Method for estimating battery state of health value, battery management system, and storage medium

Abstract

The embodiment of the application relates to the battery management technical field, in particular to a battery health state value estimation method, a battery management system and a storage medium. The embodiment of the application obtains a parameter characteristic table, determines a first candidate health value according to a reference ohmic resistance, a reference polarization resistance and a reference time constant obtained in an estimation process, and determines a reference weight according to a charging temperature, and the first candidate health value obtained by estimation and a historical health state value are weighted and fused to obtain a final state value of the battery. In this way, the advantages of equivalent model parameters reflecting the battery aging characteristics can be fully utilized, the influence degree of the current estimation result and the historical estimation result can be dynamically adjusted according to the temperature condition, the health state value jump caused by the temperature change, the equivalent model parameter fluctuation and the measurement error can be reduced, the accuracy, stability and continuity of the battery health state value estimation are improved, and a reliable basis is provided for the battery state monitoring and life management.

Description

Technical Field

[0001] This application relates to the field of battery management technology, and in particular to a method for estimating battery health status, a battery management system, and a storage medium. Background Technology

[0002] In recent years, with the widespread application of power batteries in new energy vehicles, energy storage systems, and other equipment, battery state of health (SOH) has become an important indicator for evaluating the degree of battery performance degradation and remaining service life. Accurately estimating battery state of health not only helps improve the state monitoring capabilities of battery management systems, but also provides a reliable basis for charge and discharge control, life prediction, and maintenance decisions.

[0003] In related technologies, battery state of health values ​​are typically estimated using methods such as capacity decay and internal resistance growth. However, due to the influence of ambient temperature, battery operating conditions, and measurement noise, these estimation methods have low accuracy, leading to a decrease in the accuracy of battery state of health value estimation. Summary of the Invention

[0004] One objective of this application is to provide a method for estimating battery state of health, a battery management system, and a storage medium, aiming to improve the low accuracy of battery state of health estimation in related technologies.

[0005] In a first aspect, embodiments of this application provide a method for estimating the state of health (SHS) value of a battery. The method includes: acquiring a parameter feature table, which represents the correspondence between the SHS value of the battery at a target temperature and target parameters, including the target ohmic internal resistance, target polarization internal resistance, and target time constant of the battery's equivalent model; acquiring the battery's charging temperature and charging voltage, which are the battery's temperature and voltage during an estimation step, respectively, and the estimation step including charging current and charging time; determining initial model parameters based on the charging current and charging voltage, and correcting the initial model parameters based on preset correction coefficients to obtain reference model parameters. The reference time constant is determined based on the reference model parameters, charging current, and charging voltage. The initial model parameters include the initial ohmic internal resistance and the initial polarization internal resistance, while the reference model parameters include the reference ohmic internal resistance and the reference polarization internal resistance. Based on the reference ohmic internal resistance, the reference polarization internal resistance, the reference time constant, and the parameter characteristic table, a first candidate health value is obtained. Based on the charging temperature, a reference weight is determined. Based on the reference weight, the first candidate health value and the second candidate health value are weighted and summed to obtain the final health value of the battery. The second candidate health value is the battery health state value obtained in the previous estimation. When estimating the battery health state value for the first time, the second candidate health value is the rated health value of 100%.

[0006] Secondly, embodiments of this application provide a battery management system, including a processor and a memory. The processor is communicatively connected to the memory, and the memory stores program instructions executable by the processor. When the program instructions are executed by the processor, the battery management system performs the battery health state estimation method provided in the first aspect.

[0007] Thirdly, embodiments of this application provide a computer-readable storage medium storing processor-executable program instructions, which, when executed by a processor, cause the processor to perform the battery health state estimation method provided in the first aspect.

[0008] The embodiments of this application have the following beneficial effects: Unlike related technologies, the embodiments of this application obtain a parameter feature table, determine a first candidate health value based on the reference ohmic internal resistance, reference polarization internal resistance, and reference time constant obtained during the estimation process, and determine a reference weight based on the charging temperature. The estimated first candidate health value and historical health state values ​​are then weighted and fused to obtain the final state value of the battery. This fully utilizes the advantage of equivalent model parameters reflecting battery aging characteristics, and dynamically adjusts the influence of current and historical estimation results according to temperature conditions. This effectively reduces jumps in health state values ​​caused by temperature changes, fluctuations in equivalent model parameters, and measurement errors, improving the accuracy, stability, and continuity of battery health state value estimation, thereby providing a reliable basis for battery state monitoring and lifespan management. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the related technologies or embodiments will be briefly introduced below. Obviously, the drawings described below only show some embodiments of this application and should not be considered as limiting the scope of protection. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a schematic diagram illustrating an application scenario for estimating battery health status values ​​in some embodiments of this application; Figure 2 This is a schematic diagram of the structure of a battery management system provided in some embodiments of this application; Figure 3 This is a flowchart illustrating a method for estimating battery health status values ​​provided in some embodiments of this application; Figure 4A This is a schematic diagram of the second-order RC model of the battery in some embodiments of this application; Figure 4BThese are schematic diagrams of the first-order RC model and PNGV model of the battery provided in some embodiments of this application; Figure 5A This is a schematic diagram of the complete fitted function curve obtained in some embodiments of this application; Figure 5B This is a schematic diagram of the fitting function curves obtained from some embodiments of this application. Figure 1 ; Figure 6A This is a schematic diagram of the battery static voltage during experimental steps in some embodiments of this application; Figure 6B This is a schematic diagram of battery resting voltage and battery SOC in some embodiments of this application; Figure 6C This is a schematic diagram of the battery OCV-SOC curves obtained by fitting in some embodiments of this application; Figure 6D This is a schematic diagram of the fitting function curves obtained from some embodiments of this application. Figure 2 ; Figure 6E These are polarization voltage curves corresponding to different first time constants and second time constants in some embodiments of this application; Figure 7A This is a schematic diagram of the battery voltage change curve during the estimation process provided in some embodiments of this application; Figure 7B This is a schematic diagram of the fitting error of the second polarization voltage in some embodiments of this application; Figure 8 This is a schematic diagram of the weight temperature curve corresponding to the weight calculation formula in some embodiments of this application. Detailed Implementation

[0011] To make the objectives and advantages of the embodiments of this application more readily understood, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. The detailed description of the embodiments of this application in the accompanying drawings is not intended to limit the scope of protection claimed by this application, but only represents selected embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0012] It should be noted that, unless there is a conflict, the various technical features involved in the embodiments of this application described below can be combined with each other, and all are within the protection scope of this application. Furthermore, although functional modules are divided in the device or structural schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. In addition, the terms "first," "second," "third," and other similar expressions used herein do not limit the data or execution order, but are only for illustrative purposes and to distinguish identical or similar items with substantially the same function and effect, and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features.

[0013] Unless otherwise defined, the technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. It should be understood that the term "and / or" as used in this specification includes any and all combinations of one or more of the listed items.

[0014] This application provides a method for estimating the state of health (SHS) of a battery. By acquiring a parameter characteristic table, a first candidate SHS value is determined based on the reference ohmic resistance, reference polarization resistance, and reference time constant obtained during the estimation process. Then, a weighted fusion of the estimated first candidate SHS value and historical SHS values ​​is performed based on a reference weight determined by the charging temperature to obtain the final SHS value of the battery. This method fully utilizes the advantage of equivalent model parameters reflecting battery aging characteristics, dynamically adjusts the influence of current and historical estimation results according to temperature conditions, reduces jumps in SHS values ​​caused by temperature changes, fluctuations in equivalent model parameters, and measurement errors, and improves the accuracy, stability, and continuity of battery SHS estimation, thereby providing a reliable basis for battery state monitoring and lifespan management.

[0015] Please see Figure 1 , Figure 1 The illustration shows a schematic diagram of an application scenario for estimating battery health status values ​​in some embodiments of this application.

[0016] See Figure 1 As shown, this application scenario includes a battery management system 100 and a server 200, with the battery management system 100 communicating with the server 200 via a network. Examples of networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0017] For example, the battery management system 100 can be any suitable type of device or component, such as a microcontroller, single-chip microcomputer, or FPGA chip. The server 200 includes any suitable type of server, such as a rack server, blade server, tower server, cabinet-type server, or microserver. The server 200 is used to store parameter characteristic tables. In practical applications, the server 200 transmits the parameter characteristic tables to the battery management system 100 via a network.

[0018] For example, in this embodiment of the application, the operation of estimating the battery's state of health value is performed as follows: First, a parameter feature table is obtained from the server 200 via the network. In some embodiments, the parameter feature table is stored in the local storage of the battery management system 100, and in this embodiment of the application, the parameter feature table is obtained from the local storage. The parameter feature table represents the correspondence between the battery's state of health value at a target temperature and target parameters, including the target ohmic internal resistance, target polarization internal resistance, and target time constant of the battery's equivalent model.

[0019] Then, the battery's charging temperature and charging voltage are obtained. The charging temperature and charging voltage are the battery's temperature and voltage during the estimation step, which includes the charging current and charging time.

[0020] Next, initial model parameters are determined based on the charging current and charging voltage, and then corrected using preset correction coefficients to obtain reference model parameters. Finally, a reference time constant is determined based on the reference model parameters, charging current, and charging voltage. The initial model parameters include initial ohmic internal resistance and initial polarization internal resistance, while the reference model parameters include reference ohmic internal resistance and reference polarization internal resistance.

[0021] Then, based on the charging temperature, the reference weight is determined; and based on the reference ohmic resistance, reference polarization resistance, reference time constant, and parameter characteristic table, the first candidate health value is calculated.

[0022] Finally, the previously estimated battery health status value is used as the second candidate health value. The first and second candidate health values ​​are then weighted and summed based on reference weights to obtain the final battery health value. It can be understood that when initially estimating the battery's health status, the second candidate health value is the rated health value of 100%.

[0023] By using the above methods, the advantages of equivalent model parameters in reflecting battery aging characteristics can be fully utilized. The influence of current estimation results on historical estimation results can be dynamically adjusted according to temperature conditions, reducing the jump in health status value caused by temperature changes, fluctuations in equivalent model parameters, and measurement errors, thereby improving the accuracy of battery health status value estimation.

