Method, apparatus, and storage medium for determining a state of a single battery cell

Abstract

The application discloses a kind of method, device and storage medium for determining monomer battery state.Therein, the method comprises: obtaining the first voltage data of any one monomer battery in the monomer battery group of vehicle, wherein the first voltage data is the normal voltage data of any one monomer battery;Determine the second voltage data of any one monomer battery within a predetermined time period based on the first voltage data;Determine the variance value of the second voltage data of any one monomer battery based on the second voltage data, wherein the variance value is used to represent the fluctuation state of any one monomer battery within a predetermined time period;Determine the state of any one monomer battery as normal state or abnormal state based on the variance value.The application solves the technical problem that the diagnosis method of power battery thermal runaway risk has large amount of calculation and cannot realize online application.

Description

Technical Field

[0001] This invention relates to the field of vehicles, and more specifically, to a method, apparatus, and storage medium for determining the state of a single battery cell. Background Technology

[0002] Currently, there are many diagnostic methods for the risk of thermal runaway in power batteries, such as multi-level 3σ screening method, entropy weighting method, and entropy-based fault diagnosis method. However, all of these methods have the problem of large computational load and difficulty in real-time online application.

[0003] There is currently no effective solution to the technical problems of the diagnostic methods for thermal runaway risk of power batteries, which involve large computational loads and cannot be applied online. Summary of the Invention

[0004] This invention provides a method, apparatus, and storage medium for determining the state of a single battery cell, thereby addressing the technical problem that diagnostic methods for the risk of thermal runaway in power batteries involve large computational loads and fail to achieve online application.

[0005] According to one aspect of the present invention, a method for determining the state of a single battery cell is provided. The method may include: acquiring first voltage data of any single battery cell in a vehicle's battery pack, wherein the first voltage data is normal voltage data of the single battery cell; determining second voltage data of the single battery cell within a preset time period based on the first voltage data; determining the variance value of the second voltage data of the single battery cell based on the second voltage data, wherein the variance value characterizes the fluctuation state of the single battery cell within the preset time period; and determining whether the state of the single battery cell is normal or abnormal based on the variance value.

[0006] Optionally, obtaining the first voltage data of any single cell in the vehicle's battery pack includes: obtaining the third voltage data of any single cell; retaining the voltage data within a preset voltage data range from the third voltage data to obtain the first voltage data.

[0007] Optionally, based on the first voltage data, determining the second voltage data of any single cell within a preset time period includes: extracting the first voltage data using the preset time period to obtain the second voltage data.

[0008] Optionally, based on the variance value, determining the state of any single battery cell as normal or abnormal includes: determining the state of any single battery cell as normal in response to the variance value being less than or equal to a preset variance value; and determining the state of any single battery cell as abnormal in response to the variance value being greater than the preset variance value.

[0009] Optionally, after determining that the state of any single cell is abnormal in response to a variance value greater than a preset variance value, the method further includes: outputting a prompt message, wherein the prompt message is used to characterize that the state of any single cell is abnormal.

[0010] Optionally, after outputting the prompt information, the method further includes: shifting the preset time period backward by a target time in the time dimension to update the preset time period; and based on the updated preset time period, extracting the first voltage data to determine the second voltage data.

[0011] According to one aspect of the present invention, an apparatus for determining the state of a single battery cell is provided. The apparatus may include: an acquisition unit, configured to acquire first voltage data of any single battery cell in a vehicle's battery pack, wherein the first voltage data is normal voltage data of the single battery cell; a first determination unit, configured to determine second voltage data of any single battery cell within a preset time period based on the first voltage data; a second determination unit, configured to determine the variance value of the second voltage data of any single battery cell based on the second voltage data, wherein the variance value characterizes the fluctuation state of the single battery cell within the preset time period; and a third determination unit, configured to determine whether the state of the single battery cell is normal or abnormal based on the variance value.

[0012] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the method for determining the state of a single battery cell according to the embodiments of the present invention.

[0013] According to another aspect of the present invention, a processor is also provided. The processor is used to run a program, wherein the program, when running, executes the method for determining the state of a single battery cell according to the embodiments of the present invention.

[0014] According to another aspect of the present invention, a vehicle is also provided, which is used to perform the method for determining the state of a single battery cell according to the embodiments of the present invention.

