Method for determining state of health of battery, method for determining battery charging and discharging strategy, and apparatus

Abstract

The present application provides a method for determining the state of health of a battery, a method for determining a battery charging and discharging strategy, and an apparatus. A specific implementation of the method for determining the state of health of a battery comprises: determining respective predicted voltages of a battery to be processed, at prediction moments and under multiple battery capacities; on the basis of each of the predicted voltages and a measured voltage of said battery at each of the prediction moments, obtaining multiple voltage residuals; determining a target voltage residual that satisfies a voltage residual requirement from among the multiple voltage residuals; on the basis of the multiple battery capacities, determining a first target battery capacity corresponding to the target voltage residual; and on the basis of the first target battery capacity and a rated capacity of said battery, determining the state of health of said battery. The method can conveniently and accurately determine the state of health of batteries in a wide range of application scenarios.

Description

Battery health state determination method, battery charging and discharging strategy determination method and device Cross-reference to Related Applications

[0001] This application claims priority to Chinese Patent Application No. 202411246682.4, filed on September 5, 2024, entitled “Battery health state determination method, battery charging and discharging strategy determination method and device”, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0002] The present application relates to the technical field of batteries, in particular to a battery health state determination method, a battery charging and discharging strategy determination method and device. BACKGROUND

[0003] A battery can provide power for an electronic device, and its health state can affect the performance and life of the battery. The health state of the battery can be described by SOH (state of health), so it is often necessary to determine the SOH of the battery.

[0004] In related technologies, there are two-point method, data-driven method, and method based on battery mechanism model to determine SOH. However, the two-point method requires the battery to be in a condition close to full charge or full discharge, which occurs less frequently, resulting in fewer opportunities to calculate SOH. The data-driven method requires a large amount of sample data for training and migration, so it is difficult to determine SOH using it. The method based on the battery mechanism model needs to consider the error caused by the battery mechanism model, so the accuracy of the SOH calculated based on it is low.

[0005] Therefore, in related technologies, the accuracy of the SOH of the battery is low, and the application scenarios are limited, so it is not convenient to accurately determine the health state of the battery. SUMMARY

[0006] The purpose of the embodiments of the present application is to provide a battery health state determination method, a battery charging and discharging strategy determination method and device, which can facilitate and accurately determine the health state of the battery in more application scenarios.

[0007] In a first aspect, an embodiment of the present application provides a battery state of health determination method, which comprises: determining a predicted voltage of a to-be-processed battery at a plurality of battery capacities respectively at a predicted time; obtaining a plurality of voltage residuals according to each predicted voltage and a measured voltage of the to-be-processed battery at each predicted time; determining a target voltage residual that meets a voltage residual requirement from the plurality of voltage residuals; determining a first target battery capacity corresponding to the target voltage residual according to the plurality of battery capacities; and determining a state of health of the to-be-processed battery according to the first target battery capacity and a rated capacity of the to-be-processed battery. In this way, voltage information can be collected under any working condition, a smaller voltage residual means a smaller error of SOH, and the calculation process is simple, so the state of health of the battery can be determined conveniently and accurately in more application scenarios.

[0008] Optionally, the determining of the predicted voltage of the to-be-processed battery at a plurality of battery capacities respectively at a predicted time comprises: for each battery capacity, determining a corresponding predicted voltage of the to-be-processed battery at the battery capacity according to the battery capacity and a plurality of groups of battery parameters in a preset period. In this way, the obtaining of the plurality of voltage residuals according to each predicted voltage and the measured voltage of the to-be-processed battery at each predicted time comprises: for each predicted voltage, determining a voltage difference between the predicted voltage and the measured voltage of the to-be-processed battery at the predicted time; and determining the voltage residual according to a plurality of voltage differences determined in the preset period. In this way, the accuracy of the voltage residual can be improved, thereby improving the accuracy of the state of health of the to-be-processed battery in the preset period.

[0009] Optionally, the determining of the predicted voltage of the to-be-processed battery at a plurality of battery capacities respectively at a predicted time comprises: determining the predicted voltage of the to-be-processed battery at a plurality of battery capacities respectively based on a Kalman filtering algorithm. In this way, the predicted voltage can be determined more accurately through the Kalman filtering algorithm.

[0010] Optionally, the determining of the state of health of the to-be-processed battery according to the first target battery capacity and the rated capacity of the to-be-processed battery comprises: determining a first state of health value of the to-be-processed battery according to the first target battery capacity and the rated capacity of the to-be-processed battery; and determining the state of health of the to-be-processed battery according to the first state of health value. In this way, voltage information of the to-be-processed battery can be collected under most working conditions, so that the first state of health value can be determined under most working conditions. Therefore, the state of health of the to-be-processed battery can be determined according to the first state of health value under more working conditions, thereby reducing the application limitations caused by working conditions.

[0011] Optionally, the determining the state of health of the battery to be processed according to the first target battery capacity and the rated capacity of the battery to be processed further comprises: determining the state of health of the battery to be processed according to the first state of health value and a second state of health value. Compared with the above implementation manner of determining the state of health of the battery to be processed based on the first state of health value alone, the state of health of the battery to be processed is determined jointly based on the first state of health value and the second state of health value in this implementation manner. In this way, the error of a single state of health value can be reduced, thereby improving the accuracy of the determined state of health.

[0012] Optionally, the second state of health value is determined according to the SOC of the battery to be processed and / or according to the attenuation degree of the battery to be processed. In this way, the second state of health value can be determined according to the SOC and / or the attenuation degree of the battery to be processed, so as to improve the accuracy of the state of health of the battery to be processed.

[0013] Optionally, the second state of health value is determined according to the SOC of the battery to be processed, and before the determining the state of health of the battery to be processed according to the first state of health value and the second state of health value, the method further comprises: determining a predicted SOC corresponding to each of a plurality of battery capacities of the battery to be processed; for each of the predicted SOCs, determining an SOC residual according to the predicted SOC and a corrected SOC; determining a target SOC residual satisfying an SOC residual requirement from a plurality of SOC residuals; determining a second target battery capacity corresponding to the target SOC residual according to the plurality of battery capacities; and determining the second state of health value of the battery to be processed according to the second target battery capacity and the rated capacity of the battery to be processed. In this way, since the SOC of the battery to be processed can be collected under part of the working conditions of the battery to be processed, the state of health of the battery to be processed can be determined in combination with the SOC, and compared with the implementation manner of determining the state of health of the battery to be processed using only the first state of health value, the accuracy of the state of health can be further improved.

[0014] Optionally, the determining the predicted SOC corresponding to each of the plurality of battery capacities of the battery to be processed comprises: determining the predicted SOC corresponding to each of the plurality of battery capacities of the battery to be processed based on a Kalman filtering algorithm. In this way, the Kalman filtering algorithm can be used to determine a more accurate predicted SOC under more application scenarios.