[0024] It should be understood that Figure 1The application scenario shown is merely an illustrative representation of one instance in which the battery management system 100 is used to estimate the health status of a battery in some embodiments of this application. It does not impose any limitations on the structure, type, or number of battery management systems in any other embodiments.

[0025] To facilitate understanding of the battery health status estimation method provided in the embodiments of this application, the battery management system provided in the embodiments of this application will be described in detail first.

[0026] Please see Figure 2 , Figure 2 The schematic diagram illustrates the structure of a battery management system provided in some embodiments of this application.

[0027] See Figure 2 As shown, the battery management system 100 includes at least one processor 110 and at least one memory 120 connected in communication. Figure 2 Taking a bus system 130, a processor 110, and a memory 120 as an example, the various components of the battery management system 100 are coupled together through the bus system 130, which is used to realize the connection and communication between the various components. It is easy to understand that the bus system 130 may include, in addition to the data bus, a power bus, a control bus, and a status signal bus, etc., but for clarity and brevity, these will not be discussed further. Figure 2 All buses are labeled as Bus System 130. Understandably, Figure 2 The structures shown in the embodiments are merely illustrative and do not limit the structure of the battery management system described above. For example, the battery management system may also include... Figure 2 The structure shown has more or fewer components, or has the same as Figure 2 The diagram shows different configurations of the structure.

[0028] Specifically, processor 110 is configured to provide computational and control capabilities to support the battery management system 100 in executing corresponding business logic and functions, such as supporting the battery management system 100 in executing the battery health state estimation method provided in the embodiments of this application. Processor 110 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), or a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0029] The memory 120, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, instructions, and modules, such as the program, instructions, and modules corresponding to the battery health state estimation method in the embodiments of this application. In some embodiments, the memory 120 includes a program storage area and a data storage area. The program storage area stores the operating system and applications required for at least one function, while the data storage area stores data created according to the use of the processor 110. The processor 110 executes various functional applications and data processing of the battery management system 100 by running the non-transitory software programs, instructions, and modules stored in the memory 120, thereby implementing the battery health state estimation method provided in the embodiments of this application, or executing the steps in any possible implementation of the battery health state estimation method provided in the embodiments of this application. In some embodiments, the memory 120 may include high-speed random access memory and may also include non-transitory memory. For example, at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 120 may also include memory remotely located relative to the processor 110, and these remotely located memories can be connected to the processor 110 through a communication network. It is understood that examples of the aforementioned communication networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0030] As can be understood from the above, the battery health state estimation method provided in this application embodiment can be implemented by any suitable type of battery management system with certain computing and control capabilities, such as the battery management system 100 described above. In some feasible implementations, the battery health state estimation method provided in this application embodiment can be implemented by a processor executing program instructions stored in memory.

[0031] The following will describe in detail the method for estimating battery health status values ​​provided in the embodiments of this application, with reference to exemplary applications and implementations of the battery management system provided in the embodiments of this application.

[0032] For details, please refer to Figure 3 As shown, the battery health status value estimation method provided in this application embodiment includes steps S31 to S36 to estimate the battery health status value.

[0033] Step S31: Obtain the parameter feature table.

[0034] For example, the parameter feature table is used to represent the correspondence between the battery's health status value and the target parameters at the target temperature. The target parameters include the target ohmic internal resistance, target polarization internal resistance, and target time constant of the battery's equivalent model.

[0035] In this application, the equivalent model of the battery is a second-order RC model, which is used as an example for illustration. The second-order RC model includes the ohmic internal resistance. The following components are considered: first polarization internal resistance R1, second polarization internal resistance R2, first polarization capacitor C1, second polarization capacitor C2, and open-circuit voltage U0. First time constant. Second time constant It is understood that the embodiments of this application employ a first time constant. Second time constant The ontology is chosen as the identification parameter because practice has shown that the first time constant... Second time constant The order of magnitude remains constant across all batteries and will not change due to cell modification. However, when the first polarization capacitor C1 and the second polarization capacitor C2 are used directly as identification parameters, the order of magnitude will change due to cell modification, which is not conducive to parameter identification.

[0036] Please see Figure 4A , Figure 4A A schematic diagram of the structure of a second-order RC model 40 is shown. The second-order RC model 40 includes an ohmic internal resistance. The components include the first polarization internal resistance R1, the second polarization internal resistance R2, the first polarization capacitor C1, the second polarization capacitor C2, and the open-circuit voltage U0. Specifically, the first polarization internal resistance R1 is the electrochemical polarization internal resistance. The second polarization internal resistance R2 is the concentration polarization internal resistance. The first polarization capacitor C1 is an electrochemical polarization capacitor. The second polarization capacitor C2 is the concentration polarization capacitor. .

[0037] Understandably, the equivalent model of a battery can also be any other suitable model, for example, please refer to [link to relevant documentation]. Figure 4B As shown, the equivalent model of the battery can be a first-order RC model 41, which includes the ohmic internal resistance. The battery includes a first polarization internal resistance R1, a first polarization capacitor C1, and an open-circuit voltage U0. In some embodiments, the equivalent model of the battery can be a PNGV (Partnership for a New Generation of Vehicles) model 42, wherein the PNGV model 42 includes an equivalent capacitance. Ohmic internal resistance The first polarization internal resistance R1, the first polarization capacitor C1, and the open-circuit voltage U0.

[0038] Open circuit voltage (OCV) is a core component of the battery equivalent model. The open circuit voltage U0 of a battery refers to the voltage across its terminals when the battery is in an open-circuit state with no external load connected. In this state, no current flows inside the battery; therefore, the open circuit voltage directly reflects the electrochemical potential difference of the battery under static conditions and is unaffected by internal resistance.

[0039] The battery terminal voltage Ut is the actual output voltage of the equivalent model after considering the battery's internal resistance and load effects. It refers to the voltage between the positive and negative terminals of the battery when it is under load, i.e., under normal operating conditions. Because of the internal resistance of the battery, current flows through it, causing a voltage drop, thus making the actual terminal voltage lower than the open-circuit voltage U0. Changes in battery terminal voltage are influenced by various factors, including state of charge (SOC), temperature, and discharge rate.

[0040] It is understandable that the parameters that can be directly measured in experiments using the second-order RC model 40 include the battery current. Terminal voltage Ut, other resistor and capacitor parameters (ohmic internal resistance) The first polarization internal resistance R1, the second polarization internal resistance R2, the first polarization capacitor C1, and the second polarization capacitor C2 cannot be directly measured, so parameter identification is required.

[0041] The identification of resistance and capacitance in the battery equivalent model involves a series of experiments, and the commonly used experimental methods include the following four.

[0042] 1. Constant Current Charge-Discharge Test: The battery is charged and discharged with a constant current, and the voltage change over time is recorded. By analyzing the charge-discharge curves, the ohmic internal resistance and electrochemical polarization resistance of the battery can be estimated.

[0043] 2. Time-domain transient test: Apply a brief current pulse or a step change in current to the battery and measure the instantaneous change or step response of the battery voltage before and after the application of the pulse or step change. This method can be used to estimate the dynamic internal resistance of the battery, including RC elements with fast and slow responses, reveal the transient characteristics of the battery, and help identify the RC time constant.

[0044] 3. AC Impedance Spectrum: This method uses a small-amplitude AC signal (typically in the millivolt range) to measure the battery's impedance over a wide frequency range. It can provide impedance information of the battery at different time scales, thereby identifying the parameters of the RC circuit.

[0045] 4. Hybrid Pulse Power Characterization (HPPC) Test: Brief, high-intensity charge-discharge pulses are applied to batteries at different states of charge, and their voltage response is measured. By analyzing the voltage changes at the moment the pulse ends and after the pulse ends, the internal impedance characteristics of the battery are revealed. This combines the characteristics of time-domain transient testing with consideration of the battery's regenerative capabilities, providing a more comprehensive view of battery performance.

[0046] For example, multiple sets of batteries with different health status values ​​are obtained, and each set of batteries is tested at various temperatures, such as the HPPC (Hybrid Pulse Power Characterization) experiment, to obtain the experimental data corresponding to each set of batteries.

[0047] Based on experimental data, calibration data for each group of batteries at different temperatures were obtained through fitting, thereby identifying corresponding parameters such as ohmic internal resistance, polarization internal resistance (including the first polarization internal resistance and the second polarization internal resistance), and time constant (including the first time constant and the second time constant). The calibration data includes at least the identification parameters of the battery's equivalent model.

[0048] One HPPC pulse consists of a discharge pulse, a rest recovery pulse, and a feedback pulse. The rest voltage rebound curve after the discharge pulse is used to identify the first polarization internal resistance R1, the second polarization internal resistance R2, the first polarization capacitance C1, and the second polarization capacitance C2. Because the voltage across the battery surges instantaneously upon applying the discharge pulse, but no polarization effect occurs inside the battery at this moment, the first polarization voltage U1 and the second polarization voltage U2 remain unchanged. Therefore, the ohmic internal resistance can be calculated using the voltage change at the battery terminals caused by the instantaneous current flow. When using a parameter fitting tool for global fitting, the data from the entire pulse-rest process are fitted synchronously, and all model parameters are identified simultaneously.

[0049] For example, in this application embodiment, the identified ohmic resistance, polarization resistance and time constant are classified by temperature, and calibration data with the same temperature or located in the same temperature range are divided into the same temperature dataset.

[0050] For each temperature dataset, a correspondence is established between the health state value and the ohmic internal resistance, polarization internal resistance, and time constant, so that each health state value corresponds to a set of target ohmic internal resistance, target polarization internal resistance, and target time constant. The target ohmic internal resistance is the identified ohmic internal resistance, the target polarization internal resistance is the sum of the first polarization internal resistance and the second polarization internal resistance, and the target time constant is equal to the sum of the first time constant and the second time constant.

[0051] The parameter characteristic table is generated by summarizing the correspondence between the health status values ​​of each group of batteries at the target temperature (e.g., 25℃) and the target ohmic internal resistance, target polarization internal resistance, and target time constant.

[0052] For example, the parameter feature table is shown in Table 1 below.