[0015] In this embodiment of the invention, the first voltage data of any single battery cell in a vehicle's battery pack is obtained, wherein the first voltage data is the normal voltage data of any single battery cell; based on the first voltage data, the second voltage data of any single battery cell within a preset time period is determined; based on the second voltage data, the variance value of the second voltage data of any single battery cell is determined, wherein the variance value is used to characterize the fluctuation state of any single battery cell within the preset time period; based on the variance value, the state of any single battery cell is determined to be normal or abnormal. In other words, this embodiment of the invention obtains the first voltage data of any single battery cell in a vehicle's battery pack, extracts the first voltage data through a preset time period to obtain the second voltage data, calculates the variance value of the second voltage data, and determines whether the state of any single battery cell is normal or abnormal based on the variance value. This achieves the goal of a simple and efficient method for determining the state of a single battery cell, solving the technical problem that the diagnostic method for thermal runaway risk of power batteries has a large computational load and cannot be applied online, thus achieving the technical effect of a diagnostic method for thermal runaway risk of power batteries with a small computational load and online application. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0017] Figure 1 This is a flowchart of a method for determining the state of a single cell according to an embodiment of the present invention;

[0018] Figure 2 This is a flowchart of a time-series-based method for diagnosing potential anomalies in battery thermal runaway according to an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of a time-series-based battery thermal runaway potential anomaly diagnosis system according to an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of an apparatus for determining the state of a single battery cell according to an embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0023] Example 1

[0024] According to an embodiment of the present invention, a method for determining the state of a single cell is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0025] Figure 1 This is a flowchart of a method for determining the state of a single cell according to an embodiment of the present invention, such as... Figure 1 As shown, the method may include the following steps:

[0026] Step S101: Obtain the first voltage data of any single cell in the vehicle's battery pack, wherein the first voltage data is the normal voltage data of any single cell.

[0027] In the technical solution provided by step S101 of the present invention, the first voltage data of any single battery in the single battery pack of the vehicle is obtained and uploaded to the vehicle data platform in time series. The time series can be 1 second, 2 seconds, 3 seconds, etc., and the vehicle can be a new energy vehicle.

[0028] For example, when a new energy vehicle is in motion, the normal voltage data of any single battery cell can be uploaded to the data platform, or the normal voltage data of all single batteries in the battery pack can be uploaded to the data platform. The single batteries in the battery pack are numbered, for example, 1, 2, 3, 4; then, with the number of each single battery cell as the horizontal axis and the first voltage data of the corresponding single battery cell as the vertical axis, a single battery cell voltage matrix of the battery pack is established.

[0029] Step S102: Based on the first voltage data, determine the second voltage data of any single cell within a preset time period.

[0030] In the technical solution provided by step S102 of the present invention, the second voltage data of any single cell is taken from the first voltage data within a preset time period. The preset time period can be 50 seconds, and each second of the preset time period corresponds to one voltage data. The second voltage data is a portion of the first voltage data. When the first voltage data is from the first voltage data, the second voltage data, the third voltage data... the first thousandth voltage data, the second voltage data of the first voltage data within the preset time period is from the first voltage data, the second voltage data, the third voltage data... the fiftieth voltage data.

[0031] Step S103: Based on the second voltage data, determine the variance value of the second voltage data of any single cell, wherein the variance value is used to characterize the fluctuation state of any single cell within a preset time period.

[0032] In the technical solution provided by step S103 of the present invention, the average of the first voltage data, the second voltage data, the third voltage data... the fiftieth voltage data of the second voltage data within a preset time period is calculated. The average of the first voltage data is subtracted and then squared to obtain A1, the average of the second voltage data is subtracted and then squared to obtain A2, the average of the third voltage data is subtracted and then squared to obtain A3... the average of the fiftieth voltage data is subtracted and then squared to obtain A50. A1 plus A2 plus A3... plus A3 gives B1. The quotient between B1 and fifty is determined as the variance value. When the variance value is larger, it indicates that the second voltage data fluctuates too much and is unstable voltage data.

[0033] Step S104: Based on the variance value, determine whether the state of any single cell is normal or abnormal.

[0034] In the technical solution provided by step S104 of the present invention, the relationship between the variance value and the preset variance value is determined, or the variance value is determined to be within the normal threshold range, thereby determining whether the state of any single battery cell is normal or abnormal.