[0015] Optionally, before the determining the SOC residual according to the predicted SOC and the corrected SOC for each of the predicted SOCs, the method further comprises: if the to-be-processed battery satisfies a first correction condition and / or a second correction condition, determining the SOC corresponding to the to-be-processed battery when the correction condition is satisfied as the corrected SOC; wherein the first correction condition comprises that the to-be-processed battery is fully charged or fully discharged; and the second correction condition comprises that the to-be-processed battery is stationary for a duration exceeding a preset duration threshold. In this way, the corrected SOC can be determined in more application scenarios, thereby facilitating the determination of the health state of the to-be-processed battery.

[0016] Optionally, if the to-be-processed battery satisfies the first correction condition and / or the second correction condition, the SOC corresponding to the to-be-processed battery when the correction condition is satisfied is determined as the corrected SOC, comprising: if the to-be-processed battery satisfies the first correction condition and / or the second correction condition multiple times within a preset period, determining the open-circuit voltage corresponding to the to-be-processed battery each time the correction condition is satisfied; for each open-circuit voltage, determining a candidate SOC corresponding to the to-be-processed battery according to the open-circuit voltage; and determining the corrected SOC from the multiple candidate SOCs according to the rate of change of the open-circuit voltage with the candidate SOC. In this way, a more accurate corrected SOC can be determined within a preset period, thereby improving the accuracy of the health state of the to-be-processed battery.

[0017] Optionally, the determining the health state of the to-be-processed battery according to the first health state value and the second health state value comprises: determining a first weight corresponding to the first health state value and a second weight corresponding to the second health state value; and performing weighted fusion of the first health state value and the second health state value based on the first weight and the second weight.

[0018] The health state of the to-be-processed battery is determined based on the fusion result. In this way, the first health state value and the second health state value can be weighted and fused, and the health state of the to-be-processed battery can be determined based on the fusion result.

[0019] Optionally, the determining the first weight corresponding to the first health state value and the second weight corresponding to the second health state value comprises: determining the first weight and the second weight according to the confidence of the corrected SOC; wherein the confidence of the corrected SOC corresponding to the to-be-processed battery when the first correction condition and the second correction condition are satisfied is greater than the confidence of the corrected SOC corresponding to the to-be-processed battery when any correction condition is satisfied. In this way, the first weight and the second weight can be determined according to the confidence of the corrected SOC, thereby improving the accuracy of the two weights and, to some extent, the accuracy of the health state of the to-be-processed battery.

[0020] Optionally, the determining the first weight corresponding to the first health state value and the second weight corresponding to the second health state value comprises: if the to-be-processed battery satisfies the first correction condition, the second weight is greater than the first weight, so as to determine a more accurate health state.

[0021] In a second aspect, an embodiment of the present application provides a battery charging and discharging strategy determination method, which comprises the following steps: determining predicted voltages of a to-be-processed battery at a plurality of battery capacities respectively at a prediction time; obtaining a plurality of voltage residuals according to each predicted voltage and a measured voltage of the to-be-processed battery at each prediction time; determining a target voltage residual meeting a voltage residual requirement from the plurality of voltage residuals; determining a first target battery capacity corresponding to the target voltage residual according to the plurality of battery capacities; determining a health state of the to-be-processed battery according to the first target battery capacity and a rated capacity of the to-be-processed battery; and determining a charging and discharging strategy according to the health state of the to-be-processed battery. In this way, a suitable charging and discharging strategy can be determined according to the health state of the to-be-processed battery, and the service life of the to-be-processed battery is improved to a certain extent.

[0022] In a third aspect, an embodiment of the present application provides a battery health state determination device, which comprises: a predicted voltage determination module, configured to determine predicted voltages of a to-be-processed battery at a plurality of battery capacities respectively at a prediction time; a voltage residual determination module, configured to obtain a plurality of voltage residuals according to each predicted voltage and a measured voltage of the to-be-processed battery at each prediction time; a target voltage residual determination module, configured to determine a target voltage residual meeting a voltage residual requirement from the plurality of voltage residuals; a first target battery capacity determination module, configured to determine a first target battery capacity corresponding to the target voltage residual according to the plurality of battery capacities; and a health state determination module, configured to determine a health state of the to-be-processed battery according to the first target battery capacity and a rated capacity of the to-be-processed battery. In this way, since voltage information can be collected under any working condition, a smaller voltage residual means a smaller error of SOH, and the calculation process is simple, so the health state of the battery can be determined conveniently and accurately in more application scenarios.

[0023] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores computer readable instructions, and when the computer readable instructions are executed by the processor, the steps in the method provided in the first aspect or the second aspect are executed.

[0024] In a fifth aspect, an embodiment of the present application provides a computer readable storage medium, having stored thereon a computer program, which, when executed by a processor, causes the steps of the method according to the first aspect or the second aspect to be performed.

[0025] In a sixth aspect, an embodiment of the present application provides a computer program product, comprising a computer program or instructions, which, when executed by a processor, causes the method according to the first aspect or the second aspect to be performed.

[0026] Other features and advantages of the present application will be set forth in the following description, and in part will be apparent from the description, or can be learned by practice of the application. The objects and other advantages of the present application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0028] FIG. 1 is a flowchart of a battery health state determination method provided by an embodiment of the present application;

[0029] FIG. 2 is a data graph of different battery capacities and their corresponding voltage residuals provided by an embodiment of the present application;

[0030] FIG. 3 is a structure diagram of an equivalent circuit model provided by an embodiment of the present application;

[0031] FIG. 4 is a data graph of different battery capacities and their corresponding SOC residuals provided by an embodiment of the present application;

[0032] FIG. 5 is a curve diagram of the open circuit voltage of a battery to be processed changing with a candidate SOC in a charging state and a discharging state provided by an embodiment of the present application;

[0033] FIG. 6 is a curve diagram of the rate of change of the open circuit voltage of a battery to be processed changing with a candidate SOC provided by an embodiment of the present application;

[0034] FIG. 7 is a flowchart of a battery charging and discharging strategy determination method provided by an embodiment of the present application;

[0035] FIG. 8 is a structure block diagram of a battery health state determination apparatus provided by an embodiment of the present application;

[0036] FIG. 9 is a structural schematic diagram of an electronic device for performing a battery state of health determination method or a battery charging and discharging strategy determination method according to an embodiment of the present application. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be clearly and completely described in connection with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. The components of the embodiments of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0038] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0039] It should be noted that: the embodiments in the present application or the technical features in the embodiments can be combined without conflict.

[0040] In the related art, the accuracy of the SOH of the battery is low, and the application scenarios are limited, so it is not convenient to accurately determine the state of health of the battery. In order to improve this situation, the present application provides a battery state of health determination method. Further, a plurality of voltage residuals can be obtained according to the predicted voltage and the measured voltage corresponding to different battery capacities of the battery to be processed, and then the battery capacity with smaller error of the predicted voltage can be determined according to the plurality of voltage residuals, so as to determine the state of health of the battery to be processed according to the battery capacity and the rated capacity of the battery to be processed. The battery to be processed, i.e. the battery whose state of health is to be determined, can be one battery or a plurality of batteries. If the battery to be processed is one battery, it can have a plurality of battery capacities. If the battery to be processed is a plurality of batteries, at least two batteries have different capacities.

[0041] In this way, since voltage information can be collected under any working condition, and smaller voltage residual means smaller error of SOH, and the calculation process is simple, the state of health of the battery can be conveniently and accurately determined in more application scenarios.