[0053] Table 1:

[0054] Table 1 only schematically illustrates the correspondence between the health status values ​​(including 100%, 90%, 80%, and 70%) of each group of batteries at the target temperature of 25°C and the target ohmic internal resistance R0, target polarization internal resistance Rt, and target time constant Tt. It does not impose any limitations on the health status values, target temperature, and target parameters (including target ohmic internal resistance, target polarization internal resistance, and target time constant) in other embodiments.

[0055] In some embodiments, for health status values ​​or temperatures not covered during the test, interpolation calculations can be performed based on the target parameters corresponding to adjacent health status values ​​or the target parameters at adjacent temperatures to supplement and generate the corresponding target ohmic resistance, target polarization resistance and target time constant, thereby improving the completeness of the parameter feature table and the accuracy of subsequent health status value estimation.

[0056] Step S32: Obtain the battery's charging temperature and charging voltage.

[0057] Here, charging temperature and charging voltage refer to the battery's temperature and voltage during the estimation step, respectively. The estimation step includes charging current and charging time.

[0058] The estimation step is as follows: when the battery SOC (State of Charge) reaches the preset charge threshold (e.g., 45%) and the battery temperature is greater than the estimated temperature threshold (e.g., 0℃), let it stand for 10 minutes, and then charge the battery for the preset charging time (i.e., 4 minutes) with the preset charging current (i.e., 0.5C, where C is the charging rate).

[0059] The 10-minute resting period is to allow the battery's polarization voltage (including the first and second polarization voltages) to approach its maximum value. This reduces or avoids the adverse effects of polarization voltage on the estimation of state of health (SHS) values. Understandably, to improve the accuracy of SHS estimation, the charging current and charging time of the estimation step are the same as those used in battery testing experiments (i.e., the step current and first step time of the experimental step). Engineers can customize the charging current and charging time according to battery characteristics and actual needs; this application embodiment does not impose any limitations on this.

[0060] For example, in this application embodiment, an estimation step is performed on the battery, that is, the battery is first left to stand for 10 minutes to allow the battery's polarization voltage to approach the specified value. Next, the battery is continuously charged at a charging current of 0.5C for 4 minutes. During the battery estimation step, the battery temperature and voltage are collected in real time using a data acquisition module (including a temperature sensor, voltage sampling module, etc.) equipped with the battery to obtain the charging temperature and charging voltage. The charging voltage includes the battery voltage before and after charging. In one or more embodiments, the charging temperature is the average temperature of the battery during the battery estimation step. It can be understood that a weighted sum of multiple temperatures detected during the battery estimation step or a temperature at a specified location on the battery can also be selected as the charging temperature. It should be understood that the battery estimation step is performed to simulate HPPC test conditions, facilitating data comparison to obtain corresponding parameters, and then using these parameters to estimate the subsequent State of Health (SOH).

[0061] It should be understood that the charging voltage is a sampled value of the battery terminal voltage during the estimation step of the battery, and the charging voltage includes the voltage sampled at multiple sampling times.

[0062] In some embodiments, to reduce the impact of instantaneous measurement noise on subsequent health status value estimation, the collected temperature and voltage data can be filtered separately before obtaining the charging temperature and charging voltage. For example, moving average filtering, median filtering, or low-pass filtering can be used to process the temperature and voltage data to obtain more stable and accurate charging temperature and charging voltage.

[0063] Step S33: Determine the initial model parameters based on the charging current and charging voltage, and correct the initial model parameters based on the preset correction coefficient to obtain the reference model parameters, and determine the reference time constant based on the reference model parameters, charging current and charging voltage.

[0064] The initial model parameters include the initial ohmic internal resistance and the initial polarization internal resistance, and the reference model parameters include the reference ohmic internal resistance and the reference polarization internal resistance.

[0065] Obtain the charging current sequence and charging voltage sequence of the battery during the estimation step. The charging current sequence includes the charging current at multiple sampling times, which characterizes the current changes of the battery during the estimation step. The charging voltage sequence includes the charging voltage at multiple sampling times, which characterizes the changes in the battery's terminal voltage in response to changes in the charging current.

[0066] The charging current sequence is used as the input to the battery equivalent model, and the charging voltage sequence is used as the output. A parameter identification algorithm is employed to identify the parameters of the battery equivalent model, yielding the initial model parameters. These parameter identification algorithms include, but are not limited to: least squares method, recursive least squares method, genetic algorithm, particle swarm optimization algorithm, and extended Kalman filter algorithm.

[0067] Optionally, a parameter identification algorithm is used to fit the model parameters of the battery equivalent model based on the relationship between the change in charging current and the charging voltage response, in order to obtain the initial ohmic internal resistance and the initial polarization internal resistance. The initial ohmic internal resistance characterizes the instantaneous voltage loss characteristics caused by the ohmic effect inside the battery, while the initial polarization internal resistance characterizes the voltage response characteristics caused by the polarization effect inside the battery.

[0068] The correction coefficients include a first coefficient for correcting the initial ohmic internal resistance and a second coefficient for correcting the initial polarization internal resistance. The first and second coefficients are used to compensate for model parameter deviations caused by temperature changes, changes in battery aging, or measurement errors during the parameter identification process.

[0069] For example, in this embodiment of the application, the initial ohmic internal resistance is corrected and calculated with a first coefficient to obtain a reference ohmic internal resistance, so that the reference ohmic internal resistance can reflect the actual ohmic impedance characteristics under the current battery state. The initial polarization internal resistance is corrected and calculated with a second coefficient to obtain a reference polarization internal resistance, so that the reference polarization internal resistance can reflect the actual polarization characteristics under the current battery state.

[0070] For example, based on the reference ohmic internal resistance, the reference polarization internal resistance, and the charging current and charging voltage collected during the estimation process, the dynamic response characteristics in the battery equivalent model are analyzed to obtain a reference time constant. The reference time constant characterizes the response speed of the battery polarization process and reflects the characteristics of the polarization voltage change over time caused by changes in charging current.

[0071] The reference ohmic internal resistance, reference polarization internal resistance, and reference time constant are used as model parameters to reflect the current battery state, which are then combined with the parameter feature table to determine the first candidate health value.

[0072] In some embodiments, to improve the accuracy of parameter identification, outlier removal, filtering, and time synchronization are performed on the charging current sequence and charging voltage sequence before parameter identification. This reduces the adverse effects of measurement noise and sampling errors on the identification results of the reference ohmic resistance, reference polarization resistance, and reference time constant, thereby improving the accuracy of subsequent health status value estimation.

[0073] Step S34: Based on the reference ohmic resistance, reference polarization resistance, reference time constant, and parameter characteristic table, obtain the first candidate health value.

[0074] For example, based on the charging temperature, a parameter characteristic table is obtained with the target charging temperature as the reference temperature. For instance, if the charging temperature is 25℃, the parameter characteristic table shown in Table 1 is obtained. This parameter characteristic table includes multiple health state values ​​corresponding to the target ohmic internal resistance, target polarization internal resistance, and target time constant.

[0075] The reference ohmic resistance is compared with each target ohmic resistance in the parameter characteristic table to determine whether the reference ohmic resistance is the same as any of the target ohmic resistances. When the reference ohmic resistance is the same as one of the target ohmic resistances, the health state value corresponding to that target ohmic resistance is determined as the first undetermined health value. When the reference ohmic resistance is different from all the target ohmic resistances, the two target ohmic resistances corresponding to the two adjacent health state values ​​where the reference ohmic resistance is located are determined. The interpolation ratio is calculated based on the positional relationship between the reference ohmic resistance and the two target ohmic resistances. The interpolation ratio is then used to interpolate the two adjacent health state values ​​to obtain the first undetermined health value.

[0076] The reference polarization internal resistance is compared with the target polarization internal resistances in the parameter characteristic table to determine whether the reference polarization internal resistance is the same as any of the target polarization internal resistances. When the reference polarization internal resistance is the same as one of the target polarization internal resistances, the health state value corresponding to that target polarization internal resistance is determined as the first undetermined health value. When the reference polarization internal resistance is different from all the target polarization internal resistances, the two target polarization internal resistances corresponding to the two adjacent health state values ​​where the reference polarization internal resistance is located are determined. The interpolation ratio is calculated according to the positional relationship between the reference polarization internal resistance and the two target polarization internal resistances, and the interpolation is performed on the two adjacent health state values ​​according to the interpolation ratio to obtain the second undetermined health value.

[0077] The reference time constant is compared with each target time constant in the parameter feature table to determine whether the reference time constant is the same as any of the target time constants. When the reference time constant is the same as one of the target time constants, the health status value corresponding to that target time constant is determined as the first undetermined health value. When the reference time constant is different from all the target time constants, the two target time constants corresponding to the two adjacent health status values ​​of the reference time constant are determined. The interpolation ratio is calculated according to the positional relationship between the reference time constant and the two target time constants. The interpolation is performed on the two adjacent health status values ​​according to the interpolation ratio to obtain the third undetermined health value.

[0078] For example, the weighted fusion weight corresponding to the reference ohmic internal resistance is determined based on the first parameter deviation between the reference ohmic internal resistance and each target ohmic internal resistance in the parameter feature table; the weighted fusion weight corresponding to the reference polarization internal resistance is determined based on the second parameter deviation between the reference polarization internal resistance and each target polarization internal resistance in the parameter feature table; and the weighted fusion weight corresponding to the reference time constant is determined based on the third parameter deviation between the reference time constant and each target time constant in the parameter feature table. Based on the weighted fusion weights corresponding to the reference ohmic internal resistance, reference polarization internal resistance, and reference time constant, the first undetermined health value, the second undetermined health value, and the third undetermined health value are weighted and fused to obtain the first candidate health value.

[0079] In this process, the first parameter deviation, the second parameter deviation, and the third parameter deviation are normalized to the same parameter dimension, and the corresponding weighted fusion weight is determined by the normalized parameter deviation. This eliminates the influence of differences in parameter dimensions and numerical ranges on the weighted fusion result of health status value, and enables the reference ohmic resistance, reference polarization resistance, and reference time constant to participate in the determination of health status value, thereby improving the reliability of the first candidate health value.

[0080] Step S35: Determine the reference weight based on the charging temperature.

