Battery SOC estimation method, device, equipment and storage medium

Abstract

The present application relates to a battery SOC estimation method, apparatus, device, and storage medium, and relates to the field of battery technology. The method includes: obtaining an initial SOC value of a first battery and an initial SOC value of a second battery in a battery pack to be tested; determining a first SOC value of the first battery based on the initial SOC value of the first battery and a first SOC estimation algorithm; the first SOC value is the SOC value of the second battery mapped from the current SOC value of the first battery; determining a second SOC value of the second battery based on the initial SOC value of the second battery and a preset method; the preset method includes a second SOC estimation algorithm and / or a preset mapping relationship, the preset mapping relationship being a mapping relationship between the SOC value of the first battery and the SOC value of the second battery; determining the entire SOC of the battery pack to be tested based on the second SOC value and / or the third SOC value. This improves the accuracy of battery SOC estimation and avoids issues with SOC accuracy.

Description

Technical Field

[0001] The present application relates to the field of communication technology, in particular to the field of battery technology, and specifically to a battery SOC estimation method, device, equipment and storage medium. Background Art

[0002] Ternary lithium batteries, a popular type of power battery, typically offer high energy density, excellent low-temperature performance, and linear voltage variation. However, they also come with issues like high cost and poor safety. By combining ternary lithium batteries with lithium iron phosphate batteries, their complementary advantages can improve overall pack safety and reduce costs, while also addressing the inaccurate SOC estimation issues associated with lithium iron phosphate batteries by leveraging the linear voltage variation of ternary lithium batteries.

[0003] At present, due to the differences in self-discharge rate, aging rate, voltage-capacity ratio, etc. between the batteries of the above two systems, it is necessary to determine the SOC of the entire battery pack of the two systems through a battery data model and a Kalman filter algorithm. However, this method will reduce the estimation accuracy of the battery SOC. Summary of the Invention

[0004] This application provides a battery SOC estimation method, device, equipment, and storage medium to at least solve the technical problem of inaccurate battery SOC estimation in related technologies. The technical solution of this application is as follows:

[0005] According to a first aspect of the present application, a battery SOC estimation method is provided, including: obtaining an initial SOC value of a first battery and an initial SOC value of a second battery in a battery pack to be tested; determining a first SOC value of the first battery according to the initial SOC value of the first battery and a first SOC estimation algorithm; the first SOC value is the SOC value of the second battery mapped from the current SOC value of the first battery; determining a second SOC value of the second battery based on the initial SOC value of the second battery and a preset method; the preset method includes a second SOC estimation algorithm and / or a preset mapping relationship; when the initial SOC value of the second battery is less than a threshold value, the preset method is the SOC estimation algorithm, and when the initial SOC value of the second battery is greater than the threshold value, the preset method is a preset mapping relationship; the preset mapping relationship is a mapping relationship between the SOC value of the first battery and the SOC value of the second battery; and determining the entire SOC of the battery pack to be tested according to the first SOC value and / or the second SOC value.

[0006] According to the above technical means, the present application can calculate the first SOC value of the first battery through the initial SOC value of the first battery and the SOC estimation algorithm. The SOC estimation algorithm can improve the stability and reliability of the battery model parameter identification. Furthermore, when determining the second SOC value of the second battery, it can be determined according to the SOC estimation algorithm or according to a preset mapping relationship. Using different methods to determine the second SOC value of the second battery can reduce the error of the second battery SOC, so as to improve the accuracy of the subsequent determination of the SOC of the entire battery pack to be tested. At the same time, the battery SOC estimation device can map the current SOC value of the first battery to the first SOC value of the same dimension as the second battery through a preset mapping relationship, which is beneficial to the subsequent calculation of the SOC of the entire pack, thereby at least solving the technical problem of inaccurate battery SOC estimation accuracy in the related art.

[0007] In addition, the present application can select a method for calculating the SOC value of the second battery according to different situations of the SOC of the second battery to reduce calculation errors.

[0008] In a possible embodiment, the above method also includes: the preset method includes an SOC estimation algorithm; based on the initial SOC value of the second battery and the preset method, determining the second SOC value of the second battery, including: based on the initial SOC value of the second battery and the SOC estimation algorithm, determining the expected SOC value of the second battery; the initial SOC value of the second battery is less than a threshold value; when the expected SOC value is less than the threshold value, determining the expected SOC value to be the second SOC value.

[0009] According to the above technical means, when the SOC of the second battery is less than the threshold, the present application can determine that the SOC of the second battery calculated by the SOC estimation algorithm is more accurate. The SOC estimation algorithm combines the battery equivalent circuit model and measurement information for closed-loop calculation, and the SOC error can be corrected online iteratively, with high robustness.

[0010] In a possible embodiment, the above method also includes: the preset method includes a preset mapping relationship; based on the initial SOC value of the second battery and the preset method, determining the second SOC value of the second battery, including: based on the current SOC value of the first battery and the preset mapping relationship, determining the expected SOC value of the second battery; the initial SOC value of the second battery is greater than a threshold value; when the expected SOC value is greater than the threshold value, determining the expected SOC value to be the second SOC value.

[0011] In a possible embodiment, the above method also includes: a preset method includes an SOC estimation algorithm and a preset mapping relationship; based on the initial SOC value of the second battery and the preset method, determining the second SOC value of the second battery, including: based on the initial SOC value of the second battery and the SOC estimation algorithm, determining the expected SOC value of the second battery; the initial SOC value of the second battery is less than a threshold value; when the expected SOC value is greater than the threshold value, determining the second SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship.

[0012] According to the above technical means, the stability and reliability of battery model parameter identification can be improved, and the parameters of the Kalman filter algorithm can be expanded by adaptively adjusting the working conditions, making the SOC estimation process smoother and the estimation accuracy more accurate.

[0013] In a possible embodiment, the above method also includes: a preset method includes an SOC estimation algorithm and a preset mapping relationship; based on the initial SOC value of the second battery and the preset method, determining the second SOC value of the second battery, including: based on the current SOC value of the first battery and the preset mapping relationship, determining the expected SOC value of the second battery; the initial SOC value of the second battery is greater than a threshold value; when the expected SOC value is less than the threshold value, determining the second SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm.

[0014] According to the above technical means, the SOC error of ternary lithium can be corrected online iteratively within the entire SOC range, and the SOC error of lithium iron phosphate can be corrected online iteratively within a certain range, avoiding the cumulative error caused by the complete use of ampere-hour integration to calculate the SOC of lithium iron phosphate. Compared with the existing SOC estimation technology of hybrid batteries, it is more reliable.