[0035] In this application, steps S101 to S104 involve obtaining the first voltage data of any single battery cell in a vehicle's battery pack, where the first voltage data represents the normal voltage data of any single battery cell; determining the second voltage data of any single battery cell within a preset time period based on the first voltage data; determining the variance value of the second voltage data of any single battery cell based on the second voltage data, where the variance value characterizes the fluctuation state of any single battery cell within the preset time period; and determining whether the state of any single battery cell is normal or abnormal based on the variance value. In other words, this embodiment of the invention obtains the first voltage data of any single battery cell in a vehicle's battery pack, extracts the first voltage data through a preset time period to obtain the second voltage data, calculates the variance value of the second voltage data, and determines whether the state of any single battery cell is normal or abnormal based on the variance value. This achieves the goal of a simple and efficient method for determining the state of a single battery cell, solving the technical problem that the diagnostic method for thermal runaway risk of power batteries has a large computational load and cannot be applied online, thus achieving the technical effect of a diagnostic method for thermal runaway risk of power batteries with a small computational load and online application capability.

[0036] The method described in this embodiment will be further described below.

[0037] As an optional embodiment, step S101, obtaining the first voltage data of any single cell in the vehicle's battery pack, includes: obtaining the third voltage data of any single cell; retaining the voltage data within a preset voltage data range in the third voltage data to obtain the first voltage data.

[0038] In this embodiment, the third voltage data of any single battery cell in the vehicle's single battery pack, which is uploaded to the vehicle data platform in time series, is obtained. The third voltage data within the range of 2 to 5 volts is retained to obtain the first voltage data, and other voltage data are discarded.

[0039] For example, the third voltage data of any single cell in a vehicle's battery pack, or the third voltage data of every single cell in the battery pack, can be obtained within one hour and uploaded to the vehicle data platform in a time sequence. If there are 3600 third voltage data points for any single cell, the 3600 third voltage data points within the range of 2 to 5 volts are retained to obtain the first voltage data. The obtained first voltage data points will have 3500. This is only an example and is not a specific limitation.

[0040] For another example, the third voltage data of any single cell in the vehicle's battery pack, or the third voltage data of each single cell in the battery pack, can be obtained by uploading the data to the vehicle data platform in time sequence within half an hour. If there are 1800 third voltage data points for any single cell, the 1800 third voltage data points within the range of 2 to 5 volts are retained to obtain the first voltage data. The obtained first voltage data points are 1000. This is only an example and is not a specific limitation.

[0041] As an optional embodiment, step S102, based on the first voltage data, determines the second voltage data of any single cell within a preset time period, including: extracting the first voltage data using the preset time period to obtain the second voltage data.

[0042] In this embodiment, the first voltage data is extracted using a preset time period to obtain the second voltage data. In other words, the second voltage data is a portion of the first voltage data.

[0043] For example, a preset time period of 50 seconds is used to extract the above 3,500 first voltage data points, and the second voltage data points are obtained from the first to the fiftieth voltage data points out of the 3,500 voltage data points.

[0044] For another example, a preset time period of 50 seconds is used to extract the above 3500 first voltage data points, and the second voltage data points are obtained from the second to the fifty-first voltage data points out of the 3500 voltage data points.

[0045] As an optional embodiment, step S104, determining the state of any single battery cell as normal or abnormal based on the variance value, includes: determining the state of any single battery cell as normal in response to the variance value being less than or equal to a preset variance value; and determining the state of any single battery cell as abnormal in response to the variance value being greater than the preset variance value.

[0046] In this embodiment, if the variance value is less than or equal to a preset variance value, the state of any single battery cell is determined to be normal; if the variance value is greater than the preset variance value, the state of any single battery cell is determined to be abnormal. There are two methods for determining the preset variance value.

[0047] For example, one method for pre-setting variance values ​​is the threshold method. This involves stratifying the battery based on three data points: temperature, State of Charge (SOC) (the percentage of battery charge reached), and average current. For instance, battery temperature could be divided into seven levels: below 0°C, 0-10°C, 10-20°C, 20-30°C, 30-40°C, 40-50°C, and above 50°C. SOC could be divided into ten levels: 0-10%, 10%-20%, 20%-30%, 30%-40%, 40%-50%, 50%-60%, 60%-70%, 70%-80%, 80%-90%, and 90%-100%. Average current could also be divided into ten levels. -500mA to -400mA, -400mA to -300mA, -300mA to -200mA, -200mA to -100mA, -100mA to 0mA, 0mA to 100mA, 100mA to 200mA, 200mA to 300mA, 300mA to 400mA, 400mA to 500mA. These are just examples and not specific limitations. In each level composed of the three parameters, the reference value of the variance calculated by estimating the corresponding second voltage data under that level using normal vehicle data is used. Then, based on the reference value of each level, the threshold value under that level is set, which is the predetermined variance value.

