Battery consistency evaluation method, evaluation device, electronic device and storage medium

Abstract

The present application discloses a battery consistency evaluation method, evaluation device, electronic device and storage medium. The battery consistency evaluation method includes: obtaining multiple historical charging condition data sets of multiple charging of the battery, and the multiple charging corresponds to the multiple historical charging condition data sets one by one; for each of the data sets, obtaining the target minimum cell voltage in the data set, the target minimum cell voltage is the minimum cell voltage that is not less than the preset voltage and has the latest acquisition time; inputting each of the target minimum cell voltages into the pre-acquisition model to obtain the corresponding SOC consistency parameter value; the model is a correspondence relationship model between the minimum cell voltage and the SOC consistency parameter value; according to the SOC consistency parameter value of the multiple charging, the consistency of the battery is evaluated. The battery consistency evaluation method of the embodiment of the present application has more corresponding computing opportunities, fewer conditions required for implementation, is easy to implement, and has a wide range of applicable scenarios.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a battery consistency evaluation method, an evaluation device, an electronic device, and a storage medium. Background Art

[0002] The consistency of the power battery affects the battery capacity that can be exerted by the battery, and thus affects the vehicle's endurance. Therefore, it is very important to estimate the consistency of the battery as much as possible under various working conditions. In the relevant technology, the method used to estimate the consistency of the power battery in actual driving conditions is to discharge the battery to a low SOC state and let it stand for a sufficient period of time, and then estimate the consistency of the battery when the battery reaches a balanced state. This estimation method corresponds to fewer calculation opportunities, so there are more conditions that need to be met to obtain the battery consistency evaluation results using this method, which is more difficult to implement and has fewer applicable scenarios.

[0003] The above statements are only used to provide background information related to the present application and do not necessarily constitute prior art. Summary of the invention

[0004] In view of the fact that the method of evaluating the battery consistency after discharging the battery to a low SOC state and standing for a sufficient period of time adopted in the above-mentioned related technologies requires many conditions to be met, is difficult to implement, and has few applicable scenarios, the present application provides a battery consistency evaluation method, an evaluation device, an electronic device, and a storage medium, so as to provide a battery consistency evaluation method that requires fewer conditions during implementation, is easy to implement, and has a wide range of applicable scenarios.

[0005] According to a first aspect of an embodiment of the present application, a battery consistency evaluation method is provided, comprising:

[0006] Acquire multiple historical charging condition data sets of multiple charging of the battery, wherein the multiple charging times correspond to the multiple historical charging condition data sets one by one;

[0007] For each of the data sets, obtaining a target minimum cell voltage in the data set, where the target minimum cell voltage is a minimum cell voltage that is not less than a preset voltage and has the latest acquisition time;

[0008] Input each of the target minimum cell voltages into a pre-acquisition model to obtain a corresponding SOC consistency parameter value; the model is a correspondence relationship model between the minimum cell voltage and the SOC consistency parameter value;

[0009] The consistency of the battery is evaluated according to the SOC consistency parameter values ​​of the multiple charges.

[0010] The battery consistency evaluation method of the embodiment of the present application has more corresponding computer opportunities, requires fewer conditions for implementation, is easy to implement, and has a wide range of applicable scenarios. It largely overcomes the defects of the related art of evaluating the battery consistency by discharging the battery to a low SOC state and letting it stand for a sufficient period of time, which requires more conditions to be met, is more difficult to implement, and has fewer applicable scenarios.

[0011] In some embodiments of the present application, the step of evaluating the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges includes:

[0012] Obtaining a change rate of the SOC consistency parameter values ​​of multiple charges within a first preset time period from the SOC consistency parameter values ​​of multiple charges;

[0013] Comparing the SOC consistency parameter value of each charge within the first preset time with a first threshold, and comparing the change rate with a second threshold;

[0014] When there is at least one charging SOC consistency parameter value greater than the first threshold or the change rate greater than the second threshold within the first preset time period, determining that the battery consistency is abnormal;

[0015] When the SOC consistency parameter values ​​of multiple charges within the first preset time period are not greater than the first threshold and the change rate is not greater than the second threshold, it is determined that the consistency of the battery is normal.

[0016] By evaluating the consistency of the battery according to the SOC consistency parameter value and its change rate within the first preset time period, and taking the SOC consistency parameter value and its change rate as the evaluation basis, a more accurate battery consistency evaluation result can be obtained.

[0017] In some embodiments of the present application, the step of obtaining the change rate of the SOC consistency parameter value of multiple charges within a first preset time period from the SOC consistency of the multiple charges includes:

[0018] Obtaining, from the SOC consistency parameter values ​​of the multiple charges, SOC consistency parameter values ​​of the multiple charges within the first preset time period;

[0019] In a preset coordinate system with time as the horizontal axis and the SOC consistency parameter value as the vertical axis, fitting the SOC consistency parameter values ​​of multiple charges within the first preset time period into a line segment or multiple continuous line segments;

[0020] Obtaining the slope of each of the line segments;

[0021] According to the slope of each line segment, the change rate of the SOC consistency parameter value of multiple charges within the first preset time period is obtained. In this way, the change rate of the SOC consistency parameter value obtained is more accurate.

[0022] In some embodiments of the present application, before comparing the SOC consistency parameter value of each charge within the first preset time with the first threshold, the method further includes:

[0023] Acquire, on the line segment or the plurality of continuous line segments, an SOC consistency parameter value corresponding to each charging time point within the first preset time period, to obtain a filtered SOC consistency parameter value;

[0024] The filtered SOC consistency parameter value is used to update the SOC consistency parameter value corresponding to the first preset time period, which can improve the accuracy of the SOC consistency parameter value and help improve the accuracy of the battery consistency evaluation result.

[0025] In some embodiments of the present application, the method further comprises:

[0026] When the consistency of the battery is determined to be abnormal, an early warning message is issued, so that relevant staff can be reminded to take corresponding treatment measures in time to reduce safety hazards caused by battery over-discharge or abnormal self-discharge.

[0027] In some embodiments of the present application, obtaining the corresponding relationship model includes:

[0028] Constructing an initial model, wherein an output of the initial model is equal to a difference between a first coefficient and a first product, wherein the first product is a product of a second coefficient and a first value, wherein the first value is a logarithm of an input of the initial model with a natural constant as a base;

[0029] The minimum cell voltage in the offline calibration data is used as the input of the initial model, and the SOC consistency parameter value in the offline calibration data is used as the output of the initial model. The value of the first coefficient and the value of the second coefficient are obtained by fitting, and a corresponding relationship model between the minimum cell voltage and the SOC consistency parameter value is obtained; the offline calibration data includes multiple data pairs, and each data pair includes a corresponding minimum cell voltage and SOC consistency parameter value. In this way, a corresponding relationship model that can more accurately characterize the relationship between the minimum cell voltage and the SOC consistency parameter value can be obtained, which is helpful to obtain a more accurate SOC consistency parameter value based on the minimum cell voltage.