[0015] In a possible embodiment, the above method also includes: determining the SOC of the battery pack to be tested based on the first SOC value and / or the second SOC value, including: determining the target SOC based on the first SOC value and / or the second SOC value; determining an approximation coefficient based on the target SOC; substituting the approximation coefficient into a preset formula to obtain the SOC of the entire battery pack to be tested.

[0016] In a possible embodiment, the above method also includes: determining the target SOC based on the first SOC value and / or the second SOC value, including: when the first SOC value and the second SOC value are consistent, determining the target SOC to be any one of the first SOC value and the second SOC value; when the first SOC value and the second SOC value are inconsistent, and during the charging process, determining the maximum SOC value of the first SOC value and the second SOC value as the target SOC; when the first SOC value and the second SOC value are inconsistent, and during the discharging process, determining the minimum SOC value of the first SOC value and the second SOC value as the target SOC.

[0017] According to the above technical means, the target SOC that meets the conditions can be determined for different situations of the first SOC value and the second SOC value, thereby further improving the accuracy of the entire SOC of the battery pack to be tested and solving the problem of accurate estimation of the SOC of the hybrid battery pack throughout its life cycle.

[0018] In a possible implementation, the method further includes: the SOC of the entire battery pack to be tested satisfies the following preset formula:

[0019]

[0020] Among them, SOC pack,k is the SOC of the battery pack to be tested at time k, ω is the approximation coefficient, Q pack is the entire capacity of the battery pack to be tested.

[0021] According to a second aspect provided by the present application, a battery SOC estimation device is provided, including a processing unit and an acquisition unit; the acquisition unit is used to acquire an initial SOC value of a first battery and an initial SOC value of a second battery in a battery pack to be tested; the processing unit is used to determine a first SOC value of the first battery based on the initial SOC value of the first battery and a first SOC estimation algorithm; the first SOC value is the SOC value of the second battery mapped from the current SOC value of the first battery; the processing unit is also used to determine a second SOC value of the second battery based on the initial SOC value of the second battery and a preset method; the preset method includes a second SOC estimation algorithm and / or a preset mapping relationship, when the initial SOC value of the second battery is less than a threshold value, the preset method is the SOC estimation algorithm, and when the initial SOC value of the second battery is greater than the threshold value, the preset method is the preset mapping relationship; the preset mapping relationship is a mapping relationship between the SOC value of the first battery and the SOC value of the second battery; the processing unit is also used to determine the entire SOC of the battery pack to be tested based on the first SOC value and / or the second SOC value.

[0022] In one possible embodiment, when the SOC value of the second battery is less than a threshold value, the preset method is an SOC estimation algorithm; when the SOC value of the second battery is greater than the threshold value, the preset method is a preset mapping relationship; the linear region and the platform region are regions in the lithium iron phosphate OCV-SOC curve; the rate of change in the linear region is greater than the rate of change in the platform region.

[0023] In one possible embodiment, the preset method includes an SOC estimation algorithm; the above-mentioned processing unit is specifically used to: determine the expected SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm; the initial SOC value of the second battery is less than a threshold value; when the expected SOC value is less than the threshold value, determine the expected SOC value as the second SOC value.

[0024] In one possible embodiment, the preset method includes a preset mapping relationship; the above-mentioned processing unit is specifically used to: determine the expected SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship; the initial SOC value of the second battery is greater than the threshold value; when the expected SOC value is greater than the threshold value, determine the expected SOC value as the second SOC value.

[0025] In one possible embodiment, the preset method includes an SOC estimation algorithm and a preset mapping relationship; the above-mentioned processing unit is specifically used to: determine the expected SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm; the initial SOC value of the second battery is less than a threshold value; when the expected SOC value is greater than the threshold value, determine the second SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship.

[0026] In one possible embodiment, the preset method includes an SOC estimation algorithm and a preset mapping relationship; the above-mentioned processing unit is specifically used to: determine the expected SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship; the initial SOC value of the second battery is greater than a threshold value; when the expected SOC value is less than the threshold value, determine the second SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm.

[0027] In one possible implementation, the processing unit is specifically configured to: determine a target SOC based on the first SOC value and / or the second SOC value; determine an approximation coefficient based on the target SOC; and substitute the approximation coefficient into a preset formula to obtain the entire SOC of the battery pack to be tested.

[0028] In one possible embodiment, the above-mentioned processing unit is specifically used to: when the first SOC value and the second SOC value are consistent, determine the target SOC to be any one of the first SOC value and the second SOC value; when the first SOC value and the second SOC value are inconsistent, and during the charging process, determine the maximum SOC value of the first SOC value and the second SOC value as the target SOC; when the first SOC value and the second SOC value are inconsistent, and during the discharging process, determine the minimum SOC value of the first SOC value and the second SOC value as the target SOC.

[0029] In one possible implementation, the SOC of the entire battery pack to be tested satisfies the following preset formula:

[0030]

[0031] Among them, SOC pack,k is the SOC of the battery pack to be tested at time k, ω is the approximation coefficient, Q pack is the entire capacity of the battery pack to be tested.

[0032] In a possible implementation, the first battery is a ternary lithium battery, and the second battery is a lithium iron phosphate battery.

[0033] According to the third aspect provided by the present application, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement the method of the above-mentioned first aspect and any possible implementation method thereof.

[0034] According to the fourth aspect provided by the present application, a battery module is provided, including a module body formed by multiple single cells connected in series and / or in parallel and the above-mentioned electronic device, the module body is provided with a sensor electrically connected to the electronic device, and the sensor is used to detect the electrical parameters of each single cell in the multiple single cells.

[0035] According to the fifth aspect provided by the present application, a computer-readable storage medium is provided. When the instructions in the computer-readable storage medium are executed by the processor of an electronic device, the electronic device is enabled to execute the method in the above-mentioned first aspect and any possible implementation method thereof.

[0036] According to the sixth aspect provided by the present application, a computer program product is provided, which includes computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the method of the above-mentioned first aspect and any possible implementation method thereof.

[0037] Therefore, the above technical features of this application have the following beneficial effects:

[0038] (1) The first SOC value of the first battery can be calculated by using the initial SOC value of the first battery and the SOC estimation algorithm. The SOC estimation algorithm can improve the stability and reliability of the battery model parameter identification. Furthermore, when determining the second SOC value of the second battery, it can be determined according to the SOC estimation algorithm or according to a preset mapping relationship. Using different methods to determine the second SOC value of the second battery can reduce the error of the second battery SOC, so as to improve the accuracy of the subsequent determination of the SOC of the entire battery pack to be tested, which is beneficial to the subsequent calculation of the SOC of the entire pack, thereby at least solving the technical problem of inaccurate estimation accuracy of the battery SOC in the related art.