[0081] A temperature weighting table is pre-established, which includes multiple temperature ranges and the corresponding weight values ​​for each temperature range. Different temperature ranges may have the same or different weight values.

[0082] For example, the temperature weighting table is shown in Table 2 below.

[0083] Table 2:

[0084] It is understood that Table 2 is only a schematic representation of multiple temperature ranges and the corresponding weight values ​​for each temperature range, and it does not impose any limitations on the temperature ranges, weight values, or the correspondence between them in other embodiments.

[0085] For example, the target temperature range to which the charging temperature belongs can be determined. For instance, according to Table 2, when the charging temperature is 40℃, 40℃ is located in the temperature range [35,45), so the target temperature range is [35,45). The weight value of 0.8 corresponding to the target temperature range [35,45) is determined as the reference weight.

[0086] It is understandable that the closer the charging temperature is to the battery's optimal operating temperature, the greater the reference weight, making the current health status estimate account for a higher proportion.

[0087] Step S36: Based on the reference weights, the first candidate health value and the second candidate health value are weighted and summed to obtain the final health value of the battery.

[0088] For example, the second candidate health value is the battery health status value obtained from the previous estimation. When the battery health status value is estimated for the first time, the second candidate health value is the rated health value of 100%.

[0089] The first fusion weight corresponding to the first candidate health value is determined based on the reference weight, and the second fusion weight corresponding to the second candidate health value is determined based on the reference weight. Clearly, the sum of the first fusion weight and the second fusion weight is 1.

[0090] For example, the first candidate health value is multiplied by the first fusion weight to obtain the first weighted value. The second candidate health value is multiplied by the second fusion weight to obtain the second weighted value. The first weighted value and the second weighted value are summed to obtain the final health value of the battery. The final health value is stored as the health status value at the current moment. Thus, the final health value is the second candidate health value for the next health status value estimation.

[0091] In some embodiments, before performing a weighted summation of the first candidate health value and the second candidate health value, it is determined whether the difference between the first candidate health value and the second candidate health value exceeds a preset difference threshold. If the difference between the first candidate health value and the second candidate health value exceeds the preset difference threshold, the first fusion weight is reduced or the second fusion weight is increased before performing the weighted summation, so as to reduce the impact of abnormal estimation results on the final health value and improve the continuity and stability of health status value estimation.

[0092] This embodiment of the application obtains a parameter characteristic table, determines a first candidate health value based on the reference ohmic internal resistance, reference polarization internal resistance, and reference time constant obtained during the estimation process, and determines a reference weight based on the charging temperature. The estimated first candidate health value and historical health state values ​​are then weighted and fused to obtain the final battery state value. This approach fully utilizes the advantage of equivalent model parameters reflecting battery aging characteristics, and dynamically adjusts the influence of current and historical estimation results based on temperature conditions. This reduces jumps in health state values ​​caused by temperature changes, fluctuations in equivalent model parameters, and measurement errors, improving the accuracy, stability, and continuity of battery health state value estimation, thereby providing a reliable basis for battery state monitoring and lifespan management.

[0093] In one or more embodiments, the present application embodiments achieve the acquisition of parameter feature table through steps S311 to S314.

[0094] Step S311: Perform experimental steps on multiple groups of batteries at a set temperature to obtain experimental data for each group of batteries.

[0095] The experimental steps include a step current, a first step time, and a second step time. This application uses the HPPC experiment as an example to illustrate the experimental steps. The experimental steps are: discharge → charge the battery with a 0.5C charging current for 4 minutes → rest for 30 minutes → repeat the charging and resting steps 29 times, for a total of 30 charging and resting cycles. Here, the step current refers to a 0.5C charging current, the first step time is the charging time for each charging and resting cycle (i.e., 4 minutes), and the second step time is the resting time for each charging and resting cycle (i.e., 30 minutes).

[0096] The health status values ​​of any two sets of batteries are different. The experimental data includes the sampling experimental time, sampling experimental current, and sampling experimental voltage. Among them, the target polarization internal resistance is the sum of the first polarization internal resistance and the second polarization internal resistance, and the target time constant is the sum of the first time constant and the second time constant.

[0097] Experimental steps are performed on multiple groups of batteries at a set temperature. The current, time, voltage, etc. of each group of batteries are sampled and obtained by the data sampling module equipped with the batteries, and the corresponding experimental data of each group of batteries are obtained.

[0098] For example, the set temperatures include 0℃, 10℃, 17℃, 25℃, 40℃, and 55℃. At each temperature, experimental steps are performed on four groups (A, B, C, and D) of batteries of the same model and batch. The health status value of group A is 100%, that of group B is 90%, that of group C is 80%, and that of group D is 70%. Current, time, voltage, and other data are collected for the batteries in groups A, B, C, and D to obtain the corresponding experimental data.

[0099] In this embodiment, an improved fitting method, different from the conventional fitting method, is used. The specific fitting function is: .

[0100] in, For the second-order RC model function of the battery, These are the preset initial fitting conditions. For the sampling experiment time, To sample the experimental current, The pre-fitted battery open-circuit voltage, The ohmic internal resistance of the battery is pre-fitted. The sampling voltage is used in the experiment. , These are the first polarization voltage and the second polarization voltage, respectively. , It is the voltage value output after the fitting function is run. and The initial values ​​are all . This indicates a data sampling count point. For example, one data sampling corresponds to one charge and rest cycle. The complete experimental procedure performed in this embodiment includes 30 charge and rest cycles, thus having 30 sampling count points. .

[0101] For example, please see Figure 5A and Figure 5B , Figure 5A The function curves obtained by fitting experimental data based on the complete experimental steps are shown, with line 51 representing the complete fitted function curve. Figure 5B The diagram shows the function curves fitted to the experimental data of one charge and rest cycles based on the complete experimental steps. Line 52 represents the fitted function curves corresponding to one charge and rest cycles.

[0102] The method for pre-fitting the open-circuit voltage (OCV) is as follows: the battery resting voltage (i.e. the voltage at the end of battery resting) corresponding to 30 discrete sampling count points is curve-fitted with the battery SOC corresponding to 30 sampling count points to obtain the continuous battery OCV.

[0103] For example, please refer to Figure 6A During a single charge and rest cycle, the voltage at the end of the battery's rest period is taken as the rest voltage (e.g., ...). Figure 6A The voltage represented by point G is 3.305V, and line 61 is the fitting function curve corresponding to this charging and resting cycle.

[0104] For example, please refer to Figure 6B , Figure 6B The diagram shows the battery resting voltage corresponding to 30 sampling count points and the corresponding battery SOC (State of Charge). Data point 63 represents the battery resting voltage and the corresponding battery SOC. Please refer to [link to documentation]. Figure 6C , fitting Figure 6B The battery resting voltage and battery SOC shown below result in the following: Figure 6C The battery OCV-SOC curve is shown in line 64.

[0105] In conventional fitting, ocvVoltage uses a fixed value, meaning that the same OCV reference value or an OCV reference value calculated by linear interpolation is used for each charging and resting cycle. Using the same OCV reference value or an OCV reference value calculated by linear interpolation does not match the OCV in the actual smooth and continuous OCV-SOC curve, leading to poor fitting performance of the fitting function. In the embodiments of this application, when fitting the open-circuit voltage in advance, the fixed value used in conventional fitting is not used. Instead, based on the real-time SOC of the battery, the corresponding OCV reference value of the battery at each sampling time is obtained by querying, utilizing the smooth and continuous battery OCV to improve the fitting performance of the fitting function.

[0106] One method for pre-fitting the ohmic internal resistance is to calculate the ohmic internal resistance based on the battery voltage change caused by the current step change. Battery voltage change (or step voltage difference) refers to the voltage difference of the battery over a short period of time or a moment after current is applied. The calculation formula is: , Indicates the voltage difference across different levels. This is the charging current.

[0107] For example, please refer to Figure 6D During a single charge and rest cycle, the voltage difference between the applied current and the battery is obtained (e.g., the voltage difference between the applied current and ... Figure 6D The step voltage difference (dV) shown is represented by line 65, which is a partial curve in the fitting function curve corresponding to this charging and resting cycle.

[0108] For example, fitting the ohmic internal resistance of the battery The process is similar to fitting the battery open-circuit voltage, also obtaining the ohmic internal resistance corresponding to 30 discrete sampling points. Based on the ohmic internal resistance corresponding to the 30 sampling counting points The continuous ohmic resistance was obtained by fitting, which will not be elaborated here.

[0109] Step S312: For the candidate temperature, based on the experimental data corresponding to each group of batteries at the candidate temperature, fit the table of undetermined parameters corresponding to each group of batteries at the candidate temperature.

[0110] In this embodiment, the undetermined parameter table is used to represent the correspondence between candidate parameters and the range of state of charge values ​​at candidate temperatures. The candidate temperature is any one of a plurality of set temperatures, and the candidate parameter is any one of the target ohmic internal resistance, the first polarization internal resistance, the second polarization internal resistance, the first time constant, and the second time constant.

[0111] For example, for a candidate temperature, the experimental data corresponding to each group of batteries at the candidate temperature are fitted using a fitting function to obtain the parameter fitting results. The parameter fitting results include the specific values ​​of each candidate parameter at the candidate temperature in multiple (e.g., 30) different SOC ranges. In this embodiment of the application, all candidate parameters obtained by fitting after performing HPPC experiments on each group of batteries at the candidate temperature are formed into a table of undetermined parameters.

[0112] For example, the values ​​of the first polarization resistance R1 corresponding to a battery with a health status of 100% in the undetermined parameter table are shown in Table 3 below. Table 3 schematically shows the values ​​of the first polarization resistance R1 at 25°C in 30 different SOC ranges. The unit of the first polarization resistance R1 is... .

[0113] Table 3:

[0114] It is understood that Table 3 only schematically shows the specific values ​​of the first polarization internal resistance R1 at 25°C in 30 different SOC intervals, and does not impose any limitations on the division of SOC intervals, the values ​​of candidate parameters, or any other situations in other embodiments.

[0115] Step S313: Obtain the fusion parameter table based on the undetermined parameter table corresponding to each group of cells at the candidate temperature.