[0030] In some embodiments of the present application, constructing the initial model includes:

[0031] According to the polarization characteristics of the voltage curve of the battery during charging, an initial model of the correspondence between the minimum cell voltage and the SOC consistency parameter value in the fully charged state of the battery is established. Based on the initial model, a corresponding relationship model that can more accurately characterize the relationship between the minimum cell voltage and the SOC consistency parameter value can be obtained.

[0032] In some embodiments of the present application, before evaluating the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges, the method further includes:

[0033] For each of the target minimum cell voltages, determining whether there is a static SOC consistency parameter value within a time period of a second preset time from the acquisition time, the static SOC consistency parameter value being obtained by discharging the battery to a preset SOC interval and leaving it at rest for at least a third preset time;

[0034] If the static SOC consistency parameter value exists, using the static SOC consistency parameter value to update the SOC consistency parameter value corresponding to the target minimum cell voltage;

[0035] If the static SOC consistency parameter value does not exist, the SOC consistency parameter value corresponding to the target minimum cell voltage is not updated.

[0036] The static SOC consistency parameter value is more accurate. When the static SOC consistency parameter value exists, using the static SOC consistency parameter value to update the SOC consistency parameter value corresponding to the target minimum cell voltage can further improve the accuracy of the SOC consistency parameter value, which helps to further improve the accuracy of the battery consistency evaluation results.

[0037] In some embodiments of the present application, the method further comprises:

[0038] When the number of updates reaches the preset number of times, the model parameters of the pre-acquisition model are updated using the updated SOC consistency parameter value and the target minimum cell voltage corresponding to the updated SOC consistency parameter value to obtain an updated pre-acquisition model. In this way, the accuracy of the pre-acquisition model in characterizing the relationship between the minimum cell voltage and the SOC consistency parameter value can be further improved, which helps to further improve the accuracy of the SOC consistency parameter value obtained according to the minimum cell voltage.

[0039] In some embodiments of the present application, obtaining the static SOC consistency parameter value includes:

[0040] Discharging the battery to a preset SOC range and leaving it to stand for at least the third preset time period;

[0041] Obtaining a maximum cell voltage and a minimum cell voltage of the battery after being left at rest;

[0042] The corresponding relationship curve between the open circuit voltage and the SOC of the battery cell is queried according to the maximum battery cell voltage after standing still and the minimum battery cell voltage after standing still, and the static SOC consistency parameter value is obtained. The static SOC consistency parameter value has higher accuracy.

[0043] In some embodiments of the present application, for each of the data sets, obtaining the target minimum cell voltage in the data set includes:

[0044] For each of the data sets, compare the first voltage value in the data set with the preset full charge voltage threshold, so as to determine whether there is a first voltage value not less than the preset full charge voltage threshold in each data set; the first voltage value is the maximum value of the maximum cell voltage of each cell in the battery;

[0045] For each of the data sets, if the first voltage value is not less than the preset full-charge voltage threshold, then recording the minimum cell voltage in the data set that is not less than the preset voltage and has the latest collection time;

[0046] For each of the data sets, if the first voltage value is less than the preset full-charge voltage threshold, the minimum cell voltage in the data set is not recorded.

[0047] In this way, the minimum cell voltage that is not less than the preset voltage and has the latest collection time can be obtained from the data set that satisfies the first voltage value not less than the preset full charge voltage threshold. The SOC consistency parameter value corresponding to the minimum cell voltage can more accurately reflect the battery consistency, which helps to improve the accuracy of the battery consistency evaluation results.

[0048] According to a second aspect of an embodiment of the present application, a battery consistency assessment device is provided, comprising:

[0049] A historical charging condition data set acquisition module, used to acquire multiple historical charging condition data sets of multiple charging of the battery, wherein the multiple charging times correspond to the multiple historical charging condition data sets one by one;

[0050] A target minimum cell voltage acquisition module is used to acquire, for each of the data sets, a target minimum cell voltage in the data set, where the target minimum cell voltage is a minimum cell voltage that is not less than a preset voltage and has the latest acquisition time;

[0051] An SOC consistency parameter value acquisition module, used for inputting each of the target minimum cell voltages into a pre-acquisition model to obtain a corresponding SOC consistency parameter value; the model is a correspondence relationship model between the minimum cell voltage and the SOC consistency parameter value;

[0052] A battery consistency evaluation module is used to evaluate the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges.

[0053] The second aspect of the embodiment of the present application can achieve the same beneficial technical effect as the first aspect of the embodiment of the present application.

[0054] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the battery consistency evaluation method described in any embodiment of the present application.

[0055] The third aspect of the embodiment of the present application can achieve the same beneficial technical effect as the first aspect of the embodiment of the present application.

[0056] According to a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program is executed by a processor to implement the battery consistency evaluation method described in any embodiment of the present application.

[0057] The fourth aspect of the embodiment of the present application can achieve the same beneficial technical effect as the first aspect of the embodiment of the present application.

[0058] The above description is only an overview of the technical solution of the embodiment of the present application. In order to more clearly understand the technical means of the embodiment of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] By reading the detailed description of the following embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The accompanying drawings are only used to illustrate the embodiments of the present application and are not to be considered as limitations of the present application. In addition, the same reference numerals are used to represent the same components throughout the drawings.

[0060] Figure 1 is a schematic diagram of the structure of a vehicle according to one or more embodiments.

[0061] Figure 2 The present invention is a flow chart of a battery consistency evaluation method according to one or more embodiments.

[0062] Figure 3 The diagram is a schematic diagram of multiple sampling points obtained by sampling the charging voltage during the charging process according to one or more embodiments.

[0063] Figure 4Schematic diagram of multiple corresponding points between minimum cell voltage and SOC consistency parameter values ​​obtained through offline calibration according to one or more embodiments.

[0064] Figure 5 A flow chart of evaluating battery consistency based on SOC consistency parameter values ​​of multiple charges according to one or more embodiments is provided.

[0065] Figure 6 It is a schematic diagram of three continuous line segments obtained by fitting in a preset coordinate system according to one or more embodiments.

[0066] Figure 7 FIG. 4 is a structural block diagram of a battery consistency evaluation device according to one or more embodiments.

[0067] Figure 8 is a structural block diagram of an electronic device according to one or more embodiments.

[0068] Fig. 9 FIG. 1 is a schematic diagram of a computer-readable storage medium according to one or more embodiments.

[0069] The meanings of the reference numerals in the above drawings are as follows:

[0070] 1000: vehicle, 100: battery, 200: controller, 300: motor; 40: electronic device; 400: processor; 401: memory; 402: bus; 403: communication interface; 50: optical disk. DETAILED DESCRIPTION

[0071] The following embodiments of the technical solution of the present application are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0072] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0073] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two (including two), unless otherwise clearly and specifically defined.

[0074] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0075] In order to further promote energy conservation and emission reduction and sustainable economic development, new energy technology has become one of the rapidly developing hot technology fields. With the development of new energy technology, batteries, especially power batteries, have broad development prospects and have been increasingly widely used in new energy vehicles, consumer electronics, energy storage systems and other technical fields. Power batteries have the advantages of high power, high energy density, good environmental protection effect, etc., and have huge market application prospects.