[0039] (2) According to different situations of the second battery SOC, a method suitable for calculating the second battery SOC value can be selected to reduce calculation errors.

[0040] (3) When the SOC of the second battery is less than the threshold, the present application can determine that the SOC of the second battery calculated by the SOC estimation algorithm is more accurate. The SOC estimation algorithm combines the battery equivalent circuit model and measurement information for closed-loop calculation, and can perform online iterative correction on the SOC error, with high robustness.

[0041] (4) It can improve the stability and reliability of battery model parameter identification, and expand the Kalman filter algorithm parameters by adaptively adjusting the working conditions, making the SOC estimation process smoother and the estimation accuracy more accurate.

[0042] (5) The SOC error of ternary lithium can be corrected online iteratively within the entire SOC range, and the SOC error of lithium iron phosphate can be corrected online iteratively within a certain range, avoiding the cumulative error caused by the complete use of ampere-hour integration to calculate the SOC of lithium iron phosphate. Compared with the existing hybrid battery SOC estimation technology, it has better reliability.

[0043] (6) The target SOC that meets the conditions can be determined for different situations of the first SOC value and the second SOC value, thereby further improving the accuracy of the entire SOC of the battery pack to be tested and solving the problem of accurately estimating the SOC of the hybrid battery pack throughout its life cycle.

[0044] It should be noted that the technical effects brought about by any implementation method in the second to sixth aspects can refer to the technical effects brought about by the corresponding implementation method in the first aspect, and will not be repeated here.

[0045] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application, and do not constitute an improper limitation on the present application.

[0047] Figure 1 is a structural diagram of a battery SOC estimation system according to an exemplary embodiment;

[0048] Figure 2 is a flow chart showing a battery SOC estimation method according to an exemplary embodiment;

[0049] Figure 3 is a schematic diagram showing a preset mapping relationship according to an exemplary embodiment;

[0050] Figure 4 is a schematic diagram showing an SOC estimation algorithm according to an exemplary embodiment;

[0051] Figure 5 is a diagram of a Thevenin equivalent circuit model according to an exemplary embodiment;

[0052] Figure 6 is a schematic diagram showing an OCV-SOC relationship of a second battery according to an exemplary embodiment;

[0053] Figure 7 is a schematic diagram showing an SOC estimation result of a whole battery pack to be tested according to an exemplary embodiment;

[0054] Figure 8 is a block diagram of a battery SOC estimation device according to an exemplary embodiment;

[0055] Figure 9 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0056] In order to enable ordinary people in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0057] It should be noted that the terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0058] In related technologies, lithium iron phosphate batteries (second batteries) have become the mainstream energy storage units of current new energy vehicle power batteries due to their advantages of low cost, high safety, and long cycle life. However, due to the relatively wide voltage platform area, the battery state of charge (SOC) of lithium iron phosphate batteries is difficult to calculate accurately. If used under conditions of not being fully charged (charged to 100%) / fully discharged (battery is completely discharged) for a long time, it is easy to cause a large deviation in the estimated value of the lithium iron phosphate SOC, which will have a great impact on the battery management system (BMS) charge and discharge control, remaining power / energy, remaining mileage, etc. Therefore, inaccurate SOC estimation of lithium iron phosphate batteries has become a technical difficulty and user pain point in the industry.

[0059] Among mainstream power batteries, ternary lithium batteries (first batteries) have the characteristics of high energy density, good low-temperature performance, and linear voltage change, but at the same time they have problems such as high cost and poor safety. If ternary lithium batteries and lithium iron phosphate batteries are mixed into a group to complement each other's advantages, it can not only improve the safety of the entire package and reduce costs, but also use the linear voltage change characteristics of ternary lithium to solve the problem of inaccurate SOC estimation of lithium iron phosphate.

[0060] Since the batteries of the above two systems differ in self-discharge rate, aging rate, voltage-to-capacity ratio, etc., it is necessary to establish their own battery mathematical models based on their respective characteristics for SOC estimation.

[0061] In addition, the accuracy of the battery mathematical model is easily affected by the model parameters. In the current industry, the battery model parameters obtained based on offline test data identification usually have good accuracy for fresh batteries, but offline testing usually requires a long test cycle and the test samples and test granularity are relatively limited. At the same time, since battery parameters change with factors such as battery aging, temperature differences within the battery pack, and battery process / material differences, the battery model constructed by offline identified parameters lacks good adaptability in scenarios such as the entire life cycle, variable temperature environments, and large-scale battery grouping, which may reduce the SOC estimation accuracy. In addition, the initial parameters of the traditional extended Kalman filter algorithm are usually fixed values, but the actual operating conditions of the battery may not meet the algorithm's assumptions about noise, thereby affecting the algorithm's performance.

[0062] Currently, for SOC estimation of ternary lithium batteries (first battery) and lithium iron phosphate batteries (second battery), one method is to place a ternary lithium battery (first battery) inside the lithium iron phosphate battery (second battery), and based on the characteristics of the open circuit voltage-SOC curves of the two batteries, calibrate the initial SOC value by the open circuit voltage of the ternary lithium or lithium iron phosphate in different SOC ranges, and calculate the battery pack SOC by the ampere-hour integration method. This application uses the method of calibrating the initial SOC value to perform SOC estimation, which is essentially still based on ampere-hour integration. The SOC cannot be corrected during the calculation process. If the battery rest conditions are not met for a long time or the rest time calibration is unreasonable, the SOC calculation will still produce cumulative deviations.

[0063] Another method is to use the extended Kalman filter algorithm to obtain the estimated SOC value of the ternary lithium battery (first battery), and based on the characteristic that the change in the amount of charge of each single cell in the same time period of the series battery pack is the same, the estimated SOC value of the lithium iron phosphate battery (second battery) is calculated. In view of the possible self-discharge phenomenon of the lithium iron phosphate battery (second battery), a variable correction coefficient is introduced to perform feedback correction on the lithium iron phosphate SOC between two full-charge conditions. This application calculates the ternary lithium SOC through a model-based method, and calculates the lithium iron phosphate SOC based on the ampere-hour integral. It realizes the SOC estimation of the two system batteries with a lower computational burden, but this method only calibrates and corrects the SOC of the lithium iron phosphate battery (second battery) when fully charged. Since the lithium iron phosphate SOC is calculated using the ampere-hour integral, if the ternary lithium SOC estimation is inaccurate or fails, the SOC calculation of the lithium iron phosphate may have a large deviation. Both of the above methods have the problem that the estimation of the battery SOC is prone to deviation and inaccurate determination.