[0116] The fusion parameter table is used to represent the correspondence between the health status value of each group of batteries and the candidate parameters at the candidate temperature.

[0117] For example, in this embodiment of the application, the average value of the candidate parameter within a preset charge range is selected as the standard value of the candidate parameter, and the standard values ​​of each candidate parameter are filled into the corresponding positions in the pre-constructed first initial parameter table to obtain the fusion parameter table.

[0118] For example, in some embodiments, the preset charge range is 40% to 50% (including three sub-ranges [40%, 43.3%), [43.3%, 46.6%), and [46.6%, 50%)). The average value of the candidate parameter within the 40% to 50% range is used as the standard value. For example, for the first polarization resistance R1, according to Table 3, the average value of the first polarization resistance R1 within the 40% to 50% range is... It should be understood that the 40% to 50% range is used because the battery's OCV changes slowly within this SOC range, and the values ​​of each candidate parameter are relatively stable within this SOC range.

[0119] In some embodiments, the present application embodiments obtain a fusion parameter table based on the undetermined parameter table corresponding to each group of batteries at the candidate temperature through steps S3131 to S3133.

[0120] Step S3131: Calculate the mean value of the candidate parameters corresponding to the target charge interval in the undetermined parameter table to obtain the standard value.

[0121] The target charge range includes a first preset charge range, a second preset charge range, and a third preset charge range.

[0122] For example, according to Table 3, the first preset charge range is [40%, 43.3%), the second preset charge range is [43.3%, 46.6%), and the third preset charge range is [46.6%, 50%).

[0123] In this embodiment, for the first polarization internal resistance R1, the values ​​of the first polarization internal resistance R1 in the charged range [43.3%, 46.6%), the charged range [43.3%, 46.6%), and the charged range [46.6%, 50%) are 1.62, 1.71, and 1.78, respectively. The average value of the first polarization internal resistance R1 is calculated, and the standard value is obtained. .

[0124] Step S3132: Construct the first initial parameter table from the candidate temperatures, the health status values ​​of each group of batteries, and the candidate parameters.

[0125] Step S3133: Fill the candidate parameters in the first initial parameter table with standard values ​​to obtain the fusion parameter table.

[0126] For example, the first initial parameter table is shown in Table 4 below.

[0127] Table 4:

[0128] For example, the candidate parameters of the battery under different health states (including target ohmic internal resistance, first polarization internal resistance, second polarization internal resistance, first time constant and second time constant) in the first initial parameter table are filled with the corresponding standard values ​​to obtain the fusion parameter table.

[0129] For example, the fusion parameter table obtained after filling in the standard values ​​is shown in Table 5 below.

[0130] Table 5:

[0131] It is understood that Table 5 only shows the correspondence between the health status values ​​(including 100%, 90%, 80% and 70%) of each group of batteries at the target temperature of 25°C and the target ohmic internal resistance R0, the first polarization internal resistance R1, the second polarization internal resistance R2, the first time constant T1 and the second time constant T2, and does not impose any limitations on the health status values, temperature and candidate parameters in other embodiments.

[0132] Step S314: Based on the fusion parameter table, merge the first polarization internal resistance and the second polarization internal resistance into the target polarization internal resistance, and merge the first time constant and the second time constant into the target time constant to obtain the parameter characteristic table.

[0133] For example, merging the first polarization internal resistance and the second polarization internal resistance into the target polarization internal resistance means determining the sum of the first polarization internal resistance and the second polarization internal resistance as the target polarization internal resistance, and merging the first time constant and the second time constant into the target time constant means determining the sum of the first time constant and the second time constant as the target time constant, and finally obtaining the parameter characteristic table.

[0134] It should be understood that, due to the large variability of the first time constant T1 and the second time constant T2, the variances of the fitted polarization voltage curves are not significantly different after adjustments within a certain range. For example, at room temperature (25°C), experimental data were obtained by charging the battery for 4 minutes with a charging current of 0.5C. The polarization voltage curve was then fitted based on the experimental data within the charge range of 43.3%-46.6% (where, , The polarization voltage curve is similar to... , The polarization voltage curves obtained by time-fitting are not significantly different. For example, please refer to... Figure 6E , Figure 6E Schematic illustration , as well as , The polarization voltage curves at different times show that the fitting results for T1 and T2 are very close within a certain range, and the fitting results are very close to the actual voltage. The sum of T1 and T2 is also very close, which can reliably fit the voltage curve. Therefore, in this embodiment, the sum of the first time constant and the second time constant is determined as the target time constant. ,Will As a parameter affected by the State of Health (SOH) value, it reduces the difficulty of online identification.

[0135] Similarly, to reduce the difficulty of online identification, this application embodiment determines the sum of the first polarization internal resistance and the second polarization internal resistance as the target polarization internal resistance, that is... ,Will As a parameter affected by health status values.

[0136] In some embodiments, the present application embodiments achieve, through steps S3141 to S3142, a parameter feature table is obtained by merging the first polarization internal resistance and the second polarization internal resistance into a target polarization internal resistance and merging the first time constant and the second time constant into a target time constant based on the fusion parameter table.

[0137] Step S3141: Construct a second initial parameter table using the candidate temperature, the health status value of each battery group, the target ohmic internal resistance, the target polarization internal resistance, and the target time constant.

[0138] Step S3142: Determine the target ohmic internal resistance in the second initial parameter table as the target ohmic internal resistance in the fusion parameter table, and determine the target polarization internal resistance in the second initial parameter table as the sum of the first polarization internal resistance and the second polarization internal resistance, and determine the target time constant in the second initial parameter table as the sum of the first time constant and the second time constant, to obtain the parameter characteristic table.

[0139] For example, the constructed second initial parameter table is shown in Table 6 below.

[0140] Table 6:

[0141] For example, in this embodiment, the target parameters (including target ohmic internal resistance, target polarization internal resistance, and target time constant) of the battery under different health state values ​​in the second initial parameter table are filled with the corresponding values. That is, the target ohmic internal resistance in the fusion parameter table is determined to be the target ohmic internal resistance in the second initial parameter table, the sum of the first polarization internal resistance and the second polarization internal resistance is determined to be the target polarization internal resistance in the second initial parameter table, and the sum of the first time constant and the second time constant is determined to be the target time constant in the second initial parameter table, thus obtaining a parameter feature table. For example, in some embodiments, the filled parameter feature table is as shown in Table 1 above.

[0142] In some embodiments, the present application implements steps S331 to S335 to determine the initial model parameters based on the charging current and charging voltage, correct the initial model parameters based on a preset correction coefficient to obtain reference model parameters, and determine the reference time constant based on the reference model parameters, charging current and charging voltage.

[0143] Step S331: Obtain the correction coefficient.

[0144] The correction factors include a first factor and a second factor. The first factor is used to correct the obtained initial ohmic resistance to obtain the corrected initial ohmic resistance (i.e., the reference ohmic resistance). The second factor is used to correct the obtained initial polarization resistance to obtain the corrected initial polarization resistance (i.e., the reference polarization resistance).

[0145] In some embodiments, a calibration process is performed on the battery to obtain calibration experimental data, and a correction coefficient is obtained based on the calibration experimental data. The correction coefficient is stored in the local storage of the battery management system. In this embodiment, the correction coefficient is obtained from the local storage.

[0146] In some embodiments, the correction coefficient is obtained through steps S3311 to S3315.

[0147] Step S3311: Obtain the battery's calibration temperature and calibration voltage.

[0148] Among them, calibration temperature and calibration voltage are the battery temperature and voltage during the calibration process, respectively. The calibration process includes calibration current and calibration time.

[0149] For example, when the battery leaves the factory, the embodiments of this application perform a calibration process on the battery and calculate a correction coefficient based on the experimental data of the battery during the calibration process (including calibration temperature, calibration voltage, calibration current, etc.).

[0150] The calibration step is the same as the estimation step, namely: when the battery SOC (State of Charge) reaches the preset charge threshold (e.g., 45%) and the battery temperature is greater than the estimated temperature threshold (e.g., 0℃), let it stand for 10 minutes, and then charge the battery with the preset calibration current (i.e., 0.5C, where C is the charging rate) for the preset calibration time (i.e., 4 minutes).

[0151] For example, in this embodiment of the application, a calibration step is performed on the battery, that is, the battery is first left to stand for 10 minutes to bring the battery's polarization voltage close to the specified value. Next, the battery is continuously charged at a charging current of 0.5C for 4 minutes. During the battery calibration process, the battery temperature and voltage are collected in real time using a data acquisition module (including a temperature sensor, a voltage sampling module, etc.) equipped on the battery to obtain the calibration temperature and calibration voltage. The calibration voltage includes the battery voltage before and after charging. In one or more embodiments, the calibration temperature is the average temperature of the battery during the calibration process. It is understood that a weighted sum of multiple temperatures detected during the battery calibration process or a temperature at a specified location on the battery can also be selected as the calibration temperature.

[0152] It should be understood that the calibration voltage is the sampled value of the battery terminal voltage during the calibration process, and the calibration voltage includes the voltage sampled at multiple sampling times.

[0153] Step S3312: Based on the calibration current and calibration voltage, obtain the calibration ohmic internal resistance and the calibration polarization internal resistance.

[0154] Obtain the calibration current sequence and calibration voltage sequence corresponding to the battery during the calibration process. The calibration current sequence includes the calibration current corresponding to multiple sampling times, and the calibration voltage sequence includes the calibration voltage corresponding to multiple sampling times.

[0155] The calibration current sequence is used as the input to the battery equivalent model, and the calibration voltage sequence is used as the output of the battery equivalent model. The parameter identification algorithm is used to identify the parameters of the battery equivalent model, and the parameter identification results of the battery equivalent model are obtained.

[0156] The ohmic internal resistance is extracted from the parameter identification results and determined to be the calibration ohmic internal resistance. The first polarization internal resistance and the second polarization internal resistance are extracted from the parameter identification results, and the sum of the first polarization internal resistance and the second polarization internal resistance is determined as the calibration polarization internal resistance.

[0157] Step S3313: Determine the target parameter corresponding to the rated health value in the parameter characteristic table where the target temperature is the calibration temperature as the reference parameter.

