Battery peak power correction method, device, equipment and storage medium

Abstract

The present application relates to a method, device, equipment and storage medium for correcting the peak power of a battery. The method includes: obtaining battery parameters corresponding to a vehicle battery; determining the current ohmic internal resistance corresponding to the battery parameters; obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range according to the battery model corresponding to the vehicle battery; determining the initial peak power value corresponding to the battery parameters, and using the current ohmic internal resistance, the initial ohmic internal resistance and the cutoff ohmic internal resistance to correct the initial peak power value to obtain a peak power correction value. The present application takes into account the change in ohmic internal resistance within the battery's service life range, corrects the initial peak power value, and outputs a more accurate peak power correction value that is closest to the actual state of the vehicle battery, thereby avoiding the problem of the battery management system reporting undervoltage or overvoltage faults due to inaccurate peak power values.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a method, apparatus, device, and storage medium for correcting battery state of power (SOP). Background Art

[0002] Battery power performance has always been a key concern for electric vehicles, especially when calibrating them in winter and summer. Testing the battery's power performance is particularly important in order to accurately estimate the SOP. If the battery's peak power cannot be accurately estimated, the battery will be prone to overvoltage or undervoltage under extreme operating conditions of overcooling or overheating, causing the battery system to send an alarm signal to the entire vehicle and causing irreversible damage to the battery's health.

[0003] At present, the estimation of battery SOP mainly relies on the interpolation table provided by querying the battery core R&D department. The interpolation table is a three-dimensional interpolation table of SOP-SOC-temperature obtained by the battery core R&D department through repeated experiments to demonstrate the corresponding relationship between SOP, battery state of charge (State of Charge, abbreviated SOC) and temperature. In other words, current interpolation table is used to record the SOP value corresponding to the battery at different SOCs and different temperatures, so that after obtaining the current SOC value and temperature value, the current SOP value can be obtained by querying the interpolation table. However, during the use of the interpolation table, it is found that the SOP value obtained by querying the interpolation table is less accurate. If the SOP value obtained by directly querying the interpolation table is used, there will still be a problem of battery management system (Battery Management System, abbreviated BMS) reporting undervoltage or overvoltage fault. Therefore, how to provide a SOP estimation method with higher accuracy has become a problem urgently to be solved in this area. Summary of the Invention

[0004] The present application provides a method, apparatus, device and storage medium for correcting battery peak power to solve the problem of low accuracy of peak power values ​​obtained by querying an interpolation table.

[0005] In order to solve the above technical problems, the technical solution of this application is solved through the following embodiments:

[0006] An embodiment of the present application provides a method for correcting battery peak power, including: obtaining battery parameters corresponding to a vehicle battery; determining a current ohmic internal resistance corresponding to the battery parameters; obtaining an initial ohmic internal resistance and a cutoff ohmic internal resistance corresponding to the vehicle battery within a battery life range based on a battery model corresponding to the vehicle battery; determining an initial peak power value corresponding to the battery parameters, and, using the current ohmic internal resistance, the initial ohmic internal resistance, and the cutoff ohmic internal resistance, correcting the initial peak power value to obtain a corrected peak power value.

[0007] Wherein, the determining of the current ohmic internal resistance corresponding to the battery parameters includes: determining the current ohmic internal resistance corresponding to the battery parameters using a pre-trained ohmic internal resistance calculation model; wherein, before training the ohmic internal resistance calculation model, performing the following operations at each cycle stage of the sample battery of the battery model: under each preset initial sample state of charge value, using each preset sample discharge multiple, performing a discharge test on the sample battery to determine the discharge curve and battery parameters corresponding to each sample discharge multiple; wherein the battery parameters include at least the current cycle stage and discharge current of the sample battery; for each sample discharge multiple, calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the discharge curve corresponding to the sample discharge multiple; and determining the battery parameters corresponding to the sample discharge multiple as training samples, and setting the true ohmic internal resistance corresponding to the sample discharge multiple as the annotation of the training samples, so as to train the ohmic internal resistance calculation model using the annotated training samples.

[0008] The method of calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the discharge curve corresponding to the sample discharge multiple includes: obtaining a first discharge voltage, a second discharge voltage, a third discharge voltage, and a fourth discharge voltage in the discharge curve corresponding to the sample discharge multiple; wherein, in the discharge curve, the first discharge voltage is the discharge voltage corresponding to the initial discharge point; the second discharge voltage is the discharge voltage corresponding to the current change point; the third discharge voltage is the discharge voltage corresponding to the curve inflection point; and the fourth discharge voltage is the discharge voltage corresponding to the voltage stabilization point; obtaining the discharge current from the battery parameters corresponding to the sample discharge multiple; and calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the first discharge voltage, the second discharge voltage, the third discharge voltage, the fourth discharge voltage, and the discharge current.

[0009] Wherein, before obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range according to the battery model corresponding to the vehicle battery, it also includes: identifying a test battery that meets the preset battery state and has the battery model; wherein the types of battery states include: initial state and cutoff state; performing the following operations in each cycle stage of the test battery: at each preset initial test charge state value, using each preset test discharge multiple respectively, performing a discharge test on the test battery to determine the discharge curve corresponding to each test discharge multiple; for each test discharge multiple, calculating the ohmic internal resistance corresponding to the test discharge multiple according to the discharge curve corresponding to the test discharge multiple; selecting the ohmic internal resistance with the smallest value from the ohmic internal resistances calculated in each of the cycle stages of the test battery; when the battery state of the test battery is the initial state, determining the ohmic internal resistance with the smallest value as the initial ohmic internal resistance; when the battery state of the test battery is the cutoff state, determining the ohmic internal resistance with the smallest value as the cutoff ohmic internal resistance.

[0010] Among them, the identification of a test battery that meets a preset battery state and has the battery model includes: among the test batteries of the battery model, identifying a test battery that is in the first cycle stage as a test battery with an initial battery state; among the test batteries of the battery model, identifying a test battery whose discharge voltage is less than or equal to a preset cut-off voltage as a test battery with a cut-off battery state.