[0064] For ease of understanding, the battery SOC estimation method provided in this application is specifically introduced below with reference to the accompanying drawings.

[0065] Figure 11 is a structural diagram of a battery SOC estimation system 100 according to an exemplary embodiment. The battery SOC estimation system 100 includes a determination module 101 and a collection module 102 .

[0066] The determination module 101 may be a terminal device, which may be a mobile phone, a tablet computer, or a computer with wireless transceiver function, or a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a wireless terminal in unmanned driving, a wireless terminal in telemedicine, a wireless terminal in a smart grid, a wireless terminal in a smart city, a smart home, a vehicle-mounted terminal, etc.

[0067] The acquisition module 102 is used in the embodiment of the present application to obtain the initial SOC value of the first battery and the initial SOC value of the second battery in the battery pack to be tested, and send them to the determination module 101.

[0068] It should be noted that, in the following description of the battery SOC estimation method, the first battery may be a ternary lithium battery, and the second battery may be a lithium iron phosphate battery.

[0069] Figure 2 FIG. 1 is a flow chart of a battery SOC estimation method according to an exemplary embodiment. Figure 2 As shown, the battery SOC estimation method includes the following steps:

[0070] S201 : Obtain an initial SOC value of a first battery and an initial SOC value of a second battery in a battery pack to be tested.

[0071] In one possible implementation, the battery SOC estimation device can obtain the initial SOC value of the ternary lithium through the stored value of the EEPROM or the OCV of the battery after standing. N,0 At the same time, the battery SOC estimation device can also obtain the initial SOC value of the lithium iron phosphate through the storage value of the EEPROM or the OCV of the battery after standing, or obtain the initial SOC value of the lithium iron phosphate according to the preset mapping relationship SOC L,0 .

[0072] It is understandable that, when obtaining the initial SOC value of lithium iron phosphate according to the preset mapping relationship, L,0 When the battery SOC estimation device first obtains the initial SOC value SOC of the ternary lithium N,0 , based on the initial SOC value of ternary lithium SOC N,0 The initial SOC value SOC of lithium iron phosphate is obtained by the preset mapping relationship L,0 .

[0073] The preset mapping relationship is a mapping relationship between the SOC value of the first battery and the SOC value of the second battery.

[0074] The above preset mapping relationship is an SOC mapping relationship established based on the capacity of the first battery, the second battery and the available SOC range. The main process of the preset mapping relationship can be: the battery SOC estimation device can calculate the SOC value of the battery based on the capacity Q of the first battery. N And SOC available range Determine the actual available capacity of the first battery The battery SOC estimation device can be configured to estimate the battery SOC based on the capacity Q of the second battery. L And SOC available range Determine the actual available capacity of the second battery Furthermore, according to Q L,N With Q L,L The proportional relationship will Map to Specific manifestations such as Figure 3 As shown, assuming that the rated capacity of the first battery is Q N Set to 150Ah, the available range of the first battery NCM is 0%-97%, and the rated capacity of the second battery is Q L Set to 90Ah, the available range of the second battery LEP is 0%-100%, that is, 0% of the first battery NCM corresponds to 0% of the second battery LEP, and 97% of the first battery NCM corresponds to 100% of the second battery LEP. The mapping of areas between the ranges can be determined by linear interpolation.

[0075] S202 : Determine a first SOC value of the first battery according to the initial SOC value of the first battery and a first SOC estimation algorithm.

[0076] The first SOC value is a current SOC value of the first battery mapped to the SOC value of the second battery.

[0077] As a possible implementation manner, the battery SOC estimation device may substitute the initial SOC value of the first battery into the SOC estimation algorithm to calculate the current SOC value of the first battery, that is, the real-time estimated SOC value of the first battery.

[0078] Furthermore, the battery SOC estimation device can determine the current SOC value SOC of the first battery according to the preset mapping relationship mentioned in S201 above. N,k The corresponding first SOC value SOC P,k , such as SOC P,k =P(SOC N,k ), where SOC L,k =SOC P,k, P is the mapping process, which is performed using linear interpolation. It is understood that in the embodiment of the present application, the current SOC value of the first battery is converted and mapped to the SOC value of the same dimension as the second battery, which facilitates the subsequent more accurate fusion calculation of the SOC values ​​of the two batteries.

[0079] Among them, the SOC estimation algorithm is an estimation algorithm that combines the recursive least squares algorithm with time-varying forgetting factor (VFF-RLS) algorithm and the noise adaptive extended Kalman filter (AEKF) algorithm. For details, please refer to Figure 4 As shown in FIG. The battery SOC estimation device can establish a battery Thevenin model based on the equivalent circuit parameters and OCV-SOC function of the single battery in the test battery pack. The Thevenin model then inputs the real-time parameters collected from the battery pack under test into the Thevenin model for detection based on a preset VFF-RLS algorithm with a time-varying forgetting factor to obtain output results, including terminal voltage and terminal voltage residual.

[0080] The battery SOC estimation device is based on the preset noise adaptive extended Kalman filter AEKF algorithm and Thevenin model. According to the real-time parameters and output results of the battery pack to be tested, it jointly determines the highest SOC corresponding to the maximum single cell voltage in the real-time parameters and the lowest SOC corresponding to the minimum single cell voltage in the real-time parameters; based on the highest SOC and the lowest SOC, it determines the entire pack SOC of the battery pack to be tested.

[0081] In one example, the battery SOC estimation device can create an equivalent circuit model based on the equivalent circuit parameters of the single battery in the test battery pack, namely the Thevenin model, as shown in the following example: Figure 5 The equivalent circuit parameters may include but are not limited to the equivalent resistance and equivalent voltage of the single cell, and the equivalent circuit parameters are determined in a conventional manner.

[0082] Thevenin model can be expressed by formula 1:

[0083]

[0084] Among them, U p Indicates the battery polarization voltage, I indicates the current (charging is positive and discharging is negative), R0 indicates the ohmic internal resistance, R p Represents polarization internal resistance, C p Represents polarization capacitance, U t Indicates the battery terminal voltage, U ocv Indicates the battery open circuit voltage.

[0085] The battery SOC estimation device can use the VFF-RLS algorithm to estimate the open circuit voltage U in the Thevenin model. ocv, ohmic internal resistance R0, polarization internal resistance R p , polarization capacitance C p The identification results are substituted into the Thevenin model to obtain the terminal voltage and terminal voltage residual. The identification results include the open circuit voltage U ocv , ohmic internal resistance R0, polarization internal resistance Rp, polarization capacitance Cp and other parameters.