[0158] The reference parameters include the reference ohmic internal resistance and the reference polarization internal resistance, with a rated health value of 100%.

[0159] For example, in some embodiments, the calibration temperature is 25°C, and a parameter characteristic table (denoted as the calibration characteristic table) with a target temperature of 25°C is obtained as shown in Table 1. The target parameter in the calibration characteristic table corresponding to the rated health value of 100% is determined as the reference parameter, i.e., the reference ohmic internal resistance. The value is the target ohmic internal resistance corresponding to the rated health value of 100% in the calibration characteristic table, i.e. Reference polarization internal resistance The value is the target polarization internal resistance corresponding to the rated health value of 100% in the calibration characteristic table, that is: .

[0160] Step S3314: Determine the ratio of the reference ohmic internal resistance to the calibrated ohmic internal resistance as the first coefficient.

[0161] Step S3315: Determine the ratio of the reference polarization internal resistance to the calibrated polarization internal resistance as the second coefficient.

[0162] For example, in this application embodiment, the ratio of the reference ohmic internal resistance to the calibrated ohmic internal resistance is calculated to obtain a first coefficient, namely: , As the first coefficient, As the reference ohmic internal resistance, To calibrate the internal resistance of the ohm.

[0163] For example, in this application embodiment, the ratio of the reference polarization internal resistance to the calibrated polarization internal resistance is calculated to obtain the second coefficient, namely: ,in As the second coefficient, As the reference polarization internal resistance, To calibrate the polarization internal resistance.

[0164] For example, the actual data of the battery during the calibration process is shown in Table 7 below.

[0165] Table 7:

[0166] According to Table 7, taking the target ohmic internal resistance R0 as an example, the calibrated ohmic internal resistance R0S identified by performing the calibration step is: That is, the difference between the battery voltage after 2 seconds of charging and the battery voltage at the start of charging is defined as the voltage difference (i.e., The ratio of the voltage difference to the charging current is determined as the calibrated ohmic internal resistance R0S, i.e. The reference ohmic internal resistance R0T is obtained by querying the calibration characteristic table. (That is, the target ohmic internal resistance value corresponding to 100% of the rated health value), i.e.: The first coefficient is calculated. .

[0167] It is understandable that the correction factor may be different for batteries in the same batch, and each battery needs to undergo factory calibration (i.e., perform the calibration steps mentioned above) to obtain the correction factor.

[0168] Understandably, the purpose of calibrating and obtaining correction coefficients and using these correction coefficients to correct the ohmic and polarization resistance of the battery during actual operation is to ensure that even if there are certain errors in the online parameter estimation of the ohmic and polarization resistance, the estimation method remains consistent each time (i.e., using correction coefficients to correct the ohmic and polarization resistance), and the relative change pattern of the parameters will not change due to estimation errors. In this way, the reliability of the relative change amplitude of the parameters is improved.

[0169] Step S332: Based on the charging current and charging voltage, obtain the initial ohmic internal resistance and the initial polarization internal resistance.

[0170] The charging voltage is a sampled value of the battery terminal voltage during the battery estimation step. The charging voltage includes voltages sampled at multiple sampling times, including multiple times before and during battery charging. The charging current is a sampled value of the battery current during the battery estimation step.

[0171] For example, in embodiments of this application, the initial ohmic internal resistance and the initial polarization internal resistance are calculated based on the charging current and charging voltage during the estimation step of the battery.

[0172] In some embodiments, the present application embodiments achieve the initial ohmic internal resistance and initial polarization internal resistance based on the charging current and charging voltage through steps S3321 to S3322.

[0173] Step S3321: Determine the ratio of the first voltage difference to the charging current as the initial ohmic internal resistance.

[0174] Step S3322: Determine the ratio of the second voltage difference to the charging current as the initial polarization internal resistance.

[0175] The charging voltage includes a first reference voltage, a second reference voltage, and a third reference voltage. The first reference voltage is the battery voltage before charging. The second reference voltage is the battery voltage after charging for a first preset time. The third reference voltage is the battery voltage after charging for a second preset time, where the second preset time is longer than the first preset time. Engineers can customize the first and second preset times according to actual needs, for example, the first preset time is 2 seconds and the second preset time is 4 minutes. This application embodiment does not impose any limitations on this.

[0176] For example, see Figure 7A As shown, Figure 7A The voltage change curve of the battery during the estimation step is shown, where the first reference voltage is... The second reference voltage is The third reference voltage is .

[0177] In this embodiment, the first voltage difference is the difference between the second reference voltage and the first reference voltage. The second voltage difference is the difference between the third reference voltage and the second reference voltage.

[0178] For example, in this embodiment, the difference between the second reference voltage and the first reference voltage is calculated to obtain the first voltage difference. The ratio of the first voltage difference to the charging current is then calculated to obtain the initial ohmic internal resistance, i.e.: ,in, The initial ohmic internal resistance, The first reference voltage, This is the second reference voltage. This is the charging current.

[0179] For example, in this embodiment, the difference between the third reference voltage and the second reference voltage is calculated to obtain the second voltage difference. The ratio of the second voltage difference to the charging current is then calculated to obtain the initial polarization resistance, i.e.: , The initial polarization internal resistance, This is the second reference voltage. This is the third reference voltage.

[0180] Step S333: Correct the initial ohmic internal resistance based on the first coefficient to obtain the reference ohmic internal resistance.

[0181] Step S334: Correct the initial polarization internal resistance based on the second coefficient to obtain the reference polarization internal resistance.

[0182] For example, in this embodiment of the application, the initial ohmic internal resistance is multiplied by a first coefficient to determine the reference ohmic internal resistance, that is: , For reference ohmic internal resistance, As the first coefficient, Let be the initial ohmic internal resistance.

[0183] For example, in this embodiment of the application, the initial polarization resistance is multiplied by a second coefficient to determine the reference polarization resistance, that is: ,in, For reference polarization internal resistance, As the second coefficient, This represents the initial polarization internal resistance.

[0184] Step S335: Obtain the reference time constant based on the reference ohmic internal resistance, reference polarization internal resistance, charging current, and charging voltage.

[0185] The charging voltage also includes a fourth reference voltage, a fifth reference voltage, and a sixth reference voltage. The fourth reference voltage is the battery voltage after charging for a third preset duration. The fifth reference voltage is the battery voltage after charging for a fourth preset duration. The sixth reference voltage is the battery voltage after charging for a fifth preset duration. The third preset duration is longer than the first preset duration, the fourth preset duration is longer than the third preset duration but shorter than the fifth preset duration, and the fifth preset duration is shorter than the second preset duration, which is equal to the first preset duration. Third preset duration Fourth preset duration Fifth preset duration The second preset duration. Engineers can customize the third, fourth, and fifth preset durations according to actual needs. For example, the third preset duration is 25 seconds, the fourth preset duration is 50 seconds, and the fifth preset duration is 100 seconds. This embodiment does not impose any limitations on this.

[0186] For example, see Figure 7A As shown, Figure 7A The diagram shows the battery voltage change curve during the estimation step. The first preset duration is 2 seconds, the second preset duration is 4 minutes, the third preset duration is 25 seconds, the fourth preset duration is 50 seconds, and the fifth preset duration is 100 seconds. The first reference voltage is... The second reference voltage is The third reference voltage is The fourth reference voltage is The fifth reference voltage is The sixth reference voltage is .

[0187] For example, in this application embodiment, the reference time constant is calculated based on the charging current and charging voltage during the estimated step of the battery operation, combined with the corrected reference ohmic internal resistance and reference polarization internal resistance.

[0188] In some embodiments, the present application embodiments achieve, through steps S3351 to S3357, obtaining a reference time constant based on a reference ohmic internal resistance, a reference polarization internal resistance, a charging current, and a charging voltage.

[0189] Step S3351: Obtain the reference parameter table.

[0190] Step S3352: Based on the first polarization internal resistance and the second polarization internal resistance in the reference parameter table, divide the reference polarization internal resistance into the first reference internal resistance and the second reference internal resistance.

[0191] The reference parameter table is a fusion parameter table corresponding to the charging temperature. The reference parameter table is used to represent the correspondence between the health status value of each group of batteries and the candidate parameters at the charging temperature. The candidate parameters are any one of the target ohmic internal resistance, the first polarization internal resistance, the second polarization internal resistance, the first time constant, and the second time constant.

[0192] The target polarization internal resistance is the sum of the first polarization internal resistance and the second polarization internal resistance, and the target time constant is the sum of the first time constant and the second time constant.

[0193] For example, when the charging temperature is 25°C, the fusion parameter table shown in Table 5 above is used as a reference parameter table. Based on the ratio of the first polarization internal resistance to the second polarization internal resistance in the reference parameter table, the reference polarization internal resistance is divided into a first reference internal resistance and a second reference internal resistance, such as the reference polarization internal resistance... First polarization internal resistance Second polarization internal resistance According to the first polarization internal resistance Second polarization internal resistance After dividing the reference polarization internal resistance according to the ratio, the first reference internal resistance is obtained. Second reference internal resistance .

[0194] Understandably, in the example above, the first polarization internal resistance Second polarization internal resistance The sum is exactly equal to the reference polarization internal resistance. Therefore, based on the first polarization internal resistance With the second polarization internal resistance The proportional division references the polarization internal resistance Then, the first reference internal resistance With the first polarization internal resistance Equal, second reference internal resistance With the second polarization internal resistance Equal. In some other embodiments, when the first polarization internal resistance is equal. With the second polarization internal resistance The sum is not equal to the reference polarization internal resistance. At that time, according to the first polarization internal resistance With the second polarization internal resistance The proportional division references the polarization internal resistance Then, the first reference internal resistance With the first polarization internal resistance They are not equal, and the second reference internal resistance With the second polarization internal resistance They are not equal.

[0195] Step S3353: Determine the difference between the fourth reference voltage and the sum of the first voltages as the first deviation voltage.

[0196] Step S3354: Determine the difference between the fifth reference voltage and the sum of the first voltages as the second deviation voltage.

[0197] Step S3355: Determine the difference between the sixth reference voltage and the sum of the first voltages as the third deviation voltage.