[0048] For another example, another preset variance value is based on Laida's rule, which involves calculating the mean and standard deviation of all variance values ​​of the first normal data, and determining the range of normal preset variance values ​​as the variance values ​​within the range of the mean plus or minus three times the standard deviation, and determining the range of abnormal preset variance values ​​as the variance values ​​outside this range.

[0049] As an optional embodiment, after determining that the state of any single battery cell is abnormal in response to a variance value greater than a preset variance value, the method further includes: outputting a prompt message, wherein the prompt message is used to characterize the state of any single battery cell as abnormal.

[0050] In this embodiment, when any single battery cell is in an abnormal state, an indicator light in the vehicle displays a warning message.

[0051] For example, when any single battery cell is in an abnormal state, the battery indicator light on the vehicle's central control display will turn red to issue a warning, prompting the driver that the vehicle's battery pack has malfunctioned and needs to be replaced.

[0052] In one optional embodiment, after outputting the prompt information, the method further includes: shifting the preset time period backward by a target time in the time dimension to update the preset time period; and based on the updated preset time period, extracting the first voltage data to determine the second voltage data.

[0053] In this embodiment, the preset time period is shifted forward by one second in the time dimension to obtain an updated preset time period. Based on the updated preset time period, the first voltage data is truncated to obtain new second voltage data.

[0054] For example, the preset time period from 1 to 50 seconds is shifted forward by one second in the time dimension, and the shifted preset time period is from 2 to 51 seconds. Based on the shifted preset time period from 2 to 51 seconds, the above 3500 first voltage data are extracted, and the second voltage data is the second to the fifty-first voltage data in the 3500 voltage data.

[0055] For another example, the preset time period from 2 to 51 seconds is shifted forward by one second in the time dimension, resulting in a preset time period from 3 to 52 seconds. Based on the shifted preset time period from 3 to 52 seconds, the aforementioned 3500 first voltage data points are extracted, thereby obtaining the second voltage data points, which are the third to fifty-second voltage data points out of the 3500 voltage data points. The preset time period is shifted forward by one second in the time dimension until the first voltage data is processed in the time dimension.

[0056] In this embodiment of the invention, the third voltage data of any single battery cell is obtained. Voltage data within a preset voltage data range in the third voltage data is retained to obtain first voltage data. The first voltage data is then truncated using a preset time period to obtain second voltage data. When the variance value is less than or equal to the preset variance value, the state of any single battery cell is determined to be normal. When the variance value is greater than the preset variance value, the state of any single battery cell is determined to be abnormal. The information of the abnormal battery cell is output and an alarm is triggered. The preset time period is shifted forward by a target time in the time dimension to update the preset time period. Based on the updated preset time period, the first voltage data is truncated to obtain the second voltage data. This solves the technical problem that the diagnostic method for thermal runaway risk of power batteries has a large computational load and cannot be applied online, and achieves the technical effect of a diagnostic method for thermal runaway risk of power batteries with a small computational load and online application.

[0057] Example 2

[0058] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0059] Currently, a related technology proposes a digital twin-based method for assessing the thermal runaway risk of new energy vehicles in a group. This method assesses and ranks the thermal runaway risk of vehicles from the same batch or with similar battery configurations. Using all data and a digital twin model on a cloud platform, statistical methods are employed to extract and classify the characteristics of individual vehicles causing thermal runaway accidents within the group of new energy vehicles with the same battery pack. The thermal runaway probability information gain of the inducing factors is extracted, and through data fitting, the weight and bias values ​​of each thermal runaway feature are obtained. Finally, the group is ranked and the thermal runaway risk is assessed.