[0076] Battery consistency is one of the important performance indicators of batteries. Battery consistency refers to the differences in many parameters (such as voltage, charge, capacity and its decay rate, internal resistance and its change rate, life, temperature influence, self-discharge rate, etc.) of these single cells when the single cells of the same specifications and models are combined into a battery pack. The importance of battery consistency assessment lies in ensuring battery pack performance, extending battery pack life, improving safety, and optimizing the efficiency of the energy storage system.

[0077] Good consistency can ensure that the parameters such as voltage, current and capacity of each single cell of the battery pack remain relatively stable during the charging and discharging process, thereby improving the overall performance of the battery pack. For example, in electric vehicles, the consistency of the battery pack is directly related to the vehicle's cruising range, acceleration performance and safety. If the consistency is poor, some batteries in the battery pack may reach the charge and discharge limit prematurely, thereby limiting the capacity and power output of the entire battery pack and affecting the overall performance of the battery pack. In addition, the stress distribution of each battery in a battery pack with good consistency is relatively uniform during the charging and discharging process, which can reduce the difference in the aging speed of the battery, thereby extending the overall life of the battery pack. In energy storage systems, the life of the battery pack is a key indicator, and good consistency can reduce maintenance costs and replacement frequency. The importance of battery consistency is also reflected in safety. Batteries with low consistency are prone to safety hazards during use, which may lead to serious consequences such as explosion or fire, causing casualties and property losses.

[0078] Therefore, it is very important to conduct battery consistency evaluation, which helps to ensure the quality and performance of the battery pack, improve the efficiency and safety of the battery, and is of great significance for ensuring the long-term stable operation of battery equipment.

[0079] The method used in the related art to estimate the consistency of power batteries requires that the battery be discharged to a lower SOC state and then left to stand for a long time before estimation can be performed. There are fewer computing opportunities. Therefore, more conditions need to be met to obtain battery consistency evaluation results using this method, which is more difficult to implement and has fewer applicable scenarios.

[0080] In response to the problems existing in the related art, an embodiment of the present application provides a battery consistency evaluation method, which obtains multiple historical charging condition data sets of multiple charging of the battery, wherein the multiple charging is one-to-one corresponding to the multiple historical charging condition data sets, and then for each of the data sets, obtains the target minimum cell voltage in the data set, the target minimum cell voltage is the minimum cell voltage that is not less than a preset voltage and has the latest collection time, and inputs each target minimum cell voltage into a pre-acquisition model to obtain a corresponding SOC consistency parameter value, which is a correspondence model between the minimum cell voltage and the SOC consistency parameter value, and evaluates the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charging. The method corresponds to more calculation opportunities, requires fewer conditions during implementation, is easy to implement, and has a wide range of applicable scenarios. To a large extent, it overcomes the defects of the related art of evaluating the battery consistency by discharging the battery to a low SOC state and letting it stand for a sufficient period of time, which requires more conditions to be met, is more difficult to implement, and has fewer applicable scenarios.

[0081] The battery disclosed in the embodiment of the present application can be used in, but is not limited to, electrical devices such as vehicles, ships or aircraft. For the convenience of description, the following embodiments are described by taking a vehicle 1000 as an electrical device in an embodiment of the present application.

[0082] Please refer to Figure 1 , Figure 1 A schematic diagram of the structure of a vehicle 1000 provided for some embodiments of the present application. The vehicle 1000 may be a fuel vehicle, a gas vehicle or a new energy vehicle, and the new energy vehicle may be a pure electric vehicle, a hybrid vehicle or an extended-range vehicle, etc. A battery 100 is provided inside the vehicle 1000, and the battery 100 may be provided at the bottom, head or tail of the vehicle 1000. The battery 100 may be used to power the vehicle 1000, for example, the battery 100 may be used as a driving power source for the vehicle 1000, replacing or partially replacing fuel or natural gas to provide driving power for the vehicle 1000. The vehicle 1000 may also include a controller 200 and a motor 300, and the controller 200 is used to control the battery 100 to power the motor 300, for example, for the starting, navigation and working power requirements of the vehicle 1000 during driving. In addition, the battery 100 may be used not only as a driving power source for the vehicle 1000, but also as an operating power source for the vehicle 1000.

[0083] The battery of the embodiment of the present application includes but is not limited to lithium iron phosphate battery, lithium battery, ternary lithium battery, nickel metal hydride battery and lead-acid battery, etc. The battery of the embodiment of the present application includes but is not limited to battery pack, battery group, battery module, etc.

[0084] A battery consistency evaluation method proposed according to an embodiment of the present application is described below in conjunction with the accompanying drawings.

[0085] refer to Figure 2 As shown, an embodiment of the present application provides a battery consistency evaluation method, which may include steps S10 to S40:

[0086] S10. Acquire multiple historical charging condition data sets of multiple battery charges.

[0087] The multiple charging steps correspond one to one to the multiple historical charging condition data sets.

[0088] The battery may include multiple battery cells or multiple single cells. For example, the battery can be used to provide power for a vehicle and obtain background data of the vehicle from the cloud. The background data includes information such as the maximum cell voltage, minimum cell voltage, current, temperature, displayed SOC, charging time, and charging status flag of the battery.

[0089] During each battery charging process, the battery management system BMS collects battery charging condition information once every first preset time length (the first preset time length may be, for example, 10 seconds), obtains a data frame, and sends the data frame to the cloud for storage. Figure 3 As shown, Figure 3 A schematic diagram of multiple sampling points obtained by sampling the charging voltage during the charging process in an example is shown, each sampling point corresponds to a data frame, wherein the abscissa is the sampling time of the charging process data frame, and the ordinate is the charging voltage.

[0090] The background data is preprocessed by sorting them in order of charging time, removing duplicate values, removing abnormal values ​​(for example, the normal value range of SOC is between 0 and 100%. If it exceeds this range, it is considered an abnormal value. The voltage and current values ​​of 65535, which are invalid values ​​by default, are also abnormal values), and removing missing values ​​(missing values, such as empty data in the voltage column, current column, and charging time column).

[0091] Extract multiple historical charging condition data sets of multiple battery charging from the pre-processed background data. Each historical charging condition data set includes the maximum cell voltage, minimum cell voltage, current, temperature, displayed SOC, charging time, charging status flag and other information of the corresponding single charging operation.

[0092] Exemplarily, all data frames with a charging status flag of 1 are screened out from the pre-processed background data, and each data frame includes information such as maximum cell voltage, minimum cell voltage, current, temperature, displayed SOC, charging time, charging status flag, etc. All screened data frames are still sorted in order of charging time.

[0093] All the filtered data frames are divided according to the charging time. If the charging time interval between two data frames with adjacent charging times is greater than a second preset time length (the second preset time length is, for example, 1 hour), the two data frames are divided into two historical charging condition data sets. After the division is completed, multiple historical charging condition data sets are obtained, and each historical charging condition data set contains multiple data frames.

[0094] S20: For each data set, obtain a target minimum cell voltage in the data set.

[0095] The target minimum cell voltage is the minimum cell voltage that is not less than the preset voltage and is collected at the latest time.