[0198] The first voltage sum is the sum of the first reference voltage and the ohmic voltage, where the ohmic voltage is the product of the charging current and the reference ohmic internal resistance.

[0199] Among them, the fourth reference voltage Fifth reference voltage The sixth reference voltage , is a natural constant. For ohmic voltage, The first reference voltage, , These are the first and second candidate constants, respectively.

[0200] Among them, let the first deviation voltage ,Right now: Second deviation voltage ,Right now: Third deviation voltage ,Right now: Therefore, the formula for calculating the deviation voltage is: ,in, , .

[0201] For example, the known , , , Substitute into the formula: The first deviation voltage was calculated. Similarly, the known... , , , Substitute into the formula: The second deviation voltage was calculated. The known , , , Substitute into the formula: The third deviation voltage was calculated. In this embodiment of the application, the results are calculated based on the data shown in Table 7. , , .

[0202] In the above formula, (in, , To reduce the computational difficulty and meet the requirements for rapid online estimation, calculations are performed in advance to address the inconvenience of direct calculation. and hour The value is stored in the local storage of the battery management system and can be directly retrieved and used during calculations. , hour, The values ​​are shown in Table 8 below.

[0203] Table 8:

[0204] Step S3356: Calculate the first candidate constant and the second candidate constant based on the charging current, the first reference internal resistance, the second reference internal resistance, the first deviation voltage, the second deviation voltage, and the third deviation voltage.

[0205] Step S3357: Determine the sum of the first candidate constant and the second candidate constant as the reference time constant.

[0206] For example, in iterative calculation of the time constant, let T1M = x, where x is... To reduce the number of calculations, by consulting the fusion parameter table, it is known that T1M is most likely equal to 12. Therefore, the iteration range of x is reduced to 12±5. This embodiment uses x=14 as an example to illustrate the process of one iteration calculation. When T1M=14, At that time, by referring to Table 8, we can obtain: , , .

[0207] in, , will the known , Substitute into the calculation to obtain ( hour), ( hour), ( (Time). Due to , , Therefore, by combining the formula for calculating the deviation voltage, the following can be obtained: ( hour), ( hour), ( hour).

[0208] Thus, according to , , will the known , Substitute and calculate to get , and .

[0209] According to Table 8, when hour, , , , with the above , , The closest, therefore selected ,according to , , will the known , , and Substitute and calculate to get ( hour), ( hour), ( (Time). Separately ( hour), ( hour), ( (time) and the calculations obtained above ( hour), ( hour), ( Calculate the voltage difference (at time), and sum the individual voltage differences to obtain the result. The fitting error.

[0210] Where x takes the value hour, The fitting error is shown in Table 9 below.

[0211] Table 9:

[0212] Please see Figure 7B Based on Table 9, the following diagram was drawn: Figure 7B The diagram shown illustrates the fitting error, where, when When the fitting error is minimized, the fitting result is the first candidate constant. Second candidate constant The first candidate constant With the second candidate constant The sum is determined as the reference time constant. ,Right now: .

[0213] In some implementations, embodiments of this application obtain a first candidate health value based on a reference ohmic internal resistance, a reference polarization internal resistance, a reference time constant, and a parameter characteristic table through steps S341 to S345.

[0214] Step S341: From multiple parameter feature tables, select the parameter feature table whose target temperature is the charging temperature as the charging feature table.

[0215] Step S342: Determine the health status value corresponding to the reference ohmic internal resistance in the charging characteristic table as the first health value.

[0216] Step S343: Determine the health status value corresponding to the reference polarization internal resistance in the charging characteristic table as the second health value.

[0217] Step S344: Determine the health status value corresponding to the reference time constant in the charging characteristic table as the third health value.

[0218] For example, in some embodiments, the charging temperature is 25°C. From multiple parameter feature tables, the parameter feature table with a target temperature of 25°C, as shown in Table 1, is obtained as the charging feature table. The health state value corresponding to the reference ohmic internal resistance in the charging feature table is determined as the first health value, the health state value corresponding to the reference polarization internal resistance in the charging feature table is determined as the second health value, and the health state value corresponding to the reference time constant in the charging feature table is determined as the third health value.

[0219] Specifically, when the reference ohmic internal resistance is different from all the target ohmic internal resistances in the charging characteristic table, the two target ohmic internal resistances corresponding to the two adjacent health state values ​​where the reference ohmic internal resistance is located are determined; the interpolation ratio is calculated based on the positional relationship between the reference ohmic internal resistance and the two target ohmic internal resistances, and the interpolation is performed on the two adjacent health state values ​​according to the interpolation ratio to obtain the first health value.

[0220] When the reference polarization internal resistance is different from all the target polarization internal resistances in the charging characteristic table, determine the two target polarization internal resistances corresponding to the two adjacent health state values ​​where the reference polarization internal resistance is located; calculate the interpolation ratio according to the positional relationship between the reference polarization internal resistance and the two target polarization internal resistances, and perform interpolation calculation on the two adjacent health state values ​​according to the interpolation ratio to obtain the second health value.

[0221] When the reference time constant is different from all the target time constants in the charging characteristic table, determine the two target time constants corresponding to the two adjacent health state values ​​where the reference time constant is located; calculate the interpolation ratio according to the positional relationship between the reference time constant and the two target time constants, and perform interpolation calculation on the two adjacent health state values ​​according to the interpolation ratio to obtain the third health value.

[0222] Step S345: Weight and merge the first health value, the second health value, and the third health value to obtain the first candidate health value.

[0223] For example, in this embodiment of the application, the weights corresponding to the first health value, the second health value, and the third health value are calculated based on the target ohmic internal resistance, the target polarization internal resistance, and the target time constant in the charging feature table. Finally, the first health value, the second health value, and the third health value are weighted and fused according to the weights corresponding to the first health value, the second health value, and the third health value to obtain the first candidate health value.

[0224] In some implementations, the embodiments of this application achieve weighted fusion of the first health value, the second health value, and the third health value through steps S3451 to S3457 to obtain the first candidate health value.

[0225] Step S3451: Determine the ratio of the difference in ohmic internal resistance to the initial value of ohmic internal resistance as the first amplitude value.

[0226] Step S3452: Determine the ratio of the polarization internal resistance difference to the initial value of the polarization internal resistance as the second amplitude value.

[0227] Step S3453: Determine the ratio of the time constant difference to the initial value of the time constant as the third amplitude value.

[0228] In this embodiment, the ohmic resistance difference is the difference between the maximum and minimum ohmic resistance values. The maximum ohmic resistance is the maximum value among all target ohmic resistances corresponding to all health status values ​​in the charging characteristic table. The minimum ohmic resistance is the minimum value among all target ohmic resistances corresponding to all health status values ​​in the charging characteristic table. The initial ohmic resistance is the target ohmic resistance corresponding to the rated health value in the charging characteristic table.

[0229] In this embodiment, the polarization resistance difference is the difference between the maximum and minimum polarization resistance values. The maximum polarization resistance is the maximum value among all target polarization resistances corresponding to all health states in the charging characteristic table. The minimum polarization resistance is the minimum value among all target polarization resistances corresponding to all health states in the charging characteristic table. The initial polarization resistance is the target polarization resistance corresponding to the rated health value in the charging characteristic table.

[0230] In this embodiment, the time constant difference is the difference between the maximum and minimum time constant values. The maximum time constant is the maximum value among the target time constants corresponding to all health status values ​​in the charging characteristic table. The minimum time constant is the minimum value among the target time constants corresponding to all health status values ​​in the charging characteristic table. The initial time constant is the target time constant corresponding to the rated health value in the charging characteristic table.

[0231] For example, in some embodiments, the charging temperature is 25°C, and a parameter feature table with a target temperature of 25°C as shown in Table 1 is obtained as the charging feature table.

[0232] For example, according to the charging characteristics table shown in Table 1, the maximum ohmic internal resistance value for ,Right now: Minimum ohmic internal resistance value for ,Right now: Initial value of ohmic internal resistance for ,Right now: The embodiments of this application are based on the following formula: Calculate the first amplitude value ,Right now 8.

[0233] For example, according to the charging characteristics table shown in Table 1, the maximum polarization internal resistance value for ,Right now: Minimum polarization internal resistance for ,Right now: Initial value of polarization internal resistance for ,Right now: For example, embodiments of this application are based on the following formula: The second amplitude value was calculated. ,Right now .

[0234] For example, according to the charging characteristic table shown in Table 1, the maximum time constant value for ,Right now Minimum time constant value for ,Right now: Initial value of time constant for ,Right now: The embodiments of this application are based on the following formula: The third amplitude value was calculated. ,Right now .

[0235] Step S3454: Determine the ratio of the square of the first amplitude value to the sum of the squares of the amplitude values ​​as the first weight.

[0236] Step S3455: Determine the ratio of the square of the second amplitude value to the sum of the squares of the amplitude values ​​as the second weight.

[0237] Step S3456: Determine the ratio of the square of the third amplitude value to the sum of the squares of the amplitude values ​​as the third weight.

[0238] The sum of squares of the amplitude values ​​is the sum of the squares of the first amplitude value, the squares of the second amplitude value, and the squares of the third amplitude value.

[0239] For example, embodiments of this application are based on the following formula: The sum of squared amplitudes is calculated, where This is the sum of squared amplitudes. , , These are the first amplitude value, the second amplitude value, and the third amplitude value, respectively.

[0240] For example, according to the following formula: The first weight is calculated. As the first weight, The square of the first amplitude value, This is the sum of squared amplitudes.

[0241] According to the following formula: The second weight is calculated, where, As the second weight, It is the square of the second amplitude value.

[0242] According to the following formula: The third weight is calculated, where, As the third weight, It is the square of the third amplitude value.

[0243] Understandably, the weights of each parameter (i.e., reference ohmic resistance, reference polarization resistance, and reference time constant) vary with the battery state of OH. When the parameter is less affected by the battery state of OH, its weight is lower; when the parameter is more affected by the battery state of OH, its weight is higher.

[0244] Step S3457: Calculate the sum of the first intermediate value, the second intermediate value, and the third intermediate value to obtain the first candidate health value.

[0245] The first intermediate value is the product of the first weight and the first health value, the second intermediate value is the product of the second weight and the second health value, and the third intermediate value is the product of the third weight and the third health value.