[0011] Among them, determining the peak power initial value corresponding to the battery parameters includes: querying the peak power prediction value corresponding to the charge state value, discharge voltage and discharge current in the battery parameters in the peak power mapping relationship corresponding to the current environmental parameters; obtaining a preset peak power interpolation value; and using the minimum value between the peak power prediction value and the peak power interpolation value as the peak power initial value.

[0012] Among them, the correcting the peak power by using the current ohmic internal resistance, the initial ohmic internal resistance and the cut-off ohmic internal resistance includes: calculating a correction coefficient based on the current ohmic internal resistance, the initial ohmic internal resistance and the cut-off ohmic internal resistance; calculating the product of the correction coefficient and the initial value of the peak power corresponding to the battery parameter, and using the product as the peak power correction value.

[0013] An embodiment of the present application also provides a battery peak power correction device, including: a first acquisition module, used to obtain battery parameters corresponding to a vehicle battery; a determination module, used to determine the current ohmic internal resistance corresponding to the battery parameters; a second acquisition module, used to obtain the initial ohmic internal resistance and cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range according to the battery model corresponding to the vehicle battery; a correction module, used to determine the initial peak power value corresponding to the battery parameters, and use the current ohmic internal resistance, the initial ohmic internal resistance and the cutoff ohmic internal resistance to correct the initial peak power value to obtain a peak power correction value.

[0014] An embodiment of the present application also provides a battery peak power correction device, comprising: at least one communication interface; at least one bus connected to the at least one communication interface; at least one processor connected to the at least one bus; and at least one memory connected to the at least one bus, wherein the processor is configured to: execute a battery peak power correction program stored in the memory to implement any of the above-mentioned battery peak power correction methods.

[0015] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed to implement any of the above-mentioned methods for correcting battery peak power.

[0016] The above technical solution provided by the embodiment of the present application has the following advantages over the prior art: the method provided by the embodiment of the present application can obtain the battery parameters corresponding to the vehicle battery; determine the current ohmic internal resistance corresponding to the battery parameters; obtain the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range according to the battery model corresponding to the vehicle battery; determine the initial peak power value corresponding to the battery parameters, and use the current ohmic internal resistance, the initial ohmic internal resistance and the cutoff ohmic internal resistance to correct the initial peak power value to obtain a peak power correction value. The embodiment of the present application takes into account the impact of ohmic internal resistance on peak power, considers the change in ohmic internal resistance within the service life range of the vehicle battery as a dependent variable, corrects the initial peak power value obtained by looking up the table, and outputs a more accurate peak power correction value that is closest to the actual state of the vehicle battery, thereby avoiding the problem of the battery management system reporting undervoltage or overvoltage faults due to inaccurate peak power values. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings. These exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements. Unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0020] Figure 1 Flowchart of a method for correcting battery peak power according to one embodiment of the present application;

[0021] Figure 2 The following is a flow chart of steps for obtaining training samples according to an embodiment of the present application;

[0022] Figure 3 is a schematic diagram of a discharge curve according to an embodiment of the present application;

[0023] Figure 4 Flowchart of the steps for determining the initial ohmic internal resistance and the cutoff ohmic internal resistance according to one embodiment of the present application;

[0024] Figure 5 1 is a structural diagram of a battery peak power correction device according to an embodiment of the present application;

[0025] Figure 6 2 is a structural diagram of a battery peak power correction device according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0027] The disclosure below provides many different embodiments or examples for implementing different structures of the present application. In order to simplify the disclosure of the present application, the components and settings of specific examples are described below. Of course, these are merely examples and are not intended to limit the present application. In addition, the present application may repeat reference numbers and / or letters in different examples. Such repetition is for the purpose of simplicity and clarity and does not in itself indicate the relationship between the various embodiments and / or settings discussed.

[0028] The embodiment of the present application provides a method for correcting the peak power of a battery. The execution subject of the embodiment of the present application is the vehicle system. Furthermore, the execution subject of the embodiment of the present application is the application layer software execution of the BMS. Figure 1 FIG. 1 is a flow chart of a method for correcting battery peak power according to an embodiment of the present application.

[0029] Step S110: Obtain battery parameters corresponding to the vehicle battery.

[0030] Types of vehicle batteries include but are not limited to: lithium iron phosphate and ternary lithium batteries.

[0031] In an embodiment of the present application, battery parameters corresponding to the vehicle battery can be obtained while the vehicle is driving.

[0032] Battery parameters indicate the current state of the vehicle's battery. These parameters include the vehicle's battery's state of charge, discharge ratio, discharge voltage, discharge current, and the current cycle stage. The current cycle stage is determined based on the number of charge and discharge cycles the vehicle has currently completed and the preset number of charge and discharge cycles for each cycle stage.

[0033] Specifically, based on the total number of charge and discharge cycles of the vehicle battery within the battery life range, the total number of charge and discharge cycles is divided into multiple cycle stages, and each cycle stage includes a preset number of charge and discharge cycles. After the vehicle battery begins to be used, the vehicle system records the number of charge and discharge cycles of the vehicle battery. Based on the preset number of charge and discharge cycles included in each cycle stage, the cycle stage of the vehicle battery can be determined. For example: each cycle stage includes 50 cycles (i.e., 50 charge and discharge cycles), and the vehicle system records that the vehicle battery is currently in the 30th cycle, then it can be determined that the vehicle battery is in the first cycle stage.

[0034] The battery life range refers to the time period from the beginning of use to the end of the vehicle battery's life.

[0035] The total number of charge and discharge cycles refers to the total number of charge and discharge cycles a vehicle battery can complete within its battery life. A charge and discharge cycle, also known as a full cycle, is the process from the start of charging to the end of discharging a battery. Generally, during the battery development phase, charge and discharge tests are performed on batteries of the same model to determine the corresponding battery life range and the total number of charge and discharge cycles the battery can complete within that life range.

[0036] Step S120: determining the current ohmic internal resistance corresponding to the battery parameters.