[0042] It should be noted that the application can determine the SOH of the battery through a server, a server cluster, or a cloud platform. In other application scenarios, the SOH of the battery can also be determined through a battery management system or a vehicle-mounted computer, and the application does not limit this. Exemplarily, the application is described below in the context of application to a server.

[0043] It should be noted that the defects of the above-mentioned solutions in the related art are the results obtained by the inventors after practice and careful research. Therefore, the discovery process of the above-mentioned problems and the solutions proposed by the embodiments of the application to the above-mentioned problems should be the contributions made by the inventors to the application during the process of the application.

[0044] Please refer to FIG. 1, which shows a flowchart of a battery health state determination method according to an embodiment of the application. As shown in FIG. 1, the battery health state determination method includes the following steps 101 to 105.

[0045] Step 101, determining a predicted voltage of a to-be-processed battery at a prediction time under a plurality of battery capacities, respectively;

[0046] The prediction time, that is, the time at which the voltage is predicted based on any one of the plurality of battery capacities, can be, for example, the acquisition time, the use time, and the like of the related battery parameters. Thus, the voltage can be predicted based on any one of the battery capacities and the acquired related battery parameters.

[0047] The plurality of battery capacities can include, for example, a plurality of battery capacities or all battery capacities of the to-be-processed battery within a preset range, and the application does not limit this. For example, if the rated capacity of the to-be-processed battery is 100 A·h, then a few battery capacities of (60-80) A·h, (80-99) A·h, or (1-99) A·h can be randomly selected, or all battery capacities within the preset range can be selected.

[0048] It should be noted that the more the number of battery capacities, the more accurate the health state can be determined to a certain extent.

[0049] The predicted voltage can be, for example, a voltage predicted by different algorithms. These algorithms can include, for example, recursive least squares, forgetting factor least squares, Kalman filter algorithms, and the like.

[0050] In some application scenarios, the voltage, current, and other related battery parameters of the to-be-processed battery can also be used when determining the predicted voltage. Therefore, the related battery parameters can be corrected first.

[0051] For example, if the voltage of the to-be-processed battery at the current time collected is not within the preset voltage data range, the voltage is corrected to the voltage at the previous time;

[0052] The preset voltage data range may include, for example, (1-5) V. Thus, if the voltage at the current time is greater than 5 V or less than 1 V, the voltage at the previous time can be corrected to improve the accuracy of the voltage.

[0053] Secondly, if the current data of the current time of the battery to be processed is not within the preset current data range, the current data is corrected to the preset current data.

[0054] The preset current data range may include, for example, (-200-200) A. Thus, if the current data at the current time is greater than 200 A or less than -200 A, the preset current data can be corrected. The preset current data may be, for example, 0.

[0055] In this way, the collected voltage and current data can be corrected in a targeted manner, thereby reducing the errors caused by the two and improving the accuracy of the predicted voltage.

[0056] In step 102, a plurality of voltage residuals are obtained according to each predicted voltage and the measured voltage of the battery to be processed at each predicted time.

[0057] The measured voltage may be, for example, the voltage actually measured by a sensor.

[0058] In some application scenarios, the server may, for example, subtract the measured voltage corresponding to each battery capacity from the predicted voltage, so that the absolute value of the difference between the two can be determined as the corresponding voltage residual. In this way, for a plurality of battery capacities, a plurality of voltage residuals can be obtained.

[0059] In step 103, a target voltage residual that meets the voltage residual requirement is determined from the plurality of voltage residuals.

[0060] The voltage residual requirement may be regarded as a requirement for a smaller error of the predicted voltage.

[0061] In some application scenarios, the server may, for example, determine the N voltage residuals with the smallest values from the plurality of voltage residuals to obtain the target voltage parameter. When N is equal to 1, the target voltage residual may be the voltage residual with the smallest value in the plurality of voltage residuals. When N is greater than 1, the target voltage residual may be the N voltage residuals with smaller values in the plurality of voltage residuals. For example, the plurality of voltage residuals can be sorted in ascending order according to the values, and then the first N voltage residuals with smaller values can be taken.

[0062] It should be noted that when N is greater than 1, the value of N can be determined according to actual conditions, which may be, for example, 2 or 3, etc.

[0063] In some application scenarios, the server can set a voltage residual error determination threshold, and then determine the target voltage residual error from the plurality of voltage residual errors that is less than the voltage residual error determination threshold.

[0064] In step 104, a first target battery capacity corresponding to the target voltage residual error is determined according to the plurality of battery capacities.

[0065] In some application scenarios, if there is only one target voltage residual error, the battery capacity used to determine the target voltage residual error can be determined as the first target battery capacity.

[0066] In some application scenarios, if there are a plurality of target voltage residual errors, the battery capacity used to calculate each target voltage residual error can be determined respectively, and the average capacity or the median capacity of the plurality of battery capacities can be determined as the first target battery capacity.

[0067] Referring to FIG. 2, a data graph of different battery capacities and their corresponding voltage residual errors is shown. As can be seen, the voltage residual errors corresponding to different battery capacities are different. Thus, the corresponding target voltage residual error can be quickly determined, and the first target battery capacity corresponding to the target voltage residual error can be quickly determined.

[0068] In step 105, the SOH of the battery to be processed is determined according to the first target battery capacity and the rated capacity of the battery to be processed.

[0069] In the implementation, the plurality of voltage residual errors can be determined by the predicted voltage and the measured voltage corresponding to the battery to be processed at different battery capacities, so as to determine the battery capacity with smaller error of the predicted voltage, and thus the SOH of the battery to be processed can be determined according to the battery capacity and the rated capacity of the battery to be processed. In this way, since the battery capacity corresponding to the predicted voltage with smaller error is closest to the current real capacity of the battery to be processed, the error of the SOH of the battery to be processed determined based on the battery capacity is also smaller. Therefore, the health status of the battery to be processed can be determined more accurately based on the SOH with smaller error.

[0070] In addition, since the voltage information of the battery to be processed can be collected under most working conditions, and the calculation process is simple, the health status of the battery can be determined conveniently and accurately in more application scenarios.

[0071] In some optional implementation, the determination of the predicted voltage of the battery to be processed at the predicted time under the plurality of battery capacities in step 101 includes: for each battery capacity, the predicted voltage corresponding to the battery to be processed under the battery capacity is determined according to the battery capacity and a plurality of sets of battery parameters in a preset period.

[0072] The preset period can be, for example, one day, one week, or the like, which is preset according to actual needs. Alternatively, the preset period can be a cycle of use of the battery to be processed, and the application does not limit the preset period.

[0073] In this way, the plurality of voltage residuals obtained according to each predicted voltage and the measured voltage of the battery to be processed at each predicted time in step 102 include:

[0074] First, for each predicted voltage, a voltage difference between the predicted voltage and the measured voltage of the battery to be processed at the predicted time is determined.

[0075] It should be noted that the size relationship between the predicted voltage and the measured voltage is uncertain, and therefore the voltage difference is essentially the absolute value of the difference between the two.