[0096] Exemplarily, for each data set, obtaining the minimum cell voltage in the data set that is not less than the preset voltage and has the latest collection time may include: for each data set, comparing the first voltage value in the data set with the preset full charge voltage threshold, so as to determine whether there is a first voltage value that is not less than the preset full charge voltage threshold in each data set; the first voltage value is the maximum value of the maximum cell voltage of each cell in the battery; for each data set, if the first voltage value is not less than the preset full charge voltage threshold, then recording the minimum cell voltage in the data set that is not less than the preset voltage and has the latest collection time; for each data set, if the first voltage value is less than the preset full charge voltage threshold, then not recording the minimum cell voltage in the data set. In this way, the minimum cell voltage that is not less than the preset voltage and has the latest collection time can be obtained from the data set that satisfies the first voltage value that is not less than the preset full charge voltage threshold, and the SOC consistency parameter value corresponding to the minimum cell voltage can more accurately reflect the battery consistency, which helps to improve the accuracy of the battery consistency evaluation result.

[0097] Specifically, for a data set, first detect whether the maximum value of the maximum cell voltage of all data frames in the data set is greater than or equal to the preset full charge voltage threshold V (the preset full charge voltage threshold V can be, for example, 3.65V). If so, determine the last frame of all data frames in the data set that are greater than or equal to the preset full charge voltage threshold V (the last frame is the data frame with the latest collection time), extract the minimum cell voltage of the last frame, and obtain the target minimum cell voltage of the data set. If not, detect the next data set until all data sets are detected.

[0098] S30 , input each target minimum cell voltage into the pre-acquisition model to obtain a corresponding SOC consistency parameter value.

[0099] This model is a correspondence model between the minimum cell voltage and the SOC consistency parameter value, and is acquired in advance.

[0100] Exemplarily, obtaining a correspondence model may include: constructing an initial model, wherein the output of the initial model is equal to the difference between a first coefficient and a first product, the first product being the product of a second coefficient and a first value, the first value being the logarithm of the input of the initial model with a natural constant as the base; using the minimum cell voltage in the offline calibration data as the input of the initial model, using the SOC consistency parameter value in the offline calibration data as the output of the initial model, fitting to obtain the value of the first coefficient and the value of the second coefficient, and obtaining a correspondence model between the minimum cell voltage and the SOC consistency parameter value; the offline calibration data includes a plurality of data pairs, each data pair including a minimum cell voltage and an SOC consistency parameter value that correspond to each other.

[0101] Specifically, constructing the initial model may include: establishing an initial model of the correspondence between the minimum cell voltage and the SOC consistency parameter value in the fully charged state of the battery according to the polarization characteristics of the voltage curve of the battery's charging process. Based on the initial model, a corresponding relationship model that can more accurately characterize the relationship between the minimum cell voltage and the SOC consistency parameter value can be obtained. The polarization characteristics of the voltage curve of the battery's charging process can be represented by the battery's charging polarization curve, which is a curve that describes the relationship between the electrochemical reaction occurring on the electrode during the charging process of the battery and the corresponding current and voltage. During the charging process, as the charge accumulates, the potential of the electrode will change, and at the same time, a certain polarization phenomenon will occur on the electrode, which is manifested as an increase in voltage. When the current density is constant, there is a linear relationship between the electrode potential and the corresponding current, which can be expressed as a polarization curve.

[0102] In one example, the SOC consistency difference data corresponding to the minimum cell voltage value when the maximum cell voltage reaches the full charge voltage threshold is obtained through offline calibration, and the initial model of minimum voltage and SOC consistency is established based on the polarization characteristics of the voltage curve during the charging process of the lithium iron phosphate battery. The formula of the initial model is:

[0103] , formula 1;

[0104] Among them, output Y is the SOC consistency parameter value, input X is the minimum cell voltage, and A and B are model parameters.

[0105] The voltage and current data of the entire charging process are collected. The full charge voltage threshold is related to the battery cell system. For lithium iron phosphate batteries, it is generally considered that the full charge state is when the maximum voltage reaches 3.65V at a current of 0.05*the standard capacity of the battery pack.

[0106] refer to Figure 4 As shown, Figure 4 It is a schematic diagram of multiple corresponding points between the minimum cell voltage and the SOC consistency parameter value obtained through offline calibration, and the parameters of each corresponding point include the minimum cell voltage and the corresponding SOC consistency parameter value.

[0107] During offline calibration, through cell testing, the consistency parameter values ​​of the battery are adjusted to 4%SOC, 3.5%SOC, 3%SOC, 2.5%SOC, and 2%SOC respectively through cell balanced discharge. When the maximum cell voltage is charged to 3.65V, the minimum cell voltage corresponding to different SOC consistency parameter values ​​is obtained. The data is shown in Table 1, which is a mapping table for offline calibration.

[0108] Table 1

[0109]

[0110] The data in Table 1 are used to fit Formula 1, and the corresponding parameters A and B are obtained by fitting, thereby obtaining a corresponding relationship model between the minimum cell voltage and the SOC consistency parameter value.

[0111] The SOC consistency parameter value represents the SOC consistency difference. For example, when the maximum cell voltage reaches 3.65V, if the minimum cell voltage is 3.4V, then the minimum cell voltage 3.4V is substituted into the formula of the corresponding relationship model, and the SOC consistency parameter value of the maximum cell voltage and the minimum cell voltage can be calculated to be 3%, that is, the SOC consistency difference is 3%.

[0112] Substitute the target minimum cell voltage value as input into the formula of the SOC consistency model, and calculate the SOC consistency parameter value of the output battery through the formula, which is recorded as SOC_diff_min;

[0113] For example, substituting the target minimum cell voltage value of 3.4V into the formula, the SOC consistency parameter value is calculated to be 3%.

[0114] S40: Evaluate battery consistency according to the SOC consistency parameter values ​​of the multiple charges.

[0115] refer to Figure 2 As shown, in some embodiments, evaluating the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges may include:

[0116] S401. Obtain a change rate of the SOC consistency parameter value of multiple charges within a first preset time period from the SOC consistency parameter values ​​of the multiple charges.

[0117] The first preset duration is a duration pre-set according to actual application needs, and the first preset duration may be a period of time from the current moment to the preset duration. For example, the first preset duration may be a period of the last 7 days.

[0118] S402: Compare the SOC consistency parameter value of each charge within the first preset time with the first threshold, and compare the change rate with the second threshold.

[0119] S403: When the SOC consistency parameter value of at least one charge within the first preset time period is greater than the first threshold or the rate of change is greater than the second threshold, determine that the battery consistency is abnormal.

[0120] S404: When the SOC consistency parameter values ​​of multiple charges within the first preset time period are not greater than the first threshold and the rate of change is not greater than the second threshold, determine that the battery consistency is normal.

[0121] By evaluating the consistency of the battery according to the SOC consistency parameter value and its change rate within the first preset time period, and taking the SOC consistency parameter value and its change rate as the evaluation basis, a more accurate battery consistency evaluation result can be obtained.