[0086] Among them, the VFF-RLS algorithm based on the time-varying forgetting factor can dynamically adjust the forgetting factor according to the residual of the battery terminal voltage estimation, improve the performance of the recursive least squares method (referring to the RLS algorithm) under dynamic conditions, and improve the stability and reliability of online parameter identification.

[0087] On the basis of FF-RLS, VFF-RLS adds the time-varying forgetting factor λ k Introduce the observation variance matrix for correction, λ k It can be expressed as formula 2:

[0088]

[0089]

[0090] Among them, λ min represents the time-varying forgetting factor λ k The lower limit of ρ is the value of λ for adjusting the time-varying forgetting factor. k Parameters, e k represents the terminal voltage residual identified by VFF-RLS at time k. In this embodiment, λ min =0.95,λ k ∈[0.95,1],ρ=0.5。

[0091] The battery SOC estimation device establishes a battery SOC calculation based on ampere-hour integration, and its characteristics are expressed as formula 3:

[0092]

[0093] Among them, SOC k+1 represents the SOC at time k+1, SOC0 represents the initial value of SOC, η represents the Coulomb coefficient, I represents the current, Δt represents the sampling period, Q n Indicates the rated capacity of the battery.

[0094] It is understandable that the battery SOC estimation device can determine an SOC value of the battery through Formula 3, and this SOC value is not the SOC value finally obtained in S202.

[0095] Based on the Thevenin model and combined with the SOC calculation of ampere-hour integration, the system state variable is x = (SOC, Up ), input u=I, output y=U t , establish the discrete state space equation of the system, whose characteristics can be expressed as formula 4:

[0096]

[0097] in R 0,k represents the ohmic internal resistance at time k, R p,k represents the polarization internal resistance at time k, τ k =R p,k C p,k is the time constant at time k, ω k represents state noise, v k represents the measurement noise.

[0098] The battery SOC estimation device calculates a correction value for the SOC value determined by the ampere-hour integral calculation using a discrete state-space equation, and combines the SOC value determined by the ampere-hour integral calculation with the correction value to determine the battery SOC value. The SOC value in this case may be the first SOC value of the first battery.

[0099] It should be noted that the preset algorithm is not only applicable to the calculation of the SOC of the first battery, but also to the calculation of the SOC of the second battery.

[0100] It is worth noting that based on the EKF algorithm, the AEKF algorithm can update the noise covariance according to the estimated terminal voltage residual. The updating process can be expressed as Formula 5:

[0101]

[0102] in, e k It represents the residual between the estimated terminal voltage and the measured terminal voltage, and N represents the window length of the residual sequence.

[0103] It should be noted that the above detailed description of the specific calculation method of each parameter involved in S202 is intended to more clearly illustrate the battery SOC estimation method described in the embodiment of the present disclosure, and should not be understood as limiting the specific implementation of the present disclosure.

[0104] S203 : Determine a second SOC value of the second battery based on the initial SOC value of the second battery and a preset method.

[0105] Among them, the preset method includes a second SOC estimation algorithm and / or a preset mapping relationship. When the initial SOC value of the second battery is less than the threshold value, the preset method is the SOC estimation algorithm. When the initial SOC value of the second battery is greater than the threshold value, the preset method is the preset mapping relationship; the preset mapping relationship is the mapping relationship between the SOC value of the first battery and the SOC value of the second battery.

[0106] In the embodiment of the present application, the second SOC estimation algorithm may be an estimation algorithm different from the first SOC estimation algorithm, or may be the same estimation algorithm.

[0107] It is worth noting that Figure 6 As shown, the linear region and the platform region are regions in the lithium iron phosphate OCV-SOC curve, and the rate of change in the linear region is greater than the rate of change in the platform region. The linear region can be understood as a region with a good linear relationship in the lithium iron phosphate OCV-SOC curve, corresponding to the case where the initial SOC value of the second battery is less than the threshold value, or the case where the rate of change corresponding to the initial SOC value of the second battery on the OCV-SOC curve is less than the threshold value.

[0108] In the embodiment of the present application, the interval of 0%-30% of SOC is a linear interval, and the platform area can be understood as an area where there is a longer OCV platform in the lithium iron phosphate OCV-SOC curve. In the embodiment of the present application, the interval of 0%-30% of SOC is a platform interval. In this platform area, there is a many-to-one mapping relationship between OCV and SOC, corresponding to the case where the initial SOC value of the second battery is greater than the threshold value, or the case where the corresponding rate of change of the initial SOC value of the second battery on the OCV-SOC curve is greater than the threshold value.

[0109] Optionally, in an embodiment of the present application, when the SOC value of the second battery is in a linear region, the preset method is an SOC estimation algorithm; when the SOC value of the second battery is in a platform region, the preset method is a preset mapping relationship.

[0110] In one possible implementation, the preset method includes an SOC estimation algorithm; when the initial SOC value of the second battery is less than a threshold value, the battery SOC estimation device can determine the expected SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm; when the expected SOC value is less than the threshold value, the battery SOC estimation device can determine the expected SOC value as the second SOC value.

[0111] In combination with the example in S202, when the initial SOC value of the second battery is less than the threshold (0%-30%), the battery SOC estimation device can substitute the initial SOC value of the second battery into the SOC estimation algorithm proposed in S202 to calculate the expected SOC value of the second battery.

[0112] Furthermore, the battery SOC estimation device can determine whether the expected SOC value of the second battery is in the linear area or the platform area in the lithium iron phosphate OCV-SOC curve. When the expected SOC value is less than the threshold, it means that the SOC estimation of the second battery is more suitable for determination by the SOC estimation algorithm, and the expected SOC value can be used as the second SOC value.

[0113] In another possible implementation, the preset method includes a preset mapping relationship; when the initial SOC value of the second battery is greater than a threshold value, the battery SOC estimation device can determine the expected SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship, and when the expected SOC value is greater than the threshold value, determine the expected SOC value as the second SOC value.

[0114] In combination with the examples in S201 and S202, when the initial SOC value of the second battery is greater than the threshold (30%-100%), the battery SOC estimation device can map the current SOC value of the first battery according to the preset mapping relationship proposed in S201 to obtain the expected SOC value of the second battery.

[0115] Furthermore, the battery SOC estimation device can determine whether the expected SOC value of the second battery is in the linear area or the platform area in the lithium iron phosphate OCV-SOC curve. When the expected SOC value is greater than the threshold, it means that the SOC estimation of the second battery is more suitable for determination through a preset mapping relationship, and the expected SOC value can be used as the second SOC value.