[0037] In the embodiment of the present application, a pre-trained ohmic internal resistance calculation model may be used to determine the current ohmic internal resistance corresponding to the battery parameters.

[0038] The ohmic internal resistance calculation model is a pre-trained machine learning model that determines the current ohmic internal resistance of a vehicle battery based on the corresponding battery parameters. The training process for the ohmic internal resistance calculation model will be described later and is not detailed here.

[0039] The current ohmic internal resistance refers to the current ohmic internal resistance of the vehicle battery. Considering that the ohmic internal resistance of the vehicle battery increases with battery usage time, the embodiment of the present application utilizes an ohmic internal resistance calculation model to determine the current ohmic internal resistance corresponding to the battery parameters.

[0040] Step S130 , obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life interval according to the battery model corresponding to the vehicle battery.

[0041] Initial ohmic internal resistance refers to the ohmic internal resistance of the vehicle battery in its initial state. The initial state refers to the battery state when the vehicle battery is first used.

[0042] End-of-life ohm refers to the ohmic internal resistance of the vehicle battery in its end-of-life state. End-of-life refers to the battery state at the end of its life.

[0043] Specifically, during the battery development phase, during charge and discharge testing of a test battery of the battery model, the initial ohmic internal resistance and cutoff ohmic internal resistance corresponding to the battery model within the battery life range are determined. The initial ohmic internal resistance and cutoff ohmic internal resistance corresponding to the battery model within the battery life range can be stored in the vehicle system.

[0044] Step S140 , determining an initial peak power value corresponding to the battery parameter, and correcting the initial peak power value using the current ohmic internal resistance, the initial ohmic internal resistance, and the cutoff ohmic internal resistance to obtain a corrected peak power value.

[0045] In the embodiment of the present application, the peak power initial value corresponding to the battery parameter can be queried according to the preset peak power mapping relationship.

[0046] The peak power mapping relationship is used to represent the mapping relationship between the state of charge value, discharge current, discharge voltage, and peak power prediction value. Different peak power mapping relationships can be pre-set for different environmental parameters. Environmental parameters include: ambient temperature and / or ambient operating conditions.

[0047] Furthermore, different peak power mapping relationships are set for different ambient temperature ranges. The peak power mapping relationship can be set as a peak power interpolation table. For example: an ambient temperature greater than 35 degrees corresponds to a peak power interpolation table; an ambient temperature less than or equal to 35 degrees and greater than or equal to -20 degrees corresponds to a peak power interpolation table; an ambient temperature less than -20 degrees and greater than -40 degrees corresponds to a peak power interpolation table.

[0048] Furthermore, the current environmental parameters are detected; in the peak power mapping relationship corresponding to the current environmental parameters, the peak power prediction value corresponding to the charge state value, discharge voltage and discharge current in the battery parameters is queried; a preset peak power interpolation value is obtained; and the minimum value between the peak power prediction value and the peak power interpolation value is used as the peak power initial value.

[0049] Peak power interpolation refers to the integration of power measured during the battery development phase when the vehicle speed parameter reaches an extreme value. In other words, peak power interpolation is the instantaneous power value obtained by the battery manufacturer through pulse discharge current testing. Typically, the extreme speed parameter state lasts for 10 seconds, and peak power interpolation is the integral of the product of the current and voltage values ​​during these 10 seconds.

[0050] A correction coefficient is calculated according to the current ohmic internal resistance, the initial ohmic internal resistance and the cut-off ohmic internal resistance; a product of the correction coefficient and the initial peak power value corresponding to the battery parameter is calculated, and the product is used as the peak power correction value.

[0051] For example, the following formula can be used to determine the correction factor and peak power correction value:

[0052]

[0053] Where η represents the correction coefficient; R current Indicates the current ohmic internal resistance; R initial Represents the initial ohmic internal resistance; R end Indicates the cut-off ohmic internal resistance.

[0054] SOP 修正 =SOP 初始 *η;

[0055] Among them, SOP 修正 Indicates the peak power correction value; SOP 初始 Indicates the initial value of peak power.

[0056] In an embodiment of the present application, battery parameters corresponding to a vehicle battery are obtained; a current ohmic internal resistance corresponding to the battery parameters is determined; an initial ohmic internal resistance and a cutoff ohmic internal resistance corresponding to the vehicle battery within a battery life range are obtained based on a battery model corresponding to the vehicle battery; an initial peak power value corresponding to the battery parameters is determined, and the initial peak power value is corrected using the current ohmic internal resistance, the initial ohmic internal resistance, and the cutoff ohmic internal resistance to obtain a corrected peak power value. The embodiments of the present application take into account the impact of ohmic internal resistance on peak power. As the vehicle battery ages, the ohmic internal resistance of the vehicle battery will gradually increase. For example, the ohmic internal resistance of the battery is 10 milliohms when it leaves the factory. As it is used, the ohmic internal resistance changes to 20 milliohms at the end of the battery life. This change will cause the discharge current allowed to be output by the vehicle battery to decrease. Moreover, when the ohmic internal resistance is large, using a larger current to discharge will cause higher heat loss in the vehicle battery, and the vehicle battery will have the risk of spontaneous combustion. Therefore, the embodiments of the present application take the change in ohmic internal resistance within the service life range of the vehicle battery as a dependent variable to be considered, and correct the initial peak power value obtained by looking up the table to output a more accurate peak power correction value that is closest to the actual state of the vehicle battery, so as to avoid the problem of the battery management system reporting undervoltage or overvoltage faults due to inaccurate peak power values.

[0057] In order to make the present application easier to understand, the method for correcting the vehicle peak power of an embodiment of the present application will be further described below.

[0058] In this embodiment of the present application, before executing the battery peak power correction method, it is necessary to train the ohmic internal resistance calculation model. Before training the ohmic internal resistance calculation model, it is necessary to prepare training samples. The training battery model used in the training process is the same as the vehicle battery model.