[0076] Then, the voltage residual is determined according to the plurality of voltage differences determined within the preset period.

[0077] In some application scenarios, the voltage residual can be, for example, an average value of the voltage differences within the preset period. The average value can be determined, for example, by the calculation formula error wherein volt represents the voltage residual, i=0 represents that the number of predictions starts from 0, n represents the total number of predictions within the preset period, and u i represents the predicted voltage, and u pre-i represents the measured voltage at the predicted time.

[0078] In other application scenarios, the voltage residual can be, for example, a root mean square error of the voltage differences within the preset period. The root mean square error can be determined, for example, by the calculation formula wherein the meanings of the parameters are the same as described above, and will not be described herein.

[0079] In the implementation mode, the voltage residual can be determined by the plurality of voltage differences within the preset period. In this way, the accuracy of the voltage residual can be improved, thereby improving the accuracy of the state of health of the battery to be processed within the preset period.

[0080] In some optional implementation modes, the determination of the predicted voltage of the battery to be processed at the plurality of battery capacities at the predicted time in step 101 includes determining the predicted voltage corresponding to each battery capacity of the battery to be processed based on a Kalman filtering algorithm.

[0081] ​For the convenience of understanding, the Kalman filtering algorithm is introduced here. Specifically, the Kalman filtering algorithm is mainly used to estimate the state of a dynamic system, which uses a set of prediction equations to describe the evolution of the internal state of the system over time to obtain a predicted value, and uses a set of observation equations to represent how to obtain the observed value from the true state. Then, according to the prediction noise corresponding to the predicted value and the observation noise corresponding to the observed value, the Kalman gain is updated to obtain a more accurate true value by weighting the observed value and the predicted value through the Kalman gain.

[0082] Further, when using the Kalman filtering algorithm, it can be combined with an equivalent circuit model to determine the predicted voltage through both. The above equivalent circuit model may, for example, include an Rint model, a first-order RC model, a second-order RC model, etc.

[0083] Then, the server can use the Kalman filtering algorithm to determine the predicted voltage and the measured voltage of the battery to be processed at the predicted time under a plurality of battery capacities, in combination with the related parameters of the equivalent circuit model. The calculation formula of the above Kalman filtering algorithm can be:

[0084]

[0085] U k =G(χ k ,θ k ,I k )=OCV(SOC k )+U 1,k +I k R0+R (2)

[0086]

[0087] Wherein, the calculation formula (1) represents the prediction equation in the Kalman filtering algorithm, the calculation formula (2) represents the observation equation in the Kalman filtering algorithm, and the calculation formula (3) represents the specific physical variable in the matrix; Wherein, Δt represents the time interval between the acquisition time and the last acquisition time; Cap represents the battery capacity, and k represents the time index of determining SOC; U k represents the measured voltage; I k represents the collected current, and U1 represents the polarization voltage (i.e. the voltage of R1); OCV(SOCk) is a function of calculating the open circuit voltage based on SOC; Q represents the prediction noise, and R represents the measurement noise.

[0088] In addition, if the equivalent circuit model is a first-order RC model as shown in FIG. 3, the corresponding circuit model parameters are the first resistance parameter R0, the second resistance parameter R1, and the capacitance parameter C1.

[0089] In the present implementation, the predicted voltage can be determined by the Kalman filtering algorithm, so that the Kalman filtering algorithm can update the predicted voltage quickly at each time when the battery parameters are received, since the Kalman filtering algorithm is a recursive algorithm. Moreover, the battery parameters can change with the changes of the charging and discharging cycles, temperature and aging degree, and the Kalman filtering algorithm can track these changes through recursive updating, so as to obtain a more accurate predicted voltage.

[0090] Further, the Kalman filtering algorithm has prediction noise and measured noise, and one of the two noises can be adaptively selected to adaptively adjust the prediction result, so as to improve the accuracy of the predicted voltage to a certain extent. In some optional implementations, the step 105 can include: first, determining a first state of health value of the battery to be processed according to the first target battery capacity and the rated capacity of the battery to be processed; and then, determining the state of health of the battery to be processed according to the first state of health value.

[0091] In some application scenarios, the server can divide the first target battery capacity by the rated capacity to determine the first state of health value (SOHvolt) of the battery to be processed, so that the state of health of the battery to be processed can be obtained based on the first state of health value.

[0092] In these application scenarios, if the first state of health value is less than 80%, it can be determined that the current state of the battery to be processed is poor, and if the first state of health value is greater than 80%, it can be determined that the current state of the battery to be processed is good.

[0093] In the present implementation, since the voltage information of the battery to be processed can be collected in most working conditions, the first state of health value can be determined in most working conditions. Therefore, the state of health of the battery to be processed can be determined according to the first state of health value in more working conditions, which reduces the application limitations caused by working conditions.

[0094] In some optional implementations, the determination of the state of health of the battery to be processed according to the first target battery capacity and the rated capacity of the battery to be processed in the step 105 includes: determining the state of health of the battery to be processed according to the first state of health value and a second state of health value.

[0095] The second state of health value can not be determined by the voltage residual, but by other parameters. For example, by the battery internal resistance or capacitance.

[0096] If the second state of health value is determined by the battery internal resistance, the initial internal resistance of the battery and the scrap internal resistance of the battery when scrapped can be determined first, and then the first difference value corresponding to the two is calculated. Then, the second difference value corresponding to the actual internal resistance of the battery and the initial internal resistance is determined, and the second state of health value can be determined according to the ratio of the first difference value and the second difference value. For example, if the initial internal resistance of the battery before use is 0.3 mΩ, and the scrap internal resistance of the battery when scrapped is 1 mΩ, the first difference value is 0.7 mΩ. Then, after determining that the current actual internal resistance of the battery is 0.6 mΩ, the second difference value is 0.3 mΩ, and the current second state of health value can be represented by (1-0.3 / 0.7) = 4 / 7.

[0097] In addition, the process of determining the second state of health value according to the capacitance is the same as or similar to the process of determining the second state of health value by the battery internal resistance, which will not be described here.

[0098] Therefore, compared with the above implementation manner of determining the state of health of the battery to be processed based on the first state of health value alone, the state of health of the battery to be processed is determined jointly by the first state of health value and the second state of health value in the implementation manner. In this way, the error of a single state of health value can be reduced, thereby improving the accuracy of the determined state of health.

[0099] In some optional implementation manners, the second state of health value is determined according to the SOC of the battery to be processed, and / or is determined according to the attenuation degree of the battery to be processed.

[0100] In some application scenarios, the above SOC (State of charge, SOC for short) can be collected under certain special working conditions. Therefore, the second state of health value can also be determined by the SOC. The process of determining the second state of health value by the SOC is described in detail below, which will not be described here.

[0101] In other application scenarios, the second state of health value can also be determined according to the attenuation degree of the battery to be processed. For example, the attenuation information of the same type of battery as the battery to be processed can be obtained, so as to determine the attenuation information of the same type of battery in the same period as the attenuation information of the battery to be processed. Then, the state of health value of the same type of battery in the same period can be determined as the second state of health value. The same period may, for example, include the same calendar life period or the same cycle life period.