[0116] In another possible implementation, the preset method includes an SOC estimation algorithm and a preset mapping relationship; when the initial SOC value of the second battery is less than a threshold value, the battery SOC estimation device can determine the expected SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm, and when the expected SOC value is greater than the threshold value, the battery SOC estimation device determines the second SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship.

[0117] In combination with the examples in S201 and S202, when the initial SOC value of the second battery is less than the threshold value (0%-30%), the battery SOC estimation device can substitute the initial SOC value of the second battery into the SOC estimation algorithm proposed in S202 to calculate the expected SOC value of the second battery.

[0118] Furthermore, the battery SOC estimation device can determine that the expected SOC value of the second battery is in the linear area or the platform area in the lithium iron phosphate OCV-SOC curve. When the expected SOC value is greater than the threshold, it means that the SOC estimation of the second battery is more suitable for determination through a preset mapping relationship. The battery SOC estimation device can map the current SOC value of the first battery according to the preset mapping relationship proposed in S201 to obtain the second SOC value of the second battery.

[0119] In another possible implementation, the preset method includes an SOC estimation algorithm and a preset mapping relationship; when the initial SOC value of the second battery is greater than a threshold value, the battery SOC estimation device can determine the expected SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship, and when the expected SOC value is less than the threshold value, determine the second SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm.

[0120] In combination with the examples in S201 and S202, when the initial SOC value of the second battery is greater than the threshold (30%-100%), the battery SOC estimation device can map the current SOC value of the first battery according to the preset mapping relationship proposed in S201 to obtain the expected SOC value of the second battery.

[0121] Furthermore, the battery SOC estimation device can determine that the expected SOC value of the second battery is in the linear area or the platform area in the lithium iron phosphate OCV-SOC curve. When the expected SOC value is less than the threshold, it means that the SOC estimation of the second battery is more suitable for determination by the SOC estimation algorithm. The battery SOC estimation device can substitute the initial SOC value of the second battery into the SOC estimation algorithm proposed in S202 to calculate the second SOC value of the second battery.

[0122] S204 : Determine the entire SOC of the battery pack to be tested according to the first SOC value and / or the second SOC value.

[0123] As a possible implementation method, the battery SOC estimation device can determine the target SOC based on the first SOC value and / or the second SOC value, and determine the approximation coefficient based on the target SOC. Then, the battery SOC estimation device can substitute the approximation coefficient into a preset formula to obtain the SOC of the entire battery pack to be tested.

[0124] In one example, the battery SOC estimation device fuses the calculated first SOC value of the ternary lithium and / or the second SOC value of the lithium iron phosphate to obtain a target SOC, and then approximates the target SOC based on the ampere-hour integration to obtain the SOC of the entire pack.

[0125] Here, the approximation coefficient ω satisfies the following formula 6.

[0126]

[0127] Among them, SOC pack,k Indicates the SOC of the whole package at time k, SOC tar,k represents the target SOC at time k, SOC end Indicates the cutoff SOC for charging or discharging.

[0128] In the embodiment of the present application, the approximation coefficient ω is used to control the rate of unit growth and smooth the output.

[0129] Then, after determining the approximation coefficient ω, the battery SOC estimation device substitutes the approximation coefficient ω into the following formula 7 to determine the entire SOC of the battery pack to be tested, as follows: Figure 7 As shown in Figure 2, the SOC estimation results of the hybrid battery under CLTC conditions.

[0130]

[0131] Among them, Q pack Indicates the capacity of the entire package.

[0132] It is understood that because the second SOC value of the second battery can be determined based on the current SOC value of the first battery and a preset mapping relationship, the second SOC value of the second battery may coincide with the first SOC value of the first battery. Consequently, there are three scenarios when the battery SOC estimation device determines the target SOC. The following details how the battery SOC estimation device determines the target SOC.

[0133] As another possible implementation, when the first SOC value and the second SOC value are consistent, the battery SOC estimation device determines the target SOC to be either the first SOC value or the second SOC value.

[0134] In another example, the first SOC value is 35%, and the second SOC value is 35%, that is, the SOC values ​​of the batteries of the two systems are consistent, and only one of the SOC values ​​needs to be selected as the target SOC.

[0135] In another possible implementation, when the first SOC value and the second SOC value are inconsistent and the battery is in a charging process, the battery SOC estimation device determines the largest SOC value between the first SOC value and the second SOC value as the target SOC.

[0136] In another example, assuming that the second SOC value of the second battery is calculated by the SOC estimation algorithm, such as 40%, then the second SOC value is inconsistent with the first SOC value of the first battery, 35%. If the battery pack to be tested is charging at this time, the target SOC satisfies the following formula 8, that is, the largest SOC of the two system batteries is selected as the target SOC.

[0137] SOC tar,k =max(SOC P,k ,SOC L,k ) Formula 8

[0138] Among them, SOC tar,k is the target SOC at time k, SOC P,k is the first SOC value corresponding to the current SOC value of the first battery at time k, SOC L,k is a second SOC value of the second battery.

[0139] In another possible implementation, when the first SOC value and the second SOC value are inconsistent and during the discharge process, the battery SOC estimation device determines the minimum SOC value between the first SOC value and the second SOC value as the target SOC.

[0140] In another example, assuming that the second SOC value of the second battery is calculated by the SOC estimation algorithm, such as 40%, the first SOC value is inconsistent with the second SOC value of 35%. If the battery pack to be tested is discharged at this time, the target SOC satisfies the following formula 9, that is, the smallest SOC of the two system batteries is selected as the target SOC.

[0141] SOC tar,k =min(SOC P,k ,SOC L,k ) Formula 9

[0142] Among them, SOC tar,k is the target SOC at time k.

[0143] It should be pointed out that in the embodiment of the present application, the first battery is a ternary lithium battery as an example, and the second battery is a lithium iron phosphate battery as an example. The above description is for the purpose of more clearly illustrating the battery SOC estimation method recorded in the embodiment of the present disclosure, and should not be understood as a limitation on the specific implementation method of the present disclosure, that is, the embodiment of the present application does not limit the types of the first battery and the second battery.

[0144] Based on the above Figure 2The technical solution provided by the embodiment of the present application is a battery SOC estimation method, which calculates the first SOC value of the first battery through the initial SOC value of the first battery and the SOC estimation algorithm. The SOC estimation algorithm can improve the stability and reliability of battery model parameter identification. Furthermore, when determining the second SOC value of the second battery, it can be determined according to the SOC estimation algorithm or according to a preset mapping relationship. Using different methods to determine the second SOC value of the second battery can reduce the error of the second battery SOC, so as to improve the accuracy of the subsequent determination of the SOC of the entire battery pack to be tested. At the same time, the battery SOC estimation device can map the current SOC value to the first SOC value through a preset mapping relationship, which is beneficial to the subsequent calculation of the SOC of the entire pack, thereby at least solving the technical problem of inaccurate battery SOC estimation accuracy in the related art.