[0060] In another related technology, a method for early warning of thermal runaway of a single power battery cell based on cloud-based online data is proposed, including the following steps: S1: Extracting the boundary features of the battery module from the battery pack data collected in the cloud and forming a high-dimensional matrix; S2: Extracting the low-dimensional feature matrix of the high-dimensional matrix, calculating the current failure probability based on the low-dimensional feature matrix, and comparing the current failure probability with a preset failure probability threshold to determine whether there is a risk of thermal runaway; S3: When a risk of thermal runaway is determined, calculating the contribution value of each dimension in the high-dimensional matrix to the failure probability, and identifying the single battery cell corresponding to the boundary feature with the largest contribution to the failure probability as a high-risk single cell to be verified; S4: Analyzing the online voltage, temperature, and SOC data of the high-risk single cell to be verified, and issuing an alarm at three different levels according to the deviation value.

[0061] In another related technology, a cloud-based lifelong learning-based method for assessing the thermal runaway risk of power batteries is proposed, including the following steps: Cloud data cleaning: The vehicle's Internet of Vehicles system uploads the performance parameter data of the power battery collected by the Battery Management System (BMS) to the cloud in real time, and cleans the data to form a single-vehicle dataset; Calculation of the probability of thermal runaway caused by dynamic feature elements and the probability of thermal runaway based on multi-factor dynamic reliability functions: By extracting the dynamic feature elements related to thermal runaway and the reliability functions of related factors from the single-vehicle dataset, the probability of thermal runaway caused by the dynamic feature elements and the reliability functions is calculated; Finally, through a multi-source data fusion method, all thermal runaway probabilities are fused to finally calculate the comprehensive thermal runaway risk assessment and comprehensive thermal runaway probability of the power battery.

[0062] However, embodiments of the present invention propose a time-series-based method for diagnosing potential anomalies in battery thermal runaway. Figure 2 This is a flowchart of a time-series-based method for diagnosing potential anomalies in battery thermal runaway according to an embodiment of the present invention, such as... Figure 2 As shown, the method may include the following steps:

[0063] Step 201: Charge or discharge the battery.

[0064] When the vehicle is in motion, the vehicle's battery pack discharges; when the vehicle is charging, the vehicle's battery pack charges. When the vehicle's battery is charging or discharging, the individual cell voltage data of the vehicle's power battery is acquired and uploaded to the vehicle data platform in time series.

[0065] Step 202: Preprocess the battery voltage.

[0066] The system obtains the individual cell voltage data of the power battery from the BMS, and then performs data preprocessing. That is, if a frame contains abnormal data where the individual cell voltage is outside the range of 2 to 5V, the frame is removed. Then, an individual cell voltage matrix is ​​established with the individual cell code on the horizontal axis and time on the vertical axis.

[0067] Step 203: Select the size of the calculation window.

[0068] Select the calculation window size. Based on experimental experience, the window size is selected as 50 frames. The calculation window contains the voltage values ​​of all individual cells in these 50 frames. The initial calculation window is from frame 1 to frame 50.

[0069] Step 204: Calculate the variance of the voltage within the window.

[0070] For each battery cell, the variance is calculated in the time dimension, that is, the variance value of each battery cell over a time range of 50 frames is calculated.

[0071] Step 205: Determine whether the variance value exceeds the threshold.

[0072] Two different methods are used to determine all the above variance values. When the variance obtained in step 204 exceeds the threshold of the level, an alarm is triggered, and the individual battery corresponding to the variance value outside the range is regarded as the battery cell that has failed.

[0073] One type of threshold method is the threshold method, which stratifies the battery based on three data items: temperature, SO (State of Charge), and average current. For example, the battery temperature is divided into seven levels: below 0°C, 0 to 10°C, 10 to 20°C, 20 to 30°C, 30 to 40°C, 40 to 50°C, and above 50°C. The SOC (State of Charge) is divided into ten levels, for example: 0 to 10%, 10% to 20%, 20% to 30%, 30% to 40%, 40% to 50%, 50% to 60%, 60% to 70%, 70% to 80%, 80% to 90%, and 90% to 100%. The average current is also divided into ten levels. -500mA to -400mA, -400mA to -300mA, -300mA to -200mA, -200mA to -100mA, -100mA to 0mA, 0mA to 100mA, 100mA to 200mA, 200mA to 300mA, 300mA to 400mA, 400mA to 500mA. These are just examples and not specific limitations. In each level composed of the three parameters, the reference value of the variance is calculated by estimating the corresponding voltage data for that level using normal vehicle data. Then, based on the reference value for each level, the threshold for that level is set.