[0102] In the implementation manner, the second state of health value can be determined according to the SOC and / or the attenuation degree of the battery to be processed, so as to improve the accuracy of the state of health of the battery to be processed.

[0103] It should be noted that in some application scenarios, the health state of the battery to be processed can also be determined jointly using both the second health state value determined according to the SOC of the battery to be processed and the second health state value determined according to the attenuation degree of the battery to be processed, which can improve the accuracy of the health state of the battery to be processed to a certain extent compared with the application scenario of using one of them alone.

[0104] In some optional implementations, in the case where the second health state value is determined according to the SOC of the battery to be processed, before determining the health state of the battery to be processed according to the first health state value and the second health state value, the method further includes:

[0105] Step 1, determining a predicted SOC corresponding to each battery capacity of the battery to be processed respectively;

[0106] The predicted SOC can be, for example, an SOC predicted by different algorithms.

[0107] In some application scenarios, the predicted SOC corresponding to each battery capacity can be determined using, for example, the least square method.

[0108] Step 2, for each predicted SOC, determining an SOC residual according to the predicted SOC and a corrected SOC;

[0109] The corrected SOC is used to correct the predicted SOC. It can be, for example, an SOC value collected when the battery to be processed meets certain conditions (for example, the first correction condition and / or the second correction condition described below). In this way, since the corrected SOC is determined based on the mechanism of the characteristics of the battery itself, it can introduce more reliable SOC information.

[0110] In some application scenarios, the predicted SOC and the corrected SOC can be subtracted, so that the absolute value of the difference between the two can be determined as the SOC residual.

[0111] Step 3, determining a target SOC residual meeting an SOC residual requirement from the plurality of SOC residuals;

[0112] The SOC residual requirement can be, for example, a requirement for making the error of the predicted SOC smaller.

[0113] In some application scenarios, the server may, for example, determine M voltage residuals with the smallest values from the plurality of SOC residuals to obtain a target SOC residual. When M is equal to 1, the target SOC residual may be the voltage residual with the smallest value in the plurality of SOC residuals. When M is greater than 1, the target SOC residual may be the M SOC residuals with smaller values in the plurality of SOC residuals. For example, the plurality of SOC residuals may be sorted in ascending order according to the values, and then the first M voltage residuals with smaller values may be taken.

[0114] It should be noted that when M is greater than 1, the value of M may be determined according to actual conditions, which may be 2 or 3, etc.

[0115] In some application scenarios, the server may, for example, set an SOC residual determination threshold, and then determine a target SOC residual smaller than the SOC residual determination threshold from the plurality of SOC residuals.

[0116] Step 4: determining a second target battery capacity corresponding to the target SOC residual according to the plurality of battery capacities;

[0117] In some application scenarios, if there is only one target SOC residual, the battery capacity used to determine the target SOC residual may be determined as the second target battery capacity.

[0118] In some application scenarios, if there are a plurality of target SOC residuals, the battery capacity used to calculate each target SOC residual may be determined respectively, and the average capacity of the plurality of battery capacities or the battery capacity located in the middle may be determined as the second target battery capacity.

[0119] Referring to FIG. 4, a data graph between different battery capacities and their corresponding SOC residuals is shown. It can be seen that the SOC residuals corresponding to different battery capacities are different. Thus, the corresponding target SOC residual can be quickly determined to quickly determine the corresponding second target battery capacity according to the target SOC residual.

[0120] Step 5: determining a second state of health value of the battery to be processed according to the second target battery capacity and the rated capacity of the battery to be processed.

[0121] Similarly, the server may also divide the second target battery capacity by the rated capacity to determine the second state of health value (SOHsoc) of the battery to be processed.

[0122] In the present implementation, since the SOC of the battery to be processed can be acquired in some working conditions, the health status of the battery to be processed can be determined in combination with the SOC, and the accuracy of the health status can be further improved compared with the implementation of determining the health status of the battery to be processed only by using the first health status value.

[0123] In some optional implementations, the predicted SOC corresponding to each battery capacity of the battery to be processed can be determined based on a Kalman filtering algorithm.

[0124] It should be noted that the Kalman filtering algorithm has been described in detail above, and will not be described here.

[0125] Further, the present implementation can determine a more accurate predicted SOC in more application scenarios by using the Kalman filtering algorithm.

[0126] In some optional implementations, before the SOC residual is determined according to the predicted SOC and the corrected SOC for each predicted SOC, the method further includes: if the battery to be processed satisfies a first correction condition and / or a second correction condition, determining the SOC value corresponding to the battery to be processed when the correction condition is satisfied as the corrected SOC; wherein the first correction condition includes that the battery to be processed is fully charged or fully discharged; and the second correction condition includes that the standing time of the battery to be processed exceeds a preset time threshold.

[0127] It should be noted that the SOC value of the battery to be processed in the full charging condition can be determined as 100% (i.e., the corrected SOC is 100%), and the SOC value of the battery to be processed in the full discharging condition can be determined as 0% (i.e., the corrected SOC is 0%). The voltage corresponding to the full charging or full discharging can be determined according to the type of the battery to be processed, and the present application is not limited thereto. For example, when the voltage of the iron lithium cell is greater than 3.65V, it can be determined that it is fully charged; and when the voltage of the iron lithium cell is less than 2.8V, it can be determined that it is fully discharged.

[0128] The preset time threshold can be, for example, 2-3 hours.

[0129] In some application scenarios, the voltage of the battery to be processed measured after standing can be determined as the open circuit voltage. Then, an open circuit voltage and SOC relationship table (which can store the corresponding relationship between the open circuit voltage and the SOC) can be obtained in advance, so as to determine the corresponding SOC according to the acquired open circuit voltage, and determine the SOC as the corrected SOC.

[0130] In the related art, the two-point method needs the battery to be in a condition close to full charging or full discharging, and such a condition occurs less frequently, so that the opportunity to calculate SOH is less. In the present implementation, the corrected SOC can be determined when any correction condition is met (i.e., any condition is met). Therefore, the present implementation can determine the corrected SOC in more application scenarios, thereby facilitating the determination of the health status of the battery to be processed.

[0131] In some application scenarios, the battery to be processed can be recycled, and during its recycling process, the first correction condition and / or the second correction condition can be met multiple times, so there can be multiple SOCs that meet the conditions. Therefore, one of the multiple SOCs can be determined as the corrected SOC.

[0132] Specifically, if the battery to be processed meets the first correction condition and / or the second correction condition multiple times within a predetermined period, the open-circuit voltage corresponding to each time the battery to be processed meets the condition is determined.

[0133] Then, for each open-circuit voltage, a candidate SOC value corresponding to the battery to be processed is determined according to the open-circuit voltage.

[0134] Similarly, the server can determine the SOC corresponding to each open-circuit voltage according to the open-circuit voltage and SOC relationship table. Each SOC can be determined as a candidate SOC.

[0135] Secondly, the corrected SOC is determined from the multiple candidate SOCs according to the rate of change of the open-circuit voltage with the candidate SOC.

[0136] In some application scenarios, the candidate SOC corresponding to the maximum rate of change of the open-circuit voltage with the candidate SOC can be determined as the corrected SOC to improve the accuracy of the corrected SOC.