[0059] Furthermore, the ohmic internal resistance calculation model can be a Thevenin model (Thevenin model). The battery equivalent model is to model the relevant parameters inside the battery, such as ohmic internal resistance, polarization internal resistance, and other parameters that cannot be directly measured. By designing the corresponding formula by the battery equivalent model, the internal parameters or capacity state of the battery can be predicted. The Thevenin model adds polarization resistance and polarization capacitance on the basis of the Rint model (internal resistance model), which improves the accuracy of the model. Therefore, the Thevenin model is widely used. The Rint model is an internal resistance model. The origin of the internal resistance model is because it takes into account that when the battery is discharged, not all the energy is added to the load, but a part of it is consumed by its own internal resistance. Therefore, this part is visualized as a resistance model, but the Rint model accuracy is not very high, and Thevenin can make up for this shortcoming.

[0060] like Figure 2FIG. 1 shows a flow chart of steps for obtaining training samples according to an embodiment of the present application. Figure 2 The following table shows the execution process of a sample battery of the same battery model in one cycle stage. Figure 2 Just execute it.

[0061] Before training the ohmic internal resistance calculation model, the following operations are performed at each cycle stage of the sample battery of the battery model:

[0062] Step S210, under each preset initial sample state of charge value, using each preset sample discharge multiple, performing a discharge test on the sample battery, and determining the discharge curve and battery parameters corresponding to each of the sample discharge multiples; wherein the battery parameters include at least the current cycle stage and discharge current of the sample battery.

[0063] The initial sample state of charge value refers to the state of charge value that the sample battery needs to have in this round of charging and discharging.

[0064] The sample discharge multiple refers to the discharge multiple that the sample battery needs to have during this charge and discharge.

[0065] The discharge curve refers to the curve of the discharge voltage during the current charge and discharge process. In the embodiment of the present application, different initial sample charge state values ​​and different sample discharge multiples can be selected to start the discharge experiment, and then the sample is left to stand for processing to obtain the voltage curve.

[0066] Furthermore, multiple initial sample state of charge values ​​and multiple sample discharge multiples are pre-set. The embodiment of the present application performs multiple rounds of charge and discharge experiments; each round of charge and discharge experiments uses one of the initial sample state of charge values, and each round of charge and discharge experiments includes multiple charge and discharge experiments, each of which uses one of the sample discharge multiples.

[0067] Step S220 , for each of the sample discharge multiples, calculating the true ohmic internal resistance corresponding to the sample discharge multiple according to the discharge curve corresponding to the sample discharge multiple.

[0068] The true ohmic internal resistance refers to the actual ohmic internal resistance of the vehicle battery at the current initial sample state of charge and the current sample discharge multiple. The true ohmic internal resistance is the actual value used when training the ohmic internal resistance calculation model.

[0069] In the discharge curve corresponding to the sample discharge multiple, a first discharge voltage, a second discharge voltage, a third discharge voltage, and a fourth discharge voltage are obtained; wherein, in the discharge curve, the first discharge voltage is the discharge voltage corresponding to the discharge initial point; the second discharge voltage is the discharge voltage corresponding to the current change point; the third discharge voltage is the discharge voltage corresponding to the curve inflection point; and the fourth discharge voltage is the discharge voltage corresponding to the voltage stabilization point; in the battery parameters corresponding to the sample discharge multiple, the discharge current is obtained; and based on the first discharge voltage and the second discharge voltage, the third discharge voltage and the fourth discharge voltage and the discharge current, the true ohmic internal resistance corresponding to the sample discharge multiple is calculated.

[0070] Furthermore, the positions of the discharge initial point, current change point, curve inflection point, and voltage stabilization point can be determined in the discharge curve according to the slope change. The slope refers to the slope of the tangent line to a point on the discharge curve.

[0071] The discharge initial point refers to the first point in the discharge curve. The voltage corresponding to the discharge initial point is the first discharge voltage.

[0072] The current change point is the point with the largest slope in the descending portion of the discharge curve. The voltage corresponding to this current change point is the second discharge voltage. During discharge, the output current of the sample battery changes with battery performance. At this current change point, the sample battery stops outputting current, and the current changes. From this current change point onward, the voltage changes from a rapid change to a slow change, causing the slope of the current change point to become steeper.

[0073] The inflection point of the curve is the inflection point of the discharge curve, where the slope of the descending curve portion of the discharge curve is the smallest. The voltage corresponding to the inflection point of the curve is the third discharge voltage.

[0074] The voltage stabilization point is the point in the rising curve of the discharge curve where the slope is the smallest. The voltage corresponding to this voltage stabilization point is the fourth discharge point cloud. After this voltage stabilization point, the voltage fluctuation stops and remains unchanged.

[0075] For example: Figure 3 Schematic diagram of a discharge curve according to an embodiment of the present application. Select the first discharge voltage U1 ( Figure 3 1) and the second discharge voltage U2 ( Figure 3 2) and the third discharge voltage U3 ( Figure 3 3) and the fourth discharge voltage U4 ( Figure 3 4); obtain the discharge current I from the battery parameters corresponding to the current sample discharge multiple; calculate the actual ohmic internal resistance R using the following formula a :

[0076]

[0077] Step S230 , determining the battery parameters corresponding to the sample discharge multiples as training samples, and setting the true ohmic internal resistance corresponding to the sample discharge multiples as the labels of the training samples, so as to train the ohmic internal resistance calculation model using the labeled training samples.

[0078] For example, at each cycle stage of the sample battery, the following steps are used to obtain training samples:

[0079] Step S1 : sequentially obtaining an initial sample state of charge value from a plurality of preset initial sample state of charge values.

[0080] Step S2: sequentially obtain a sample discharge multiple from a plurality of preset sample discharge multiples.

[0081] Step S3 , performing a discharge test on the sample battery at the current initial sample state of charge value and the current sample discharge multiple to determine a discharge curve and battery parameters.

[0082] Step S4: determining the true ohmic internal resistance according to the currently determined discharge curve; using the battery parameters as training samples, and the true ohmic internal resistance as a label for the battery parameters.

[0083] Step S5, determining whether all sample discharge multiples have been acquired; if so, executing step S6; if not, executing step S2.