[0145] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, the battery SOC estimation device or electronic device includes a hardware structure and / or software module corresponding to the execution of each function. It should be easy for those skilled in the art to realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0146] In the embodiment of the present application, the battery SOC estimation device or electronic device can be divided into functional modules according to the above method. For example, the battery SOC estimation device or electronic device can include various functional modules corresponding to the various functional divisions, or two or more functions can be integrated into one processing module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0147] Figure 8 FIG. 1 is a block diagram of a battery SOC estimation device according to an exemplary embodiment. Figure 8The battery SOC estimation device 800 includes: a processing unit 802 and an acquisition unit 801; the acquisition unit 801 is used to acquire the initial SOC value of the first battery and the initial SOC value of the second battery in the battery pack to be tested; the processing unit 802 is used to determine a first SOC value of the first battery based on the initial SOC value of the first battery and a first SOC estimation algorithm; the first SOC value is the SOC value of the second battery mapped from the current SOC value of the first battery; the processing unit 802 is further used to determine a second SOC value of the second battery based on the initial SOC value of the second battery and a preset method; the preset method includes a second SOC estimation algorithm and / or a preset mapping relationship. When the initial SOC value of the second battery is less than a threshold value, the preset method is the SOC estimation algorithm; when the initial SOC value of the second battery is greater than the threshold value, the preset method is the preset mapping relationship; the preset mapping relationship is a mapping relationship between the SOC value of the first battery and the SOC value of the second battery; the processing unit 802 is further used to determine the entire SOC of the battery pack to be tested based on the first SOC value and / or the second SOC value.

[0148] In one possible embodiment, when the SOC value of the second battery is less than a threshold value, the preset method is an SOC estimation algorithm; when the SOC value of the second battery is greater than the threshold value, the preset method is a preset mapping relationship; the linear region and the platform region are regions in the lithium iron phosphate OCV-SOC curve; the rate of change in the linear region is greater than the rate of change in the platform region.

[0149] In one possible embodiment, the preset method includes an SOC estimation algorithm; the above-mentioned processing unit 802 is specifically used to: determine the expected SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm; the initial SOC value of the second battery is less than a threshold value; when the expected SOC value is less than the threshold value, determine the expected SOC value as the second SOC value.

[0150] In one possible embodiment, the preset method includes a preset mapping relationship; the above-mentioned processing unit 802 is specifically used to: determine the expected SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship; the initial SOC value of the second battery is greater than the threshold value; when the expected SOC value is greater than the threshold value, determine the expected SOC value as the second SOC value.

[0151] In one possible embodiment, the preset method includes an SOC estimation algorithm and a preset mapping relationship; the above-mentioned processing unit 802 is specifically used to: determine the expected SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm; the initial SOC value of the second battery is less than a threshold value; when the expected SOC value is greater than the threshold value, determine the second SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship.

[0152] In one possible embodiment, the preset method includes an SOC estimation algorithm and a preset mapping relationship; the above-mentioned processing unit 802 is specifically used to: determine the expected SOC value of the second battery based on the current SOC value of the first battery and the preset mapping relationship; the initial SOC value of the second battery is greater than a threshold value; when the expected SOC value is less than the threshold value, determine the second SOC value of the second battery based on the initial SOC value of the second battery and the SOC estimation algorithm.

[0153] In one possible implementation, the processing unit 802 is specifically configured to: determine a target SOC based on the first SOC value and / or the second SOC value; determine an approximation coefficient based on the target SOC; and substitute the approximation coefficient into a preset formula to obtain the entire SOC of the battery pack to be tested.

[0154] In one possible implementation, the processing unit 802 is specifically configured to: determine the target SOC to be either the first SOC value or the second SOC value when the first SOC value and the second SOC value are consistent; determine the maximum SOC value between the first SOC value and the second SOC value to be the target SOC when the first SOC value and the second SOC value are inconsistent and during the charging process; and determine the minimum SOC value between the first SOC value and the second SOC value to be the target SOC when the first SOC value and the second SOC value are inconsistent and during the discharging process.

[0155] In one possible implementation, the SOC of the entire battery pack to be tested satisfies the following preset formula:

[0156]

[0157] Among them, SOC pack,k is the SOC of the battery pack to be tested at time k, ω is the approximation coefficient, Q pack is the entire capacity of the battery pack to be tested.

[0158] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0159] Figure 9 FIG. 1 is a block diagram of an electronic device according to an exemplary embodiment. Figure 9 As shown, the electronic device 900 includes but is not limited to: a processor 901 and a memory 902 .

[0160] The memory 902 is configured to store executable instructions of the processor 901. It is understood that the processor 901 is configured to execute instructions to implement the battery SOC estimation method in the above embodiment.

[0161] It should be noted that those skilled in the art can understand that Figure 9 The electronic device structure shown in the figure does not limit the electronic device, and the electronic device may include Figure 9 More or fewer components may be shown, or certain components may be combined, or the components may be arranged differently.

[0162] The processor 901 is the control center of the electronic device. It uses various interfaces and lines to connect the various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 902 and calling data stored in the memory 902, it performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. The processor 901 may include one or more processing units. Optionally, the processor 901 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 901.

[0163] The memory 902 can be used to store software programs and various data. The memory 902 may mainly include a program storage area and a data storage area. The program storage area may store an operating system, application programs required by at least one functional module (such as a determination unit, a processing unit, etc.), etc. In addition, the memory 902 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0164] In an exemplary embodiment, a computer-readable storage medium including instructions is further provided, such as a memory 902 including instructions. The above instructions can be executed by the processor 901 of the electronic device 900 to implement the method in the above embodiment.

[0165] In actual implementation, Figure 8 The functions of the acquisition unit 801 and the processing unit 802 can be obtained by Figure 9 The processor 901 in the embodiment calls the computer program stored in the memory 902. The specific execution process can be referred to the description of the method part in the above embodiment, which will not be repeated here.

[0166] Optionally, the computer-readable storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0167] In an exemplary embodiment, the present application also provides a computer program product including one or more instructions, which can be executed by the processor 901 of the electronic device to implement the method in the above embodiment.