[0137] In these application scenarios, for example, a rate of change curve can be drawn to facilitate the determination of the candidate SOC corresponding to the maximum rate of change. Please refer to FIG. 5, which shows the curve of the open-circuit voltage with the candidate SOC in the charging state or discharging state of the battery to be processed. Then, the data of each coordinate point can be differentiated to obtain the rate of change curve as shown in FIG. 6, thereby facilitating the determination of the candidate SOC corresponding to the maximum rate of change.

[0138] In the present implementation, a more accurate corrected SOC can be determined within a predetermined period, thereby improving the accuracy of the health status of the battery to be processed.

[0139] In some optional implementations, determining the health status of the battery to be processed based on the first health status value and the second health status value includes:

[0140] First, determine the first weight corresponding to the first health status value and the second weight corresponding to the second health status value;

[0141] In some applications, the first and second weights can be set based on empirical values. These empirical values ​​can be determined, for example, based on the SOC and open-circuit voltage of the battery to be processed. For instance, if the corrected SOC is greater than 98% or less than 30%, the second weight can be set to 0.6. For other corrected SOC values, the second weight can be set to 0.1.

[0142] In other application scenarios, the second weight can also be determined based on the rate of change of the open-circuit voltage of the battery under test at the corrected SOC. This can be calculated using the formula k = 0.8 × der. soc ÷max der Determined. Here, k represents the second weight, 0.8 is the maximum weight value under conditions other than the first preset correction condition, and der soc The maximum value represents the rate of change of the open-circuit voltage at the corrected SOC under non-first preset correction conditions. der The maximum value representing the rate of change.

[0143] Then, the first weight can be determined based on the second weight. For example, if the second weight is 0.6, the first weight can be 0.4; if the second weight is 0.1, the first weight can be 0.9.

[0144] Then, based on the first weight and the second weight, the first health status value and the second health status value are weighted and fused; based on the fusion result, the health status of the battery to be processed is determined.

[0145] In some application scenarios, the weighted fusion process can be described by a calculation formula, such as: SOH=(1-k)×SOH volt +k×SOH soc Where k represents the second weight, SOH volt The first health status value, SOH soc The second health status value is represented by SOH, and the fusion result is represented by SOH.

[0146] It should be noted that if there are both a second health state value determined based on the SOC of the battery to be processed and a second health state value determined based on the degree of degradation of the battery to be processed, then the two can be weighted and fused together with the first health state value.

[0147] For example, the server can weight and fuse the second health state value determined based on the SOC of the battery to be processed with the first health state value using the above calculation formula, and then weight and fuse the fused result again with the second health state value determined based on the degree of degradation of the battery to be processed. The calculation formula for this second weighted fusion could be, for example, SOH. final =β×SOH+(1-β)×SOH lab Where β represents the weight of the first fusion result, and SOH represents the weight of the first fusion result. lab The second state of health (SOH) value, determined based on the degree of degradation of the battery to be treated, is used to characterize the battery's state of health. final The results of the re-fusion are characterized. Therefore, the health status of the battery to be processed can be determined based on the re-fusion results.

[0148] In this implementation, the first health status value and the second health status value can be weighted and fused, so that a more accurate health status of the battery to be processed can be determined based on the fusion result.

[0149] In some optional implementations, the determination of the first weight corresponding to the first health state value and the second weight corresponding to the second health state value includes: determining the first weight and the second weight based on the confidence level of the corrected SOC; wherein the confidence level of the corrected SOC corresponding to the battery to be processed when satisfying the first correction condition and the second correction condition is greater than the confidence level of the corrected SOC corresponding to the battery to be processed when satisfying any one of the correction conditions.

[0150] In some application scenarios, the more calibration conditions the battery to be processed meets, the higher the confidence level of the calibrated SOC. For example, if the battery to be processed is in case A, which meets both the full charge condition (first calibration condition) and the second calibration condition, then the confidence level of the calibrated SOC in case A is higher than that in case B, which only meets the second calibration condition. Therefore, the server can set the second weight to be greater than the first weight. For example, the server can set the second weight to 0.8 and the first weight to a smaller 0.2.

[0151] In this implementation, the first weight and the second weight can be determined based on the confidence level of the corrected SOC, thereby improving the accuracy of both and, to some extent, also improving the accuracy of the health status of the battery to be processed.

[0152] In some optional implementations, the determination of the first weight corresponding to the first health status value and the second weight corresponding to the second health status value includes: if the battery to be processed meets the first correction condition, then the second weight is greater than the first weight.

[0153] That is, when the battery to be processed is in a full charge state or a full discharge state, a more accurate SOC value can be collected, so that a more accurate second state of health value can be obtained. Therefore, the second weight can be set to be greater than the first weight, so that the second state of health value determined according to the SOC of the battery to be processed plays a dominant role in determining the state of health of the battery to be processed, so that a more accurate state of health is determined.

[0154] Those skilled in the art can understand that in the above method of the specific embodiment, the writing order of each step does not mean a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0155] Please refer to FIG. 7, which shows a flowchart of a battery charging and discharging strategy determination method provided by an embodiment of the present application. As shown in FIG. 7, the method comprises:

[0156] Step 701: determining predicted voltages of a battery to be processed at a plurality of battery capacities at a plurality of prediction times, respectively;

[0157] Step 702: obtaining a plurality of voltage residuals according to each predicted voltage and a measured voltage of the battery to be processed at each prediction time;

[0158] Step 703: determining a target voltage residual satisfying a voltage residual requirement from the plurality of voltage residuals;

[0159] Step 704: determining a first target battery capacity corresponding to the target voltage residual according to the plurality of battery capacities;

[0160] Step 705: determining a state of health of the battery to be processed according to the first target battery capacity and a rated capacity of the battery to be processed;

[0161] It should be noted that the implementation process and technical effects of the above steps 701 to 705 can be the same as or similar to those of the steps 101 to 105, which will not be described here.

[0162] Step 706: determining a charging and discharging strategy according to the state of health of the battery to be processed.

[0163] In some application scenarios, if the SOH of the battery to be processed is low, the charging current can be reduced, the charging and discharging interval time can be extended, and so on. Similarly, if the SOH of the battery to be processed is high, the charging current can be increased, the charging and discharging interval time can be shortened, and so on.

[0164] In some application scenarios, if the battery to be processed is a plurality of batteries, the plurality of batteries can be subjected to equalization charging and discharging. For example, the battery with a lower SOH is charged first, and then the battery with a slightly higher SOH is charged, so that the SOH of each battery tends to be consistent. In addition, when discharging, the battery with a higher SOH can be discharged first, and then the battery with a slightly lower SOH is discharged. In this way, the condition that the battery with a lower SOH is damaged due to excessive discharging can be improved, and the SOH of each battery can also tend to be consistent.

[0165] It should be noted that when it is determined to charge and discharge the battery to be processed, the server can determine the corresponding charging and discharging strategy through the above steps. Alternatively, the corresponding charging and discharging strategy can also be determined through the above steps when the preset period arrives, and the present application does not limit this.