[0084] Step S6, determining whether all initial sample charge state values ​​have been acquired; if so, ending the process; if not, executing step S1.

[0085] After obtaining multiple training samples, multiple trainings are performed on the ohmic internal resistance calculation model until the ohmic internal resistance calculation model converges. Specifically: in each training, the training sample is input into the ohmic internal resistance calculation model to obtain the predicted ohmic internal resistance output by the ohmic internal resistance calculation model; the loss value between the predicted ohmic internal resistance and the actual ohmic internal resistance marked by the training sample is calculated using a preset loss function; if the loss value is greater than or equal to the preset loss value, the parameters in the ohmic internal resistance calculation model are adjusted, and the next training is continued; if the loss value is less than the loss threshold, it is determined whether the ohmic internal resistance calculation model meets the preset convergence condition; if the convergence condition is met, it is determined that the ohmic internal resistance calculation model has converged and can be applied in the battery peak power correction method of the embodiment of the present application; if the convergence condition is not met, the next training is continued. Convergence conditions include: the ohmic internal resistance calculation model has reached a preset number of training times or the loss value of the ohmic internal resistance calculation model has been less than the loss threshold for a preset number of consecutive times.

[0086] In the embodiment of the present application, before executing the battery peak power correction method, it is necessary to determine the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range.

[0087] Furthermore, a test battery that meets a preset battery state and has the battery model is identified; wherein the types of the battery state include: an initial state and a cut-off state.

[0088] Among the test batteries of the battery model, the test battery in the first cycle stage is identified as the test battery in the initial state. The first cycle stage refers to the first cycle stage of the test battery after leaving the factory. The test battery in this cycle stage can be understood as a new battery with a low ohmic internal resistance.

[0089] Among the test batteries of the battery model, test batteries with a discharge voltage less than or equal to a preset cutoff voltage are identified as test batteries with a battery status of cutoff. The cutoff voltage is used to measure whether the test battery is nearing the end of its life. When the discharge voltage of the test battery is less than or equal to the cutoff voltage, it indicates that the test battery is nearing the end of its life.

[0090] Furthermore, the test battery of the battery model that meets the preset battery state is executed at each cycle stage. Figure 4 The steps shown can obtain the initial ohmic internal resistance and cut-off ohmic internal resistance corresponding to the test battery.

[0091] Furthermore, the model of the test battery is the same as the model of the vehicle battery.

[0092] like Figure 4 , which is a flow chart of the steps for determining the initial ohmic internal resistance and the cut-off ohmic internal resistance according to an embodiment of the present application.

[0093] In step S410 , at each preset initial test state of charge value, each preset test discharge multiple is used to perform a discharge test on the test battery, and a discharge curve corresponding to each test discharge multiple is determined.

[0094] The initial test state of charge value refers to the state of charge value that the battery needs to have during this round of charge and discharge.

[0095] The test discharge multiple refers to the discharge multiple that the battery needs to have during this charge and discharge test.

[0096] The discharge curve refers to the curve of the change of discharge voltage during the current charge and discharge process.

[0097] Furthermore, multiple initial test charge state values ​​and multiple test discharge multiples are pre-set. The embodiment of the present application performs multiple rounds of charge and discharge experiments; each round of charge and discharge experiments uses one of the initial test charge state values, and each round of charge and discharge experiments includes multiple charge and discharge experiments, and each charge and discharge experiment uses one of the test discharge multiples. For the specific process, please refer to Figure 3 Steps shown.

[0098] Step S420 , for each of the test discharge multiples, calculating the ohmic internal resistance corresponding to the test discharge multiple according to the discharge curve corresponding to the test discharge multiple.

[0099] In a discharge curve corresponding to the test discharge multiple, a first discharge voltage, a second discharge voltage, a third discharge voltage, and a fourth discharge voltage are obtained; wherein the first discharge voltage and the second discharge voltage have the same slope, and the third discharge voltage and the fourth discharge voltage have the same slope; in a battery parameter corresponding to the test discharge multiple, a discharge current is obtained; and based on the first discharge voltage and the second discharge voltage, the third discharge voltage and the fourth discharge voltage, and the discharge current, the ohmic internal resistance corresponding to the test discharge multiple is calculated.

[0100] Step S430 , selecting the smallest ohmic internal resistance from the ohmic internal resistances calculated at each cycle stage of the test battery.

[0101] In each of the multiple cycle stages, multiple ohmic internal resistances can be calculated for each initial test state of charge value; among all the calculated ohmic internal resistances, the minimum value is selected. The minimum value represents the ohmic internal resistance of the test battery at the time of the healthiest state of charge.

[0102] Step S440 , when the battery state of the test battery is the initial state, determining the ohmic internal resistance with the smallest value as the initial ohmic internal resistance; when the battery state of the test battery is the cut-off state, determining the ohmic internal resistance with the smallest value as the cut-off ohmic internal resistance.

[0103] After obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the test battery within the battery life range, the variation range of the ohmic internal resistance of the test battery within the battery life range can be determined. Furthermore, after obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the test battery within the battery life range, the initial ohmic internal resistance and the cutoff ohmic internal resistance can be stored in a vehicle system. The vehicle battery used in the vehicle system is the same model as the test battery.

[0104] If multiple test batteries of the same battery model are tested, the average value of the initial ohmic internal resistance corresponding to the multiple test batteries can be calculated as the initial ohmic internal resistance corresponding to the battery model, and the average value of the cutoff ohmic internal resistance corresponding to the multiple test batteries can be calculated as the cutoff ohmic internal resistance corresponding to the battery model.

[0105] In an embodiment of the present application, while the vehicle is traveling, a speed parameter of the vehicle is detected; when an extreme value of the speed parameter is detected, a battery parameter of the vehicle battery is acquired.

[0106] The vehicle speed parameter is used to indicate the current vehicle speed state. The vehicle speed parameter includes: vehicle speed and / or vehicle acceleration.

