battery state of health monitoring method of any one of claims 1 to 5 when the program is executed by the processor.

8. A medium, the medium being a non-transitory computer readable storage medium, having stored thereon a computer program, which when executed by a processor implements the battery state of health monitoring method of any of claims 1 to 5.