[0074] Another threshold is based on Laida's rule, which involves calculating the mean and standard deviation of all variance values ​​of the normal voltage data, and determining the range of variance values ​​within the range of the mean plus or minus three times the standard deviation as the normal threshold range, and determining the range of variance values ​​outside this range as the abnormal threshold range.

[0075] Step 206: Include in the frequency statistics.

[0076] The number of times the difference value in step 205 does not exceed the threshold is included in the frequency statistics.

[0077] Step 207 was not included in the frequency statistics.

[0078] The frequency of occurrences where the variance value does not exceed the threshold is included in the frequency statistics.

[0079] The number of times the difference value in step 205 exceeds the threshold is included in the frequency statistics.

[0080] Step 208: Count the frequency.

[0081] The number of times included in the frequency statistics in step 206.

[0082] In this embodiment, a time-series-based diagnostic system for potential anomalies in battery thermal runaway is proposed. Figure 3 This is a schematic diagram of a time-series-based battery thermal runaway potential anomaly diagnosis system according to an embodiment of the present invention, such as... Figure 3 As shown, the system may include:

[0083] The data acquisition module 301 can be used to acquire the single-cell voltage data of the power battery from the BMS.

[0084] The data preprocessing module 302 can be used to preprocess the acquired battery data. That is, if a frame contains abnormal data where the voltage of a single battery cell is outside the range of 2 to 5V, the frame will be discarded.

[0085] The diagnostic module 303 can be used to calculate the variance of battery cell data within a time window, make a judgment based on the judgment conditions, and issue an abnormal alarm if the judgment threshold is exceeded.

[0086] In this embodiment, during battery charging or discharging, the individual cell voltage data of the power battery is acquired, the battery voltage is preprocessed, the preprocessed battery voltage data is truncated using a window, the variance value of the truncated voltage data is calculated, and it is determined whether the variance value exceeds a threshold. The variance values ​​exceeding the threshold and the variance values ​​not exceeding the threshold are statistically analyzed. This solves the technical problem that the diagnostic method for the thermal runaway risk of power batteries has a large computational load and cannot be applied online, and achieves the technical effect of a diagnostic method for the thermal runaway risk of power batteries with a small computational load and online application.

[0087] Example 3

[0088] According to embodiments of the present invention, an apparatus for determining the state of a single battery cell is also provided. It should be noted that this apparatus for determining the state of a single battery cell can be used to execute the method for determining the state of a single battery cell in Embodiment 1.

[0089] Figure 4 This is a schematic diagram of a device for determining the state of a single battery cell according to an embodiment of the present invention. Figure 4 As shown, the device 400 for determining the state of a single battery cell may include: an acquisition unit 401, a first determination unit 402, a second unit 403, and a third determination unit 404.

[0090] The acquisition unit 401 is used to acquire the first voltage data of any single cell in the vehicle's single battery pack, wherein the first voltage data is the normal voltage data of any single cell.

[0091] The first determining unit 402 is used to determine the second voltage data of any single cell within a preset time period based on the first voltage data.

[0092] The second determining unit 403 is used to determine the variance value of the second voltage data of any single cell based on the second voltage data, wherein the variance value is used to characterize the fluctuation state of any single cell within a preset time period.

[0093] The third determining unit 404 is used to determine the state of any single cell as normal or abnormal based on the variance value.

[0094] Optionally, the acquisition unit 401 may include: an acquisition module for acquiring third voltage data of any single cell; and a first processing module for retaining voltage data within a preset voltage data range from the third voltage data to obtain first voltage data.

[0095] Optionally, the first determining unit 402 may include: a second processing module, used to extract the first voltage data using a preset time period to obtain the second voltage data.

[0096] Optionally, the third determining unit 402 may include: a first determining module, used to determine the state of any single cell as normal in response to a variance value being less than or equal to a preset variance value; and a second determining module, used to determine the state of any single cell as abnormal in response to a variance value being greater than a preset variance value.

[0097] Optionally, the device further includes an output unit, configured to output a prompt message after determining that the state of any single cell is abnormal in response to a variance value greater than a preset variance value, wherein the prompt message is used to characterize the state of any single cell as abnormal.