[0166] In the present implementation, after the health status of the battery to be processed is determined, the appropriate charging and discharging strategy is determined according to the health status, which to some extent improves the service life of the battery to be processed.

[0167] Please refer to FIG. 8, which shows a structural block diagram of a battery health status determination device provided by an embodiment of the present application. The battery health status determination device can be a module, a program segment or code on an electronic device. It should be understood that the device corresponds to the above-mentioned method embodiment of FIG. 1, and can perform each step involved in the method embodiment of FIG. 1.

[0168] Optionally, the above-mentioned battery health status determination device comprises a predicted voltage determination module 801, a voltage residual error determination module 802, a target voltage residual error determination module 803, a first target battery capacity determination module 804 and a health status determination module 805. The predicted voltage determination module 801 is configured to determine the predicted voltage of the battery to be processed at a plurality of battery capacities at a predicted time, respectively. The voltage residual error determination module 802 is configured to obtain a plurality of voltage residual errors according to each predicted voltage and the measured voltage of the battery to be processed at each predicted time. The target voltage residual error determination module 803 is configured to determine a target voltage residual error that meets the voltage residual error requirement from the plurality of voltage residual errors. The first target battery capacity determination module 804 is configured to determine a first target battery capacity corresponding to the target voltage residual error according to the plurality of battery capacities. The health status determination module 805 is configured to determine the health status of the battery to be processed according to the first target battery capacity and the rated capacity of the battery to be processed.

[0169] Optionally, the predicted voltage determination module 801 is further configured to: for each of the battery capacities, determine a corresponding predicted voltage of the battery to be processed at the battery capacity according to the battery capacity and a plurality of groups of battery parameters in a preset period; in this way, the voltage residual determination module 802 is further configured to: for each of the predicted voltages, determine a voltage difference between the predicted voltage and a measured voltage of the battery to be processed at a predicted time; and determine the voltage residual according to a plurality of voltage differences determined in the preset period.

[0170] Optionally, the predicted voltage determination module 801 is further configured to: determine the corresponding predicted voltages of the battery to be processed at a plurality of battery capacities based on a Kalman filtering algorithm.

[0171] Optionally, the health state determination module 805 is further configured to: determine a first health state value of the battery to be processed according to the first target battery capacity and a rated capacity of the battery to be processed; and determine the health state of the battery to be processed according to the first health state value.

[0172] Optionally, the health state determination module 805 is further configured to: determine the health state of the battery to be processed according to the first health state value and a second health state value.

[0173] Optionally, the second health state value is determined according to an SOC of the battery to be processed and / or an attenuation degree of the battery to be processed.

[0174] Optionally, the apparatus further comprises a second health state value determination module, which is configured to: when the second health state value is determined according to the SOC of the battery to be processed, determine a corresponding predicted SOC of the battery to be processed at a plurality of battery capacities before determining the health state of the battery to be processed according to the first health state value and the second health state value; for each of the predicted SOCs, determine an SOC residual according to the predicted SOC and a corrected SOC; determine a target SOC residual that meets an SOC residual requirement from a plurality of SOC residuals; determine a second target battery capacity corresponding to the target SOC residual according to the plurality of battery capacities; and determine a second health state value of the battery to be processed according to the second target battery capacity and the rated capacity of the battery to be processed.

[0175] Optionally, the second health state value determination module is further configured to: determine the corresponding predicted SOCs of the battery to be processed at a plurality of battery capacities based on a Kalman filtering algorithm.

[0176] Optionally, the apparatus further comprises a corrected SOC determining module, configured to: if the to-be-processed battery satisfies a first correction condition and / or a second correction condition, determine a SOC corresponding to a time when the to-be-processed battery satisfies the correction condition as the corrected SOC, before determining the SOC residual according to the predicted SOC and the corrected SOC for each of the predicted SOCs; wherein the first correction condition comprises that the to-be-processed battery is fully charged or fully discharged; and the second correction condition comprises that a static duration of the to-be-processed battery exceeds a preset duration threshold.

[0177] Optionally, the corrected SOC determining module is further configured to: if the to-be-processed battery satisfies the first correction condition and / or the second correction condition for multiple times within a preset period, determine an open-circuit voltage corresponding to each time when the to-be-processed battery satisfies the correction condition; determine a candidate SOC corresponding to the to-be-processed battery according to each open-circuit voltage; and determine the corrected SOC from the multiple candidate SOCs according to a rate of change of the open-circuit voltage with respect to the candidate SOC.

[0178] Optionally, the health state determining module 805 is further configured to: determine a first weight corresponding to the first health state value and a second weight corresponding to the second health state value; perform weighted fusion on the first health state value and the second health state value based on the first weight and the second weight; and determine the health state of the to-be-processed battery based on a fusion result.

[0179] Optionally, the health state determining module 805 is further configured to: determine the first weight and the second weight according to a confidence level of the corrected SOC; wherein the confidence level of the corrected SOC corresponding to a time when the to-be-processed battery satisfies the first correction condition and the second correction condition is greater than the confidence level of the corrected SOC corresponding to a time when the to-be-processed battery satisfies any correction condition.

[0180] Optionally, the health state determining module 805 is further configured to: if the to-be-processed battery satisfies the first correction condition, the second weight is greater than the first weight.

[0181] It should be noted that, for the convenience and brevity of description, the specific working process of the system or apparatus described above can refer to the corresponding process in the foregoing method embodiments, which will not be described herein.

[0182] Referring to FIG. 9, FIG. 9 is a structural schematic diagram of an electronic device for performing a battery health state determination method according to an embodiment of the present application. The electronic device can include at least one processor 901, such as a CPU, at least one communication interface 902, at least one memory 903, and at least one communication bus 904. The communication bus 904 is used to realize direct connection and communication of the components. The communication interface 902 of the device in the embodiment of the present application is used to perform signaling or data communication with other node devices. The memory 903 can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The memory 903 can also be at least one storage device located away from the aforementioned processor. The memory 903 stores computer readable instructions. When the computer readable instructions are executed by the processor 901, the electronic device can perform the method processes shown in FIG. 1 or FIG. 7.

[0183] It can be understood that the structure shown in FIG. 9 is only schematic. The electronic device can include more or fewer components than those shown in FIG. 9, or have a different configuration from that shown in FIG. 9. The components shown in FIG. 9 can be realized by hardware, software, or a combination thereof.

[0184] The embodiment of the present application provides a computer readable storage medium, which stores a computer program. When the computer program is executed by a processor, any implementation manner of the method embodiments shown in FIG. 1 or FIG. 7 can be performed.

[0185] The embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can perform the method provided by each method embodiment. For example, the method can include: determining predicted voltages of a to-be-processed battery at a plurality of battery capacities at a prediction time, respectively; obtaining a plurality of voltage residuals according to each predicted voltage and a measured voltage of the to-be-processed battery at each prediction time; determining a target voltage residual that meets a voltage residual requirement from the plurality of voltage residuals; determining a first target battery capacity corresponding to the target voltage residual according to the plurality of battery capacities; and determining a health state of the to-be-processed battery according to the first target battery capacity and a rated capacity of the to-be-processed battery.