[0122] Exemplarily, obtaining the change rate of the SOC consistency parameter value of multiple charges within a first preset time from the SOC consistency of the multiple charges may include:

[0123] S4011, acquiring SOC consistency parameter values ​​of multiple charges within a first preset time period from the SOC consistency parameter values ​​of the multiple charges;

[0124] S4012, in a preset coordinate system with time as the horizontal axis and the SOC consistency parameter value as the vertical axis, fitting the SOC consistency parameter values ​​of multiple charges within a first preset time period into a line segment or multiple continuous line segments;

[0125] refer to Figure 6 As shown, Figure 6 Three continuous line segments obtained by fitting in a preset coordinate system are shown.

[0126] S4013, obtaining the slope of each line segment;

[0127] S4014: Obtain the change rate of the SOC consistency parameter value of multiple charges within the first preset time period according to the slope of each line segment. In this way, the change rate of the SOC consistency parameter value obtained is more accurate.

[0128] Exemplarily, based on the slope of each line segment, obtaining the rate of change of the SOC consistency parameter value of multiple charges within the first preset time period can include: using the maximum slope among the slopes of each line segment, the average value of the slopes of each line segment, or the slope of the line segment closest in time as the rate of change of the SOC consistency parameter value of multiple charges within the first preset time period.

[0129] Exemplarily, before comparing the SOC consistency parameter value of each charge within the first preset time length with the first threshold value, the method may further include: obtaining the SOC consistency parameter value corresponding to the charging time point of each charge within the first preset time length on a fitted line segment or a plurality of continuous line segments to obtain a filtered SOC consistency parameter value; and using the filtered SOC consistency parameter value to update the corresponding SOC consistency parameter value within the first preset time length. In this way, the accuracy of the SOC consistency parameter value can be improved, which helps to improve the accuracy of the battery consistency evaluation result.

[0130] Exemplarily, the SOC consistency parameter value within a preset time window is extracted from the SOC consistency parameter values ​​of the aforementioned multiple charges, and a piecewise linear regression fitting is performed on the SOC consistency parameter value within the time window using a data-driven algorithm such as linear regression to obtain a regression value SOC_diff_curr of the SOC consistency parameter value within the time window.

[0131] The change of the SOC consistency parameter value is continuous and linear within a certain period of time. Data-driven algorithms such as linear regression can be used to filter and optimize the SOC consistency parameter value within the time window.

[0132] The least squares method can usually be used to find the equation of the linear regression algorithm. The equation of the linear regression algorithm can be expressed as

[0133]

[0134] Where Y is the SOC consistency parameter value output vector (y1,y2,…,y m ), the input X is the output time vector (x1,x2,…,x m ), w and b are the regression fitting parameters.

[0135] The regression fitting parameters w and b are expressed as

[0136]

[0137] in, represents x1,x2,…,x m The average value of represents y1,y2,…,y m The average value of .

[0138] The specific operation method of filtering optimization is:

[0139] The input is each SOC consistency parameter value in the first period, the first period is a period with the current time as the time end and the duration as the time window w days, that is, the SOC consistency parameter value corresponding to each data collection time point in the first period, and the linear regression method is used to calculate each SOC consistency parameter value to obtain the values ​​of the regression fitting parameters w and b of the equation of the linear regression algorithm. The fitting line segment of the linear regression method can be drawn in a pre-set rectangular coordinate system (the horizontal axis of the rectangular coordinate system is time and the vertical axis is the SOC consistency parameter value), and then the SOC consistency parameter value corresponding to each data collection time point in the first period on the fitting line segment is obtained, and it is output as the filtered SOC consistency parameter value.

[0140] In some embodiments, before evaluating the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges, the method may further include:

[0141] Step 1: for each minimum cell voltage, determine whether there is a static SOC consistency parameter value within a time period of a second preset time from the collection time.

[0142] The static SOC consistency parameter value is obtained by discharging the battery to a preset SOC range and leaving it to rest for at least a third preset time. The second preset time can be set to, for example, 7 days, and the third preset time can be set to, for example, 1 hour. Both the second preset time and the third preset time can be set according to actual application needs and are not limited here.

[0143] Step 2: If there is a static SOC consistency parameter value, the static SOC consistency parameter value is used to update the SOC consistency parameter value corresponding to the minimum cell voltage;

[0144] If there is no static SOC consistency parameter value, the SOC consistency parameter value corresponding to the target minimum cell voltage is not updated.

[0145] The static SOC consistency parameter value is more accurate. When the static SOC consistency parameter value exists, using the static SOC consistency parameter value to update the SOC consistency parameter value corresponding to the target minimum cell voltage can further improve the accuracy of the SOC consistency parameter value, which helps to further improve the accuracy of the battery consistency evaluation results.

[0146] Step 3: When the number of updates reaches the preset number, the model parameters of the pre-acquisition model are updated using the updated SOC consistency parameter value and the minimum cell voltage corresponding to the updated SOC consistency parameter value to obtain an updated pre-acquisition model. In this way, the accuracy of the pre-acquisition model in characterizing the relationship between the minimum cell voltage and the SOC consistency parameter value can be further improved, which helps to further improve the accuracy of the SOC consistency parameter value obtained according to the minimum cell voltage.

[0147] Exemplarily, assuming that the preset number of times is n, there are n data pairs in total, each data pair includes an updated SOC consistency parameter value and the minimum cell voltage corresponding to the updated SOC consistency parameter value, and the n data pairs can be respectively expressed as <minimum cell voltage v1, SOC consistency parameter value d1>, <minimum cell voltage v2, SOC consistency parameter value d2>,…, <minimum cell voltage vn, SOC consistency parameter value dn>, and the n data pairs are used to adjust the model parameters A and B in the formula of the updated corresponding relationship model to obtain an updated pre-acquisition model.

[0148] Specifically, assuming that the SOC consistency parameter value obtained by the pre-acquisition model is 3%, and the static SOC consistency parameter value is 2.5% within the second preset time period from the collection time, the SOC consistency parameter value of this charging is updated from 3% to 2.5%, and the parameters A and B of the corresponding relationship model are updated.

[0149] The least square method may be used to update the parameters A and B of the corresponding relationship model.

[0150] Regarding the least squares method, assume that there is a pair of observations (x, y) and , , satisfying the following relationship:

[0151]

[0152] in, Parameters to be determined.

[0153] To find the function The optimal estimate of the parameter w of given m sets (usually m>n) of observations , solve the objective function

[0154]

[0155] Parameters to minimize the objective function .

[0156] For unconstrained optimization problems, the general form of least squares is:

[0157]

[0158] in, is called the residual function. This method is the least squares method.

[0159] Exemplarily, obtaining the static SOC consistency parameter value may include: discharging the battery to a preset SOC interval and leaving it to stand for at least a third preset time; obtaining the maximum cell voltage and the minimum cell voltage of the battery after standing still; and querying the corresponding relationship curve between the cell open circuit voltage and the SOC according to the maximum cell voltage and the minimum cell voltage to obtain the static SOC consistency parameter value. The static SOC consistency parameter value has a higher accuracy.

[0160] The curve of the relationship between the open circuit voltage and SOC of the battery cell is also called the OCV-SOC curve. For example, after discharging the battery to below 30% SOC and leaving it for at least 1 hour, query the maximum SOC corresponding to the maximum battery cell voltage and the minimum SOC corresponding to the minimum battery cell voltage from the OCV-SOC curve, and obtain the SOC consistency parameter value based on the maximum SOC and minimum SOC.