[0098] Optionally, the device further includes: an update unit, configured to update the preset time period by shifting the preset time period backward by a target time in the time dimension after outputting the prompt information; and a processing unit, configured to extract the first voltage data and determine the second voltage data based on the updated preset time period.

[0099] In this embodiment, an acquisition unit is used to acquire the first voltage data of any single battery cell in the vehicle's battery pack, wherein the first voltage data is the normal voltage data of any single battery cell; a first determination unit is used to determine the second voltage data of any single battery cell within a preset time period based on the first voltage data; a second determination unit is used to determine the variance value of the second voltage data of any single battery cell based on the second voltage data, wherein the variance value is used to characterize the fluctuation state of any single battery cell within the preset time period; and a third determination unit is used to determine whether the state of any single battery cell is normal or abnormal based on the variance value. This solves the technical problem that the diagnostic method for thermal runaway risk of power batteries has a large computational load and cannot be applied online, and achieves the technical effect of low computational load and online application of the diagnostic method for thermal runaway risk of power batteries.

[0100] Example 4

[0101] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the storage medium including a stored program, wherein the program executes the method for determining the state of a single cell in Embodiment 1.

[0102] Example 5

[0103] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program executes the method for determining the state of a single battery cell in Embodiment 1.

[0104] Example 6

[0105] According to an embodiment of the present invention, a vehicle is also provided for performing the method for determining the state of a single battery cell in Embodiment 1.

[0106] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0107] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0108] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0109] The units described as separate components may or may not be physically separate. Similarly, the components shown as units may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0110] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0111] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0112] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining the state of a single cell, characterized in that, include: Obtain the first voltage data of any single cell in the vehicle's battery pack, wherein the first voltage data is the normal voltage data of the arbitrary single cell. Based on the first voltage data, determine the second voltage data of any single battery cell within a preset time period; Based on the second voltage data, the variance value of the second voltage data of any single cell is determined, wherein the variance value is used to characterize the fluctuation state of any single cell within the preset time period. Based on the variance value, the state of any single battery cell is determined to be either normal or abnormal. Wherein, after any one of the individual battery cells is in the abnormal state, the method further includes: shifting the preset time period backward by a target time in the time dimension to update the preset time period; and based on the updated preset time period, extracting the first voltage data to determine the second voltage data.

2. The method according to claim 1, characterized in that, Obtain the first voltage data of any single cell in the vehicle's battery pack, including: Obtain the third voltage data of any one of the individual cells; The voltage data within the preset voltage data range in the third voltage data are retained to obtain the first voltage data.

3. The method according to claim 1, characterized in that, Based on the first voltage data, determining the second voltage data of any single battery cell within a preset time period includes: The first voltage data is extracted using the preset time period to obtain the second voltage data.

4. The method according to claim 1, characterized in that, Based on the variance value, determining whether any single cell is in a normal or abnormal state includes: In response to the variance value being less than or equal to a preset variance value, the state of any single battery cell is determined to be the normal state. In response to the variance value being greater than the preset variance value, the state of any single battery cell is determined to be the abnormal state.

5. The method according to claim 4, characterized in that, After determining that the state of any single battery cell is the abnormal state in response to the variance value being greater than the preset variance value, the method further includes: Output a prompt message, wherein the prompt message is used to indicate that the state of any one of the individual battery cells is the abnormal state.

6. An apparatus for determining the state of a single battery cell, characterized in that, include: The acquisition unit is used to acquire the first voltage data of any single cell in the vehicle's single battery pack, wherein the first voltage data is the normal voltage data of the arbitrary single cell. The first determining unit is used to determine the second voltage data of any one of the individual cells within a preset time period based on the first voltage data. The second determining unit is used to determine the variance value of the second voltage data of any one individual battery cell based on the second voltage data, wherein the variance value is used to characterize the fluctuation state of any one individual battery cell within the preset time period. The third determining unit is used to determine whether the state of any single battery cell is normal or abnormal based on the variance value. Wherein, after any one of the individual battery cells is in the abnormal state, the device is further configured to perform the following steps: shifting the preset time period backward by a target time in the time dimension, and updating the preset time period; based on the updated preset time period, extracting the first voltage data, and determining the second voltage data.

7. A processor, characterized in that, The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 5 when it runs.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 5.

9. A vehicle, characterized in that, The vehicle is used to perform the method according to any one of claims 1 to 5.

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