[0186] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic.

[0187] Further, each functional module in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0188] The above merely provides an embodiment of the present application, but should not be used to limit the protection scope of the present application. For those skilled in the art, the present application can have various modifications and changes. Any modified, equivalent replaced, improved, etc. within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method of determining a state of health of a battery, the method comprising: The method comprises the following steps: determining predicted voltages of a to-be-processed battery at a plurality of battery capacities respectively at a plurality of prediction time points; obtaining a plurality of voltage residuals according to each predicted voltage and a measured voltage of the to-be-processed battery at each prediction time point; determining a target voltage residual from the plurality of voltage residuals, which meets a voltage residual requirement; determining a first target battery capacity corresponding to the target voltage residual according to the plurality of battery capacities; determining a state of health of the to-be-processed battery according to the first target battery capacity and a rated capacity of the to-be-processed battery.

2. The method of claim 1, wherein, The step of determining the predicted voltages of the to-be-processed battery at the plurality of battery capacities respectively at the plurality of prediction time points comprises the following steps: for each battery capacity, determining a corresponding predicted voltage of the to-be-processed battery at the battery capacity according to the battery capacity and a plurality of groups of battery parameters in a preset period; and The step of obtaining the plurality of voltage residuals according to each predicted voltage and the measured voltage of the to-be-processed battery at each prediction time point comprises the following steps: for each predicted voltage, determining a voltage difference between the predicted voltage and the measured voltage of the to-be-processed battery at the prediction time point; and determining the voltage residual according to a plurality of voltage differences determined in the preset period.

3. The method of claim 1, wherein, The step of determining the predicted voltages of the to-be-processed battery at the plurality of battery capacities respectively according to a Kalman filtering algorithm. The step of determining the state of health of the to-be-processed battery according to the first target battery capacity and the rated capacity of the to-be-processed battery comprises the following steps:

4. The method according to any one of claims 1 to 3, characterized in that, determining a first state of health value of the to-be-processed battery according to the first target battery capacity and the rated capacity of the to-be-processed battery; and determining the state of health of the to-be-processed battery according to the first state of health value. The step of determining the state of health of the to-be-processed battery according to the first target battery capacity and the rated capacity of the to-be-processed battery further comprises the following steps:

5. The method of claim 4, wherein, determining the state of health of the to-be-processed battery according to the first state of health value and a second state of health value. The second state of health value is determined according to an SOC of the to-be-processed battery and / or an attenuation degree of the to-be-processed battery.

6. The method of claim 5, wherein, When the second state of health value is determined according to the SOC of the to-be-processed battery, the method further comprises the following steps before determining the state of health of the to-be-processed battery according to the first state of health value and the second state of health value:

7. The method of claim 6, wherein, determining a plurality of predicted SOCs of the to-be-processed battery respectively corresponding to the plurality of battery capacities; for each predicted SOC, determining an SOC residual according to the predicted SOC and a corrected SOC; determining a target SOC residual from a plurality of SOC residuals, which meets an SOC residual requirement; determining a second target battery capacity corresponding to the target SOC residual according to the plurality of battery capacities; determining a second state of health value of the to-be-processed battery according to the second target battery capacity and the rated capacity of the to-be-processed battery. The step of determining the plurality of predicted SOCs of the to-be-processed battery respectively corresponding to the plurality of battery capacities comprises the following steps:

8. The method of claim 7, wherein, ​ Determine the predicted SOC corresponding to each of the battery capacities of the battery to be processed based on the Kalman filtering algorithm.

9. The method according to any of claims 7-8, characterized by, Before determining the SOC residual based on the predicted SOC and the corrected SOC for each of the predicted SOCs, the method further comprises: If the battery to be processed satisfies the first correction condition and / or the second correction condition, determine the SOC corresponding to the correction condition as the corrected SOC. The first correction condition includes that the battery to be processed is fully charged or fully discharged, and the second correction condition includes that the battery to be processed is stationary for more than a preset time threshold.

10. The method of claim 9, wherein, If the battery to be processed satisfies the first correction condition and / or the second correction condition, determine the SOC corresponding to the correction condition as the corrected SOC. If the battery to be processed satisfies the first correction condition and / or the second correction condition multiple times within a preset period, determine the open-circuit voltage corresponding to each time the battery to be processed satisfies the condition. For each open-circuit voltage, determine the candidate SOC corresponding to the battery to be processed based on the open-circuit voltage. Determine the corrected SOC from the plurality of candidate SOCs based on the rate of change of the open-circuit voltage with respect to the candidate SOC.

11. The method of claim 9, wherein, The determination of the health state of the battery to be processed based on the first health state value and the second health state value comprises: Determine the first weight corresponding to the first health state value and the second weight corresponding to the second health state value. Based on the first weight and the second weight, weight and fuse the first health state value and the second health state value. Based on the fusion result, determine the health state of the battery to be processed.

12. The method of claim 11, wherein, The determination of the first weight corresponding to the first health state value and the second weight corresponding to the second health state value comprises: Determine the first weight and the second weight based on the confidence of the corrected SOC. The confidence of the corrected SOC corresponding to the battery to be processed when satisfying the first correction condition and the second correction condition is greater than the confidence of the corrected SOC corresponding to the battery to be processed when satisfying any correction condition.

13. The method of claim 11, wherein, The determination of the first weight corresponding to the first health state value and the second weight corresponding to the second health state value comprises: If the battery to be processed satisfies the first correction condition, the second weight is greater than the first weight.

14. A method for determining a battery charging and discharging strategy, characterized in that, Comprise: Determine the predicted voltage of the battery to be processed at the predicted time under multiple battery capacities. Obtain a plurality of voltage residuals based on each predicted voltage and the measured voltage of the battery to be processed at each predicted time. From the plurality of voltage residuals, determine a target voltage residual that satisfies the voltage residual requirement. Determine a first target battery capacity corresponding to the target voltage residual based on the plurality of battery capacities. Determine the health state of the battery to be processed based on the first target battery capacity and the rated capacity of the battery to be processed. Determine the charging and discharging strategy based on the health state of the battery to be processed.

15. A battery state of health determination apparatus characterized by comprising: Comprise: A prediction voltage determination module is configured to determine a prediction voltage of a to-be-processed battery at a plurality of battery capacities at a prediction time point respectively; A voltage residual determination module is configured to obtain a plurality of voltage residuals according to the prediction voltages and measured voltages of the to-be-processed battery at the prediction time points respectively; A target voltage residual determination module is configured to determine a target voltage residual from the plurality of voltage residuals, which satisfies a voltage residual requirement; A first target battery capacity determination module is configured to determine a first target battery capacity corresponding to the target voltage residual according to the plurality of battery capacities; A health state determination module is configured to determine a health state of the to-be-processed battery according to the first target battery capacity and a rated capacity of the to-be-processed battery.

16. An electronic device, comprising: A computer readable medium stores computer readable instructions, which when executed by a processor, implement any one of the methods of claims 1-14.

17. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by a processor to implement any one of the methods of claims 1-14.

18. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions are executed by a processor to implement any one of the methods of claims 1-14.

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