[0107] As a vehicle moves, its speed and / or acceleration constantly change, and these changes are recorded. When extreme speed and / or acceleration are detected, the vehicle's battery parameters are acquired. These parameters include the vehicle's battery's state of charge, discharge multiple, discharge voltage, discharge current, and cycle stage at the current time.

[0108] Furthermore, when the vehicle speed reaches an extreme value, a CAN signal is generated. Therefore, when this CAN signal is detected, it indicates that an extreme speed value has been detected. Since the slope of the vehicle speed is acceleration, changes in the slope of the vehicle speed can be detected. When an extreme slope value is detected, it indicates that an extreme acceleration value has been detected.

[0109] In an embodiment of the present application, after obtaining the battery parameters of the vehicle battery, the battery parameters are first input into a trained ohmic internal resistance calculation model to obtain the current ohmic internal resistance corresponding to the battery parameters output by the ohmic internal resistance calculation model. Then, based on the battery model corresponding to the vehicle battery, the initial ohmic internal resistance and cutoff ohmic internal resistance corresponding to the battery model are obtained from the vehicle system. Finally, the initial peak power value corresponding to the battery parameters is queried through a preset peak power mapping relationship, and the current ohmic internal resistance, the initial ohmic internal resistance, and the cutoff ohmic internal resistance are used to correct the initial peak power value to obtain a peak power correction value.

[0110] The peak power mapping relationship can be reflected in a peak power interpolation table. The peak power interpolation table is obtained by adjusting the peak power basic interpolation table specified in the standard according to environmental parameters. The standard is, for example, GBT 31467.1-2015. Furthermore, different peak power interpolation tables can be set for different environmental parameters.

[0111] Specifically, based on a preset peak power basic interpolation table, a battery discharge test can be performed in advance under each environmental parameter. Under each environmental parameter, the charge state value, discharge voltage, discharge current, and peak power value in each set of mapping relationships are adjusted to form a peak power interpolation table corresponding to the environmental parameter. Environmental parameters include: ambient temperature and / or ambient operating conditions.

[0112] Environmental operating conditions include but are not limited to: NEDC (New Europe Drive Cycle), WLTC (Worldwide Harmonized Light Vehicles Test Cycle), CLTC (China Light-duty Vehicle Test Cycle) and suburban extreme conditions.

[0113] For example, when adjusting the peak power base interpolation table, consider temperature, uphill and downhill slopes (environmental conditions), and vehicle speed: In winter scenarios, due to the lower temperatures, the battery's power generation performance will be reduced. Therefore, when adjusting the peak power base interpolation table, the peak power prediction value should be reduced at the same discharge voltage and discharge current. In summer scenarios, due to the higher temperatures, the battery's charging, discharging, and power generation performance will be improved. Therefore, when adjusting the peak power base interpolation table, the peak power prediction value should be increased at the same discharge voltage and discharge current. In uphill and acceleration scenarios, the vehicle's power system needs to provide more power to maintain or increase the vehicle speed, which increases the battery's discharge power demand. Therefore, at the same discharge voltage and discharge current, the peak power prediction value should be increased to cope with the increased power demand when going uphill or accelerating. In downhill and deceleration scenarios, the opposite is true, and the peak power prediction value needs to be reduced.

[0114] An example of a peak power interpolation table is shown in Table 1. Of course, those skilled in the art should know that Table 1 is only for illustrating the embodiment of the present application and is not intended to limit the embodiment of the present application.

[0115]

[0116]

[0117] Table 1

[0118] In Table 1, the values ​​in the environmental conditions column represent the corresponding relationship between the state of charge value, discharge voltage, discharge current and peak power prediction value when the vehicle speed extreme value is detected under the environmental conditions. The extreme value in Table 1 is the vehicle speed extreme value v max and the acceleration extreme value a max The maximum value in .

[0119] Currently, battery peak power has always been a focus of battery manufacturers, and battery manufacturers have invested a lot of equipment and manpower in this area in order to have a deeper understanding of the battery power state and meet the power needs of consumers. In addition, battery peak power has a significant impact on the acceleration and other performance of electric vehicles. Therefore, accurately estimating battery peak power has long-term significance for the healthy development of the battery industry. The embodiment of the present application considers the impact of ohmic internal resistance on battery peak power, introduces the ohmic internal resistance of the vehicle battery, and corrects the peak power value to make the peak power value more accurate, so as to avoid the risk of over-discharge of the battery system and irreversible damage to the battery.

[0120] The embodiments of the present application can accurately estimate the peak power value of the battery, prevent the battery from being abused, causing overcharging or over-discharging of the battery, and protect the health of the battery; the embodiments of the present application can help the entire vehicle to more clearly understand the power of the current battery system, avoiding complaints from customers when using it; the embodiments of the present application help to standardize the functions of industry algorithm software, making it easier to upgrade and iterate.

[0121] The present application also provides a device for correcting the peak power of a battery. Figure 5 FIG. 1 is a structural diagram of a battery peak power correction device according to an embodiment of the present application.

[0122] The battery peak power correction device includes:

[0123] The first acquisition module 510 is configured to acquire battery parameters corresponding to the vehicle battery.

[0124] The determination module 520 is configured to determine the current ohmic internal resistance corresponding to the battery parameters.

[0125] The second acquisition module 530 is configured to acquire the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life interval according to the battery model corresponding to the vehicle battery.

[0126] The correction module 540 is configured to determine an initial peak power value corresponding to the battery parameter, and correct the initial peak power value using the current ohmic internal resistance, the initial ohmic internal resistance, and the cutoff ohmic internal resistance to obtain a corrected peak power value.

[0127] The functions of the device described in the embodiment of the present application have been described in the above method embodiment. Therefore, for any details not fully described in the description of this embodiment, please refer to the relevant description in the above embodiment and will not be repeated here.

[0128] The present application also provides a battery peak power correction device, such as Figure 6, which is a structural diagram of a battery peak power correction device according to an embodiment of the present application.

[0129] The battery peak power correction device includes a processor 610 , a communication interface 620 , a memory 630 , and a communication bus 640 . The processor 610 , the communication interface 620 , and the memory 630 communicate with each other via the communication bus 640 .