[0161] Exemplarily, it can be determined whether the battery is at risk based on the regression value SOC_diff_curr of the SOC consistency parameter value and the change rate SOC_diff_rate of the SOC consistency parameter value.

[0162] The SOC consistency parameter value change rate SOC_diff_rate is the SOC consistency parameter value change rate within the time window w days, that is, the w value obtained in the previous text.

[0163] If SOC_diff_curr>preset threshold C or SOC_diff_rate>preset threshold D, it is determined that the battery has a risk of excessive consistency difference or abnormal cell self-discharge.

[0164] In some embodiments, the method may further include step S50, in which, when it is determined that the battery consistency is abnormal, a warning message is issued. The warning message includes but is not limited to a text message, an audio and visual signal, etc. In this way, relevant staff can be reminded to take corresponding treatment measures in time to reduce safety hazards caused by battery over-discharge or abnormal self-discharge.

[0165] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0166] A specific example of a battery consistency evaluation method may include the following steps:

[0167] Multiple historical charging condition data sets of multiple battery charging are obtained from the cloud, and the multiple charging conditions correspond to the multiple historical charging condition data sets one by one. Each historical charging condition data set contains multiple data frames. Each data frame includes information such as the maximum cell voltage, the minimum cell voltage, the current, the temperature, the displayed SOC, the charging time, and the charging status flag.

[0168] For a data set, first detect whether the maximum value of the maximum cell voltage of all data frames in the data set is greater than or equal to the preset full-charge voltage threshold V (the preset full-charge voltage threshold V in this example is 3.65V). If so, determine the last frame of all data frames in the data set that are greater than or equal to the preset full-charge voltage threshold V (the last frame is the data frame with the latest collection time), extract the minimum cell voltage of the last frame, and obtain the target minimum cell voltage of the data set. If not, detect the next data set until all data sets are detected.

[0169] Input each target minimum cell voltage into the pre-acquisition model to obtain the corresponding SOC consistency parameter value. The target minimum cell voltage is the minimum cell voltage that is not less than the preset voltage and has the latest acquisition time. The formula of the pre-acquisition model is:

[0170] ;

[0171] Among them, output Y is the SOC consistency parameter value, input X is the minimum cell voltage, and A and B are model parameters.

[0172] For each of the target minimum cell voltages, determining whether there is a static SOC consistency parameter value within a time period of a second preset time from the acquisition time, the static SOC consistency parameter value being obtained by discharging the battery to a preset SOC interval and leaving it at rest for at least a third preset time;

[0173] If the static SOC consistency parameter value exists, using the static SOC consistency parameter value to update the SOC consistency parameter value corresponding to the target minimum cell voltage;

[0174] If the static SOC consistency parameter value does not exist, the SOC consistency parameter value corresponding to the target minimum cell voltage is not updated.

[0175] When the number of updates reaches a preset number of times, the model parameters of the pre-acquisition model are updated using the updated SOC consistency parameter value and the target minimum cell voltage corresponding to the updated SOC consistency parameter value to obtain an updated pre-acquisition model.

[0176] From the SOC consistency parameter values ​​of multiple charges, obtain the SOC consistency parameter values ​​of multiple charges within the first preset time; in a preset coordinate system with time as the horizontal axis and the SOC consistency parameter value as the vertical axis, fit the SOC consistency parameter values ​​of multiple charges within the first preset time into a line segment; obtain the slope of the line segment to obtain the rate of change of the SOC consistency parameter values ​​of multiple charges within the first preset time. Compare the SOC consistency parameter value of each charge within the first preset time with the first threshold, and compare the rate of change with the second threshold. If there is at least one SOC consistency parameter value of charge greater than the first threshold or the rate of change greater than the second threshold within the first preset time, determine that the battery consistency is abnormal.

[0177] If the battery consistency is abnormal, an early warning message will be issued, which can remind relevant staff to take corresponding treatment measures in time to reduce safety hazards caused by battery over-discharge or abnormal self-discharge.

[0178] When the maximum cell voltage reaches full charge during the charging process, the battery consistency of a single charge can be estimated when the minimum cell voltage reaches a preset voltage value. During each charging process, if the maximum cell voltage at the end of charging reaches full charge, there is an opportunity to estimate the battery consistency. The SOC consistency relationship corresponding to the cell voltage difference at the full charge moment can be adjusted in combination with other cell consistency acquisition methods (such as the static SOC consistency parameter value acquisition method), which can reduce the error caused by the relationship offset of the aged cell voltage when it reaches full charge.

[0179] The battery consistency evaluation method of this example is simple and easy to implement, has many calculation opportunities, and has a wide range of applications. The method of this example evaluates the battery consistency based on the minimum cell voltage value when the maximum cell voltage reaches the full charge during the charging process, realizes dynamic evaluation of battery consistency, greatly increases the battery consistency calculation opportunity, and can be combined with other consistency estimation methods to provide accurate consistency evaluation results for the battery. The method of this example can correct the calculation results in combination with historical calculation results, reduce the influence of single calculation error noise, and make the calculation results more accurate. It can predict the changing trend of battery consistency parameter values ​​and the changing rate of battery consistency parameter values, realize early warning, and greatly reduce the probability of battery over-discharge, vehicle breakdown, self-discharge abnormality and other problems.

[0180] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0181] refer to Figure 7 As shown, another embodiment of the present application provides a battery consistency evaluation device, comprising:

[0182] A historical charging condition data set acquisition module is used to acquire multiple historical charging condition data sets of multiple charging of the battery, where the multiple charging times correspond to the multiple historical charging condition data sets one by one;

[0183] A target minimum cell voltage acquisition module is used to acquire, for each data set, a target minimum cell voltage in the data set, where the target minimum cell voltage is a minimum cell voltage that is not less than a preset voltage and has the latest acquisition time;

[0184] An SOC consistency parameter value acquisition module, used to input each target minimum cell voltage into a pre-acquisition model to obtain a corresponding SOC consistency parameter value; the model is a correspondence relationship model between the minimum cell voltage and the SOC consistency parameter value;

[0185] The battery consistency evaluation module is used to evaluate the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges.

[0186] Exemplarily, the battery consistency assessment module may include:

[0187] A change rate acquisition unit, used to acquire a change rate of the SOC consistency parameter value of multiple charges within a first preset time period from the aforementioned SOC consistency parameter values ​​of multiple charges;

[0188] A comparison unit, configured to compare the SOC consistency parameter value of each charge within a first preset time period with a first threshold value, and to compare the change rate with a second threshold value;

[0189] A judgment unit, configured to judge that the battery consistency is abnormal when there is at least one charging SOC consistency parameter value greater than a first threshold value or a change rate greater than a second threshold value within a first preset time period;

[0190] The judgment unit is further configured to judge that the battery consistency is normal when the SOC consistency parameter values ​​of multiple charges within a first preset time period are not greater than a first threshold and the rate of change is not greater than a second threshold.