[0168] It should be noted that when the instructions in the above-mentioned computer-readable storage medium or one or more instructions in the computer program product are executed by the processor of the electronic device, the various processes of the above-mentioned method embodiment are implemented and the same technical effect as the above-mentioned method can be achieved. To avoid repetition, they will not be repeated here.

[0169] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete the full classification or partial functions described above.

[0170] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0171] The units described as separate components may or may not be physically separate, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0172] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0173] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the full classification part or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute the full classification part or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard drives, ROM, RAM, magnetic disks or optical disks.

[0174] The above are only specific embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or replacements within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A battery SOC estimation method, characterized in that: include: Obtaining an initial SOC value of a first battery and an initial SOC value of a second battery in the battery pack to be tested; determining a first SOC value of the first battery according to an initial SOC value of the first battery and a first SOC estimation algorithm; Determining a second SOC value of the second battery based on the initial SOC value of the second battery and a preset method; The preset method includes a second SOC estimation algorithm and / or a preset mapping relationship; When the initial SOC value of the second battery is less than a threshold value and the expected SOC value of the second battery is less than the threshold value, the preset method is the second SOC estimation algorithm; when the initial SOC value of the second battery is greater than the threshold value and the expected SOC value of the second battery is greater than the threshold value, the preset method is the preset mapping relationship; The estimated SOC value of the second battery is obtained based on the initial SOC value of the second battery and the second SOC estimation algorithm, or based on the current SOC value of the first battery and the preset mapping relationship algorithm, where the preset mapping relationship is a mapping relationship between the SOC value of the first battery and the SOC value of the second battery; The SOC of the entire battery pack to be tested is determined according to the first SOC value and / or the second SOC value.

2. The method according to claim 1, characterized in that The preset method includes the second SOC estimation algorithm; The determining, based on the initial SOC value of the second battery and a preset method, a second SOC value of the second battery includes: determining an estimated SOC value of the second battery based on an initial SOC value of the second battery and the second SOC estimation algorithm; the initial SOC value of the second battery being less than the threshold; When the estimated SOC value is less than the threshold, the estimated SOC value is determined to be the second SOC value.

3. The method according to claim 1, characterized in that The preset manner includes the preset mapping relationship; The determining, based on the initial SOC value of the second battery and a preset method, a second SOC value of the second battery includes: Determining an expected SOC value of the second battery based on a current SOC value of the first battery and the preset mapping relationship; an initial SOC value of the second battery is greater than the threshold; When the estimated SOC value is greater than the threshold, the estimated SOC value is determined to be the second SOC value.

4. The method according to claim 1, wherein The preset method includes the second SOC estimation algorithm and the preset mapping relationship; The determining, based on the initial SOC value of the second battery and a preset method, a second SOC value of the second battery includes: determining an estimated SOC value of the second battery based on an initial SOC value of the second battery and the second SOC estimation algorithm; the initial SOC value of the second battery being less than the threshold; When the estimated SOC value is greater than the threshold, a second SOC value of the second battery is determined based on the current SOC value of the first battery and the preset mapping relationship.

5. The method according to claim 1, wherein The preset method includes the second SOC estimation algorithm and the preset mapping relationship; The determining, based on the initial SOC value of the second battery and a preset method, a second SOC value of the second battery includes: Determining an expected SOC value of the second battery based on a current SOC value of the first battery and the preset mapping relationship; an initial SOC value of the second battery is greater than the threshold; In a case where the predicted SOC value is less than the threshold, a second SOC value of the second battery is determined based on the initial SOC value of the second battery and the second SOC estimation algorithm.

6. The method according to any one of claims 1 to 5, characterized in that The determining the entire SOC of the battery pack to be tested according to the first SOC value and / or the second SOC value includes: determining a target SOC according to the first SOC value and / or the second SOC value; Based on the target SOC, an approximation coefficient is determined; Substitute the approximation coefficient into a preset formula to obtain the entire SOC of the battery pack to be tested.

7. The method according to claim 6, characterized in that The determining the target SOC according to the first SOC value and / or the second SOC value includes: When the first SOC value and the second SOC value are consistent, determining the target SOC to be either the first SOC value or the second SOC value; When the first SOC value and the second SOC value are inconsistent and the charging process is in progress, determining the maximum SOC value between the first SOC value and the second SOC value as the target SOC; In the case that the first SOC value and the second SOC value are inconsistent and during the discharging process, the minimum SOC value between the first SOC value and the second SOC value is determined as the target SOC.

8. The method according to claim 1, characterized in that The SOC of the battery pack to be tested satisfies the following preset formula: in, is the SOC of the battery pack under test at time k, is the approximation coefficient, is the entire pack capacity of the battery pack to be tested.

9. The method according to claim 1, characterized in that The first SOC value is an SOC value of the second battery mapped from the current SOC value of the first battery.

10. The method according to any one of claims 1 to 9, characterized in that The first battery is a ternary lithium battery, and the second battery is a lithium iron phosphate battery.

11. A battery SOC estimation device, characterized in that: include: processing unit and acquisition unit; The acquiring unit is configured to acquire an initial SOC value of a first battery and an initial SOC value of a second battery in the battery pack to be tested; the processing unit is configured to determine a first SOC value of the first battery according to an initial SOC value of the first battery and a first SOC estimation algorithm; The first SOC value is an SOC value of the second battery mapped from the current SOC value of the first battery; The processing unit is further configured to determine a second SOC value of the second battery based on the initial SOC value of the second battery and a preset method; The preset manner includes a second SOC estimation algorithm and / or a preset mapping relationship. When the initial SOC value of the second battery is less than a threshold value and the expected SOC value of the second battery is less than the threshold value, the preset manner is the second SOC estimation algorithm. When the initial SOC value of the second battery is greater than a threshold value and the expected SOC value of the second battery is greater than the threshold value, the preset manner is the preset mapping relationship. The estimated SOC value of the second battery is obtained based on the initial SOC value of the second battery and the second SOC estimation algorithm, or based on the current SOC value of the first battery and the preset mapping relationship algorithm, where the preset mapping relationship is a mapping relationship between the SOC value of the first battery and the SOC value of the second battery; The processing unit is further configured to determine the entire SOC of the battery pack to be tested based on the first SOC value and / or the second SOC value.

12. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 10.

13. A battery module, characterized in that: The invention comprises a module body formed by connecting a plurality of single cells in series and / or in parallel and an electronic device as claimed in claim 12, wherein the module body is provided with a sensor electrically connected to the electronic device, and the sensor is used to detect the electrical parameters of each single cell in the plurality of single cells.

14. A computer-readable storage medium, characterized in that When the computer-executable instructions stored in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can perform the method according to any one of claims 1 to 10.

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