[0130] The memory 630 is used to store computer programs.

[0131] In one embodiment of the present application, the processor 610, when executing the program stored on the memory 630, implements the battery peak power correction method provided by any of the aforementioned method embodiments, including: obtaining battery parameters corresponding to the vehicle battery; determining the current ohmic internal resistance corresponding to the battery parameters; obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range according to the battery model corresponding to the vehicle battery; determining the peak power initial value corresponding to the battery parameters, and using the current ohmic internal resistance, the initial ohmic internal resistance and the cutoff ohmic internal resistance to correct the peak power initial value to obtain a peak power correction value.

[0132] Wherein, the determining of the current ohmic internal resistance corresponding to the battery parameters includes: determining the current ohmic internal resistance corresponding to the battery parameters using a pre-trained ohmic internal resistance calculation model; wherein, before training the ohmic internal resistance calculation model, performing the following operations at each cycle stage of the sample battery of the battery model: under each preset initial sample state of charge value, using each preset sample discharge multiple, performing a discharge test on the sample battery to determine the discharge curve and battery parameters corresponding to each sample discharge multiple; wherein the battery parameters include at least the current cycle stage and discharge current of the sample battery; for each sample discharge multiple, calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the discharge curve corresponding to the sample discharge multiple; and determining the battery parameters corresponding to the sample discharge multiple as training samples, and setting the true ohmic internal resistance corresponding to the sample discharge multiple as the annotation of the training samples, so as to train the ohmic internal resistance calculation model using the annotated training samples.

[0133] The method of calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the discharge curve corresponding to the sample discharge multiple includes: obtaining a first discharge voltage, a second discharge voltage, a third discharge voltage, and a fourth discharge voltage in the discharge curve corresponding to the sample discharge multiple; wherein, in the discharge curve, the first discharge voltage is the discharge voltage corresponding to the initial discharge point; the second discharge voltage is the discharge voltage corresponding to the current change point; the third discharge voltage is the discharge voltage corresponding to the curve inflection point; and the fourth discharge voltage is the discharge voltage corresponding to the voltage stabilization point; obtaining the discharge current from the battery parameters corresponding to the sample discharge multiple; and calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the first discharge voltage, the second discharge voltage, the third discharge voltage, the fourth discharge voltage, and the discharge current.

[0134] Wherein, before obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range according to the battery model corresponding to the vehicle battery, it also includes: identifying a test battery that meets the preset battery state and has the battery model; wherein the types of battery states include: initial state and cutoff state; performing the following operations in each cycle stage of the test battery: at each preset initial test charge state value, using each preset test discharge multiple respectively, performing a discharge test on the test battery to determine the discharge curve corresponding to each test discharge multiple; for each test discharge multiple, calculating the ohmic internal resistance corresponding to the test discharge multiple according to the discharge curve corresponding to the test discharge multiple; selecting the ohmic internal resistance with the smallest value from the ohmic internal resistances calculated in each of the cycle stages of the test battery; when the battery state of the test battery is the initial state, determining the ohmic internal resistance with the smallest value as the initial ohmic internal resistance; when the battery state of the test battery is the cutoff state, determining the ohmic internal resistance with the smallest value as the cutoff ohmic internal resistance.

[0135] Among them, the identification of a test battery that meets a preset battery state and has the battery model includes: among the test batteries of the battery model, identifying a test battery that is in the first cycle stage as a test battery with an initial battery state; among the test batteries of the battery model, identifying a test battery whose discharge voltage is less than or equal to a preset cut-off voltage as a test battery with a cut-off battery state.

[0136] Among them, determining the peak power initial value corresponding to the battery parameters according to a preset peak power interpolation table includes: querying the peak power prediction value corresponding to the charge state value, discharge voltage and discharge current in the battery parameters in the peak power mapping relationship corresponding to the current environmental parameters; obtaining a preset peak power interpolation value; and using the minimum value between the peak power prediction value and the peak power interpolation value as the peak power initial value.

[0137] Among them, the correcting the peak power by using the current ohmic internal resistance, the initial ohmic internal resistance and the cut-off ohmic internal resistance includes: calculating a correction coefficient based on the current ohmic internal resistance, the initial ohmic internal resistance and the cut-off ohmic internal resistance; calculating the product of the correction coefficient and the initial value of the peak power corresponding to the battery parameter, and using the product as the peak power correction value.

[0138] The present application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the steps of the battery peak power correction method provided in any of the aforementioned method embodiments. Since the battery peak power correction method has been described in detail above, any details not fully described in this embodiment are referred to the relevant descriptions in the aforementioned embodiments and are not further elaborated here.

[0139] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0140] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, or of course, by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the relevant technology, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiment.

[0141] It should be understood that the terms used herein are for the purpose of describing specific example embodiments only and are not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "one", "an" and "said" as used herein may also be meant to include plural forms. The terms "comprise", "include", "contain" and "have" are inclusive and therefore specify the presence of stated features, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, steps, operations, elements, parts, and / or combinations thereof. The method steps, processes, and operations described herein are not to be construed as necessarily requiring them to be performed in the specific order described or illustrated, unless the order of execution is clearly indicated. It should also be understood that additional or alternative steps may be used.

[0142] The foregoing is merely a list of specific embodiments of the present application, intended to enable those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the broadest scope consistent with the principles and novel features of the present application.