[0191] Exemplarily, the change rate acquisition unit may include:

[0192] An SOC consistency parameter value acquisition subunit is used to acquire the SOC consistency parameter values ​​of multiple charges within a first preset time period from the aforementioned SOC consistency parameter values ​​of multiple charges;

[0193] A fitting subunit, configured to fit the SOC consistency parameter values ​​of multiple charges within a first preset time period into a line segment or a plurality of continuous line segments in a preset coordinate system with time as the horizontal axis and the SOC consistency parameter value as the vertical axis;

[0194] A slope acquisition subunit is used to obtain the slope of each line segment;

[0195] The change rate acquisition subunit is used to obtain the change rate of the SOC consistency parameter value of multiple charges within a first preset time period according to the slope of each line segment.

[0196] Exemplarily, the battery consistency evaluation module may further include a filtering update unit, which is used to obtain the SOC consistency parameter value corresponding to the charging time point of each charging within the first preset time length on the aforementioned line segment or multiple continuous line segments before the comparison unit compares the SOC consistency parameter value of each charging within the first preset time length with the size of the first threshold, and obtain the filtered SOC consistency parameter value; use the filtered SOC consistency parameter value to update the corresponding SOC consistency parameter value within the first preset time length.

[0197] Exemplarily, the device may further include:

[0198] The early warning module is used to issue an early warning message when it is determined that the consistency of the battery is abnormal.

[0199] Exemplarily, the device may further include a corresponding relationship model acquisition module, and the corresponding relationship model acquisition module includes:

[0200] An initial model building unit, used for building an initial model, wherein an output of the initial model is equal to a difference between a first coefficient and a first product, wherein the first product is a product of a second coefficient and a first value, and wherein the first value is a logarithm of an input of the initial model with a natural constant as a base;

[0201] A fitting unit is used to use the minimum cell voltage in the offline calibration data as the input of the initial model, and the SOC consistency parameter value in the offline calibration data as the output of the initial model, to fit the value of the first coefficient and the value of the second coefficient, and to obtain a corresponding relationship model between the minimum cell voltage and the SOC consistency parameter value; the offline calibration data includes multiple data pairs, and each data pair includes a minimum cell voltage and SOC consistency parameter value that correspond to each other.

[0202] Exemplarily, the initial model building unit is further specifically used to establish an initial model of the correspondence between the minimum cell voltage and the SOC consistency parameter value in a fully charged state of the battery according to the polarization characteristics of the voltage curve of the battery during the charging process.

[0203] Exemplarily, the device may further include a judgment updating module, which is used for, before the battery consistency evaluation module evaluates the consistency of the battery according to the SOC consistency parameter values ​​of the aforementioned multiple charges:

[0204] For each target minimum cell voltage, determine whether there is a static SOC consistency parameter value within a second preset time period from the aforementioned acquisition time, where the static SOC consistency parameter value is obtained by discharging the battery to a preset SOC range and leaving it at rest for at least a third preset time period;

[0205] If there is a static SOC consistency parameter value, the static SOC consistency parameter value is used to update the SOC consistency parameter value corresponding to the target minimum cell voltage;

[0206] If there is no static SOC consistency parameter value, the SOC consistency parameter value corresponding to the target minimum cell voltage is not updated.

[0207] Exemplarily, the device may further include:

[0208] The pre-acquisition model update module is used to update the model parameters of the pre-acquisition model using the updated SOC consistency parameter value and the target minimum cell voltage corresponding to the updated SOC consistency parameter value when the number of updates reaches a preset number, so as to obtain an updated pre-acquisition model.

[0209] Exemplarily, the device may also include a static SOC consistency parameter value acquisition module, which is used to obtain a static SOC consistency parameter value; the static SOC consistency parameter value acquisition module is further specifically used to: discharge the battery to a preset SOC range and let it stand for at least a third preset time; obtain the maximum cell voltage and the minimum cell voltage of the battery after standing still; query the corresponding relationship curve between the cell open circuit voltage and the SOC according to the maximum cell voltage and the minimum cell voltage after standing still, and obtain the static SOC consistency parameter value.

[0210] Exemplarily, the target minimum cell voltage acquisition module is further specifically used for:

[0211] For each data set, comparing the first voltage value in the data set with the preset full charge voltage threshold; the first voltage value is the maximum value of the maximum cell voltage of each cell in the battery;

[0212] For each data set, if the first voltage value is not less than the preset full-charge voltage threshold, then the minimum cell voltage in the data set that is not less than the preset voltage and has the latest collection time is recorded;

[0213] For each data set, if the first voltage value is less than the preset full-charge voltage threshold, the minimum cell voltage in the data set is not recorded.

[0214] The battery consistency evaluation device of the embodiment of the present application has more corresponding computer opportunities, requires fewer conditions for implementation, is easy to implement, and has a wide range of applicable scenarios. It largely overcomes the defects of the related art of evaluating the battery consistency by discharging the battery to a low SOC state and letting it stand for a sufficient period of time, which requires more conditions to be met, is more difficult to implement, and has fewer applicable scenarios.

[0215] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0216] Another embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the battery consistency evaluation method of any of the above-mentioned embodiments.

[0217] refer to Figure 8 As shown, the electronic device 40 may include: a processor 400, a memory 401, a bus 402 and a communication interface 403, wherein the processor 400, the communication interface 403 and the memory 401 are connected via the bus 402; the memory 401 stores a computer program that can be run on the processor 400, and when the processor 400 runs the computer program, the battery consistency evaluation method provided in any of the aforementioned embodiments of the present application is executed.

[0218] The memory 401 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the device network element and at least one other network element is realized through at least one communication interface 403 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0219] The bus 402 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory 401 is used to store a program, and the processor 400 executes the program after receiving an execution instruction. The method disclosed in any implementation of the aforementioned embodiment of the present application may be applied to the processor 400, or implemented by the processor 400.

[0220] The processor 400 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 400. The above processor 400 can be a general-purpose processor, which may include a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a readily available programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor to be executed, or the hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 401, and the processor 400 reads the information in the memory 401 and completes the steps of the above method in combination with its hardware.

[0221] The electronic device provided in the embodiment of the present application and the method provided in the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the method adopted, operated or implemented by them.

[0222] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0223] Another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to implement the battery consistency evaluation method of any of the above embodiments. Fig. 9 As shown, the computer-readable storage medium shown is a CD 50 on which a computer program (ie, a program product) is stored. When the computer program is run by a processor, the battery consistency evaluation method provided by any of the aforementioned embodiments will be executed.

[0224] It should be noted that examples of computer-readable storage media may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0225] The computer-readable storage medium provided in the above-mentioned embodiments of the present application and the method provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the method adopted, run or implemented by the application program stored therein.

[0226] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0227] It should be noted that:

[0228] The term "module" is not intended to be limited to a specific physical form. Depending on the specific application, a module can be implemented as hardware, firmware, software, and / or a combination thereof. In addition, different modules can share common components or even be implemented by the same components. There may or may not be clear boundaries between different modules.

[0229] The algorithm and display provided herein are not inherently related to any specific computer, virtual device or other equipment. Various general devices can also be used together with examples based on this. According to the above description, it is obvious to construct the structure required for this type of device. In addition, the application is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the application described herein, and the description made to specific languages ​​above is for the purpose of disclosing the best mode of implementation of the application.

[0230] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0231] The above embodiments only express the implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A battery consistency evaluation method, characterized in that: include: Acquire multiple historical charging condition data sets of multiple charging of the battery, wherein the multiple charging times correspond to the multiple historical charging condition data sets one by one; For each of the data sets, obtaining a target minimum cell voltage in the data set, where the target minimum cell voltage is a minimum cell voltage that is not less than a preset voltage and has the latest acquisition time; Input each of the target minimum cell voltages into a pre-acquisition model to obtain a corresponding SOC consistency parameter value; the model is a correspondence relationship model between the minimum cell voltage and the SOC consistency parameter value; evaluating the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges; Acquiring the corresponding relationship model includes: Constructing an initial model, wherein an output of the initial model is equal to a difference between a first coefficient and a first product, wherein the first product is a product of a second coefficient and a first value, wherein the first value is a logarithm of an input of the initial model with a natural constant as a base; The minimum cell voltage in the offline calibration data is used as the input of the initial model, and the SOC consistency parameter value in the offline calibration data is used as the output of the initial model. The value of the first coefficient and the value of the second coefficient are fitted to obtain a correspondence model between the minimum cell voltage and the SOC consistency parameter value; the offline calibration data includes multiple data pairs, and each data pair includes a minimum cell voltage and SOC consistency parameter value that correspond to each other.

2. The method according to claim 1, characterized in that The step of evaluating the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges includes: Obtaining a change rate of the SOC consistency parameter values ​​of multiple charges within a first preset time period from the SOC consistency parameter values ​​of multiple charges; Comparing the SOC consistency parameter value of each charge within the first preset time with a first threshold, and comparing the change rate with a second threshold; When there is at least one charging SOC consistency parameter value greater than the first threshold or the change rate greater than the second threshold within the first preset time period, determining that the battery consistency is abnormal; When the SOC consistency parameter values ​​of multiple charges within the first preset time period are not greater than the first threshold and the change rate is not greater than the second threshold, it is determined that the consistency of the battery is normal.

3. The method according to claim 2, characterized in that The acquiring, from the SOC consistency of the multiple charges, a change rate of a SOC consistency parameter value of the multiple charges within a first preset time period includes: Obtaining, from the SOC consistency parameter values ​​of the multiple charges, SOC consistency parameter values ​​of the multiple charges within the first preset time period; In a preset coordinate system with time as the horizontal axis and the SOC consistency parameter value as the vertical axis, fitting the SOC consistency parameter values ​​of multiple charges within the first preset time period into a line segment or multiple continuous line segments; Obtaining the slope of each of the line segments; According to the slope of each of the line segments, the change rate of the SOC consistency parameter value of multiple charges within the first preset time period is obtained.

4. The method according to claim 3, characterized in that Before comparing the SOC consistency parameter value of each charge within the first preset time period with the first threshold, the method further includes: Acquire, on the line segment or the plurality of continuous line segments, an SOC consistency parameter value corresponding to each charging time point within the first preset time period, to obtain a filtered SOC consistency parameter value; The filtered SOC consistency parameter value is used to update the SOC consistency parameter value corresponding to the first preset time length.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: When it is determined that the consistency of the battery is abnormal, a warning message is issued.

6. The method according to claim 1, characterized in that The constructing of the initial model comprises: According to the polarization characteristics of the voltage curve of the battery during the charging process, an initial model of the corresponding relationship between the minimum cell voltage and the SOC consistency parameter value in the fully charged state of the battery is established.

7. The method according to any one of claims 1 to 4, characterized in that Before evaluating the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges, the method further includes: For each of the target minimum cell voltages, determining whether there is a static SOC consistency parameter value within a time period of a second preset time from the acquisition time, the static SOC consistency parameter value being obtained by discharging the battery to a preset SOC interval and leaving it at rest for at least a third preset time; If the static SOC consistency parameter value exists, using the static SOC consistency parameter value to update the SOC consistency parameter value corresponding to the target minimum cell voltage; If the static SOC consistency parameter value does not exist, the SOC consistency parameter value corresponding to the target minimum cell voltage is not updated.

8. The method according to claim 7, characterized in that The method further comprises: When the number of updates reaches a preset number of times, the model parameters of the pre-acquisition model are updated using the updated SOC consistency parameter value and the target minimum cell voltage corresponding to the updated SOC consistency parameter value to obtain an updated pre-acquisition model.

9. The method according to claim 7, characterized in that: Obtaining the static SOC consistency parameter value includes: Discharging the battery to a preset SOC range and leaving it to stand for at least the third preset time period; Obtaining a maximum cell voltage and a minimum cell voltage of the battery after being left at rest; The corresponding relationship curve between the open circuit voltage of the battery cell and the SOC is queried according to the maximum battery cell voltage after standing still and the minimum battery cell voltage after standing still, so as to obtain the consistency parameter value of the standing SOC.

10. The method according to any one of claims 1 to 4, characterized in that For each of the data sets, obtaining a target minimum cell voltage in the data set includes: For each of the data sets, comparing a first voltage value in the data set with a preset full-charge voltage threshold; the first voltage value is the maximum value of the maximum cell voltage of each cell in the battery; For each of the data sets, if the first voltage value is not less than the preset full-charge voltage threshold, then recording the minimum cell voltage in the data set that is not less than the preset voltage and has the latest collection time; For each of the data sets, if the first voltage value is less than the preset full-charge voltage threshold, the minimum cell voltage in the data set is not recorded.

11. A battery consistency evaluation device, characterized in that: include: A historical charging condition data set acquisition module, used to acquire multiple historical charging condition data sets of multiple charging of the battery, wherein the multiple charging times correspond to the multiple historical charging condition data sets one by one; A target minimum cell voltage acquisition module is used to acquire, for each of the data sets, a target minimum cell voltage in the data set, where the target minimum cell voltage is a minimum cell voltage that is not less than a preset voltage and has the latest acquisition time; An SOC consistency parameter value acquisition module, used for inputting each of the target minimum cell voltages into a pre-acquisition model to obtain a corresponding SOC consistency parameter value; the model is a correspondence relationship model between the minimum cell voltage and the SOC consistency parameter value; A battery consistency evaluation module, used to evaluate the consistency of the battery according to the SOC consistency parameter values ​​of the multiple charges; The acquisition module of the corresponding relationship model includes: An initial model building unit, used for building an initial model, wherein an output of the initial model is equal to a difference between a first coefficient and a first product, wherein the first product is a product of a second coefficient and a first value, and the first value is a logarithm of an input of the initial model with a natural constant as a base; A fitting unit is used to use the minimum cell voltage in the offline calibration data as the input of the initial model, and the SOC consistency parameter value in the offline calibration data as the output of the initial model, to fit the value of the first coefficient and the value of the second coefficient, and obtain a corresponding relationship model between the minimum cell voltage and the SOC consistency parameter value; the offline calibration data includes a plurality of data pairs, and each of the data pairs includes a minimum cell voltage and a SOC consistency parameter value that correspond to each other.

12. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the battery consistency evaluation method according to any one of claims 1 to 10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement the battery consistency evaluation method according to any one of claims 1 to 10.

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