Claims

1. A method for correcting battery peak power, characterized in that: include: Get the battery parameters corresponding to the vehicle battery; Determining a current ohmic internal resistance corresponding to the battery parameters; Obtaining, according to the battery model corresponding to the vehicle battery, an initial ohmic internal resistance and a cutoff ohmic internal resistance corresponding to the vehicle battery within a battery life interval; Determining an initial peak power value corresponding to the battery parameter, and correcting the initial peak power value using the current ohmic internal resistance, the initial ohmic internal resistance, and the cutoff ohmic internal resistance to obtain a corrected peak power value; Wherein, determining the current ohmic internal resistance corresponding to the battery parameters includes: determining the current ohmic internal resistance corresponding to the battery parameters using a pre-trained ohmic internal resistance calculation model; wherein, before training the ohmic internal resistance calculation model, calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the discharge curve corresponding to the sample discharge multiple; calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the discharge curve corresponding to the sample discharge multiple includes: obtaining a first discharge voltage, a second discharge voltage, a third discharge voltage, and a fourth discharge voltage in the discharge curve corresponding to the sample discharge multiple; wherein, in the discharge curve, the first discharge voltage is the discharge voltage corresponding to the initial discharge point; the second discharge voltage is the discharge voltage corresponding to the current change point; the third discharge voltage is the discharge voltage corresponding to the curve inflection point; and the fourth discharge voltage is the discharge voltage corresponding to the voltage stabilization point; obtaining the discharge current from the battery parameters corresponding to the sample discharge multiple; and calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the first discharge voltage, the second discharge voltage, the third discharge voltage, the fourth discharge voltage, and the discharge current.

2. The method according to claim 1, characterized in that Before training the ohmic internal resistance calculation model, the method includes: The following operations were performed at each cycle stage for the sample battery of the battery model: Under each preset initial sample state of charge value, using each preset sample discharge multiple, perform a discharge test on the sample battery to determine the discharge curve and battery parameters corresponding to each sample discharge multiple; wherein the battery parameters include at least the current cycle stage and discharge current of the sample battery; For each of the sample discharge multiples, the true ohmic internal resistance corresponding to the sample discharge multiple is calculated based on the discharge curve corresponding to the sample discharge multiple; and the battery parameters corresponding to the sample discharge multiple are determined as training samples, and the true ohmic internal resistance corresponding to the sample discharge multiple is set as the label of the training sample, so as to use the labeled training samples to train the ohmic internal resistance calculation model.

3. The method according to claim 1, characterized in that Before obtaining the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life interval according to the battery model corresponding to the vehicle battery, the method further includes: Identify a test battery that meets a preset battery state and has the battery model; wherein the types of the battery state include: an initial state and a cut-off state; The following operations were performed at each cycle stage of the test cell: Under each preset initial test state of charge value, using each preset test discharge multiple, performing a discharge test on the test battery, and determining a discharge curve corresponding to each test discharge multiple; For each of the test discharge multiples, calculating the ohmic internal resistance corresponding to the test discharge multiple according to the discharge curve corresponding to the test discharge multiple; Selecting the smallest ohmic internal resistance among the ohmic internal resistances calculated at each cycle stage of the test battery; When the battery state of the test battery is an initial state, the ohmic internal resistance with the smallest value is determined as the initial ohmic internal resistance; when the battery state of the test battery is a cut-off state, the ohmic internal resistance with the smallest value is determined as the cut-off ohmic internal resistance.

4. The method according to claim 3, characterized in that The step of identifying a test battery that meets a preset battery state and has the battery model includes: Among the test batteries of the battery model, identifying the test battery in the first cycle stage as the test battery with the battery state being the initial state; Among the test batteries of the battery model, test batteries whose discharge voltage is less than or equal to a preset cut-off voltage are identified as test batteries whose battery status is the cut-off state.

5. The method according to claim 1, wherein The determining the initial peak power value corresponding to the battery parameter includes: In the peak power mapping relationship corresponding to the current environmental parameters, query the peak power prediction value corresponding to the charge state value, discharge voltage and discharge current in the battery parameters; Get the preset peak power interpolation; The minimum value between the peak power prediction value and the peak power interpolation value is used as the peak power initial value.

6. The method according to claim 1, characterized in that The correcting the peak power by using the current ohmic internal resistance, the initial ohmic internal resistance, and the cut-off ohmic internal resistance includes: Calculating a correction coefficient according to the current ohmic internal resistance, the initial ohmic internal resistance, and the cut-off ohmic internal resistance; The product of the correction coefficient and the peak power initial value corresponding to the battery parameter is calculated, and the product is used as the peak power correction value.

7. A battery peak power correction device, characterized in that: include: A first acquisition module is used to obtain battery parameters corresponding to the vehicle battery; a determination module for determining a current ohmic internal resistance corresponding to the battery parameter; wherein determining the current ohmic internal resistance corresponding to the battery parameter comprises: determining the current ohmic internal resistance corresponding to the battery parameter using a pre-trained ohmic internal resistance calculation model; wherein, before training the ohmic internal resistance calculation model, calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on a discharge curve corresponding to the sample discharge multiple; calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the discharge curve corresponding to the sample discharge multiple comprises: obtaining a first discharge voltage, a second discharge voltage, a third discharge voltage, and a fourth discharge voltage from the discharge curve corresponding to the sample discharge multiple; wherein, in the discharge curve, the first discharge voltage is the discharge voltage corresponding to the discharge initial point; the second discharge voltage is the discharge voltage corresponding to the current change point; the third discharge voltage is the discharge voltage corresponding to the curve inflection point; and the fourth discharge voltage is the discharge voltage corresponding to the voltage stabilization point; obtaining a discharge current from the battery parameter corresponding to the sample discharge multiple; and calculating the true ohmic internal resistance corresponding to the sample discharge multiple based on the first discharge voltage, the second discharge voltage, the third discharge voltage, the fourth discharge voltage, and the discharge current; A second acquisition module is used to obtain the initial ohmic internal resistance and the cutoff ohmic internal resistance corresponding to the vehicle battery within the battery life range according to the battery model corresponding to the vehicle battery; The correction module is used to determine the peak power initial value corresponding to the battery parameter, and correct the peak power initial value using the current ohmic internal resistance, the initial ohmic internal resistance and the cut-off ohmic internal resistance to obtain a peak power correction value.

8. A battery peak power correction device, characterized in that: include: at least one communication interface; at least one bus connected to the at least one communication interface; at least one processor coupled to the at least one bus; At least one memory connected to the at least one bus, wherein the processor is configured to: execute a battery peak power correction program stored in the memory to implement the battery peak power correction method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed to implement the battery peak power correction method according to any one of claims 1 to 6.

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