[0246] For example, embodiments of this application are based on the following formula: Calculate the first candidate health value. The first candidate health value, , , These are the first health value, the second health value, and the third health value, respectively. , , These are the first weight, the second weight, and the third weight, respectively. The first median value, The second intermediate value, It is the third intermediate value.

[0247] In some implementations, the embodiments of this application determine the reference weight based on the charging temperature through steps S351 to S352.

[0248] Step S351: In response to the charging temperature being lower than the preset temperature threshold, substitute the charging temperature into the preset weight calculation formula to calculate the reference weight.

[0249] Step S352: In response to the charging temperature being greater than or equal to a preset temperature threshold, determine the standard weight value 1 as the reference weight.

[0250] It is understood that engineers can customize the preset temperature threshold based on experience data and actual needs, for example, setting the preset temperature threshold to 25°C. This application embodiment does not impose any limitations on this.

[0251] The reference weights are temperature-related weighting coefficients. At low temperatures (i.e., temperatures less than or equal to a preset temperature threshold), the lower the temperature, the more exponentially (rapidly) the model parameters change, and the greater the impact of temperature sampling errors. To reduce the influence of temperature, a weighting calculation formula is designed that satisfies the condition: the lower the temperature, the lower the coefficient.

[0252] For example, the weight calculation formula is as follows: ,in, For reference weighting, It is a natural constant. This refers to the charging temperature.

[0253] The weight calculation formula mentioned above is derived from the fitted equation: The formula for fitting the temperature-weight correspondence is obtained by using the ratio of the target ohmic resistance R0 at a preset temperature threshold to the target ohmic resistance R0 at other temperatures, for example, see [reference missing]. Figure 8 As shown, the weighted temperature curve corresponding to the final fitted weight calculation formula is shown as line 81. In the fitted equation, , and These are all parameters to be fitted. For temperature, Weights. It's understandable that the methods for calculating the fitting weights are fairly conventional, such as using nonlinear least squares fitting, which will not be elaborated upon here.

[0254] For example, the charging temperature is compared with a preset temperature threshold. When the charging temperature is lower than the preset temperature threshold, the charging temperature is substituted into the weighting calculation formula to calculate a reference weight. When the charging temperature is greater than or equal to the preset temperature threshold, the charging temperature is substituted into the weighting calculation formula, and a standard weight value of 1 is determined as the reference weight. The reference weight is directly assigned as 1, i.e.: .

[0255] In some implementations, the embodiments of this application achieve the final health value of the battery by weighted summing of the first candidate health value and the second candidate health value based on reference weights through steps S361 to S363.

[0256] Step S361: Calculate the product of the first candidate health value and the reference weight to obtain the first product value.

[0257] Step S362: Calculate the product of the second candidate health value and the weight difference to obtain the second product value.

[0258] Step S363: Calculate the sum of the first product value and the second product value to obtain the final health value.

[0259] The weight difference is the difference between the standard weight value of 1 and the reference weight.

[0260] For example, embodiments of this application are based on the following formula: The final health value of the battery is calculated. For the final health value, , These are the first candidate health value and the second candidate health value, respectively. The first product value, This is the weighted difference. This is the second product value.

[0261] In summary, this embodiment of the application obtains a parameter feature table, determines a first candidate health value based on the reference ohmic internal resistance, reference polarization internal resistance, and reference time constant obtained during the estimation process, and determines a reference weight based on the charging temperature. The estimated first candidate health value and historical health state values ​​are then weighted and fused to obtain the final battery state value. This approach fully utilizes the advantage of equivalent model parameters reflecting battery aging characteristics while dynamically adjusting the influence of current and historical estimation results based on temperature conditions. This effectively reduces jumps in health state values ​​caused by temperature changes, fluctuations in equivalent model parameters, and measurement errors, improving the accuracy, stability, and continuity of battery health state value estimation, thereby providing a reliable basis for battery state monitoring and lifespan management.

[0262] This application embodiment only requires a short charge of the battery to quickly and accurately estimate the battery's state of health value based on changes in the battery's equivalent model parameters. The calculation method is simple, the computational load is small, and it is easy to implement in engineering. It does not require fully charging or discharging the battery, saving time and improving efficiency.

[0263] The embodiments of this application are applicable to the estimation of the state of health of batteries under various environments and uses. For example, they are used to estimate the state of health of batteries used as portable energy storage, UPS (Uninterruptible Power Supply), starting power, or industrial and commercial energy storage. They have a wide range of applications and strong adaptability.

[0264] This application provides a computer-readable storage medium storing processor-executable program instructions. When executed by the processor, the program instructions cause the processor to perform the battery health state estimation method provided in this application, or to perform the steps in any possible implementation of the battery health state estimation method provided in this application.

[0265] In some embodiments, the storage medium may be a flash memory, a hard disk, an optical disk, a register, a magnetic surface memory, a removable disk, a CD-ROM, a random access memory (RAM), a read-only memory (ROM), an electrically programmable ROM, and an electrically erasable programmable ROM, or any other form of storage medium known in the art, or various devices including one or any combination of the above storage media.

[0266] In some embodiments, program instructions may take the form of programs, software, software modules, scripts, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as stand-alone programs or as modules, components, subroutines, or other units suitable for use in a computing environment.

[0267] As an example, program instructions may, but do not necessarily, correspond to files in the file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, or in a single file dedicated to the program in question, or in multiple collaborative files (such as files that store one or more modules, subroutines, or code sections).

[0268] As an example, program instructions can be deployed to execute on a computing device (including devices such as smart terminals and servers), or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network. It is understood that all or part of the steps of the methods described in the embodiments provided in this application can be implemented directly using electronic hardware or processor-executable program instructions, or a combination of both.

[0269] Those skilled in the art will understand that the embodiments provided in this application are merely illustrative. The order in which the steps in the methods of the embodiments are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The order can be adjusted, merged, and deleted according to actual needs. Modules or sub-modules, units or sub-units in the apparatus or system of the embodiments can be merged, divided, and deleted according to actual needs. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0270] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, and of course, it can also be implemented using hardware. Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. It should be understood that the storage medium can be flash memory, hard disk, optical disk, register, magnetic surface memory, removable disk, CD-ROM, random access memory (RAM), read-only memory (ROM), electrically programmable ROM, and electrically erasable programmable ROM, etc.

[0271] It should be noted that the above embodiments are for illustrating the technical concept and features of this application, and are intended to enable those skilled in the art to understand the content of this application and implement it accordingly. They should not be construed as limiting the scope of protection of this application. Those skilled in the art can understand that all or part of the processes of the above embodiments can be implemented, modified according to the technical solutions described in the embodiments of this application, or equivalent substitutions can be made to some of the technical features. It is understood that these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should be considered as equivalent changes and modifications made based on the embodiments of this application, all of which should fall within the scope of the claims of this application.

Claims

1. A method for estimating the state of health of a battery, characterized in that, The estimation method includes: Obtain a parameter feature table, wherein the parameter feature table is used to represent the correspondence between the health status value of the battery at the target temperature and the target parameters, wherein the target parameters include the target ohmic internal resistance, target polarization internal resistance and target time constant of the battery's equivalent model; The charging temperature and charging voltage of the battery are obtained, wherein the charging temperature and the charging voltage are the temperature and voltage of the battery during the estimation step, and the estimation step includes charging current and charging time. Initial model parameters are determined based on the charging current and the charging voltage, and the initial model parameters are corrected based on a preset correction coefficient to obtain reference model parameters. A reference time constant is determined based on the reference model parameters, the charging current and the charging voltage. The initial model parameters include initial ohmic internal resistance and initial polarization internal resistance, and the reference model parameters include reference ohmic internal resistance and reference polarization internal resistance. Based on the reference ohmic resistance, the reference polarization resistance, the reference time constant, and the parameter characteristic table, a first candidate health value is obtained; Based on the charging temperature, a reference weight is determined; Based on the reference weights, the first candidate health value and the second candidate health value are weighted and summed to obtain the final health value of the battery. The second candidate health value is the health status value of the battery obtained in the previous estimation. When the health status value of the battery is estimated for the first time, the second candidate health value is 100% of the rated health value.

2. The method for estimating battery health status value according to claim 1, characterized in that, The target polarization internal resistance is the sum of the first polarization internal resistance and the second polarization internal resistance; the target time constant is the sum of the first time constant and the second time constant; and the parameter feature table includes: Experimental steps are performed on multiple groups of batteries at a set temperature to obtain experimental data for each group of batteries. The experimental steps include step current, first step time and second step time. The health status values ​​of any two groups of batteries are different. The experimental data includes sampling experimental time, sampling experimental current and sampling experimental voltage. For the candidate temperature, based on the experimental data corresponding to each group of batteries at the candidate temperature, a table of undetermined parameters corresponding to each group of batteries at the candidate temperature is fitted. The table of undetermined parameters is used to represent the correspondence between the candidate parameters and the range of state of charge values ​​at the candidate temperature. The candidate temperature is any one of a plurality of set temperatures. The candidate parameter is any one of the target ohmic internal resistance, the first polarization internal resistance, the second polarization internal resistance, the first time constant, and the second time constant. Based on the undetermined parameter table corresponding to each group of batteries at the candidate temperature, a fusion parameter table is obtained. The fusion parameter table is used to represent the correspondence between the health status value of each group of batteries at the candidate temperature and the candidate parameters. Based on the fusion parameter table, the first polarization internal resistance and the second polarization internal resistance are merged into the target polarization internal resistance, and the first time constant and the second time constant are merged into the target time constant to obtain the parameter feature table.

3. The method for estimating battery health status value according to claim 2, characterized in that, The process of obtaining a fusion parameter table based on the undetermined parameter table corresponding to each group of batteries at the candidate temperature includes: Calculate the mean value of the candidate parameters corresponding to the target charge interval in the undetermined parameter table to obtain the standard value. The target charge interval includes a first preset charge interval, a second preset charge interval, and a third preset charge interval. The candidate temperatures, the health status values ​​of each battery group, and the candidate parameters are used to construct a first initial parameter table; The candidate parameters in the first initial parameter table are filled with the standard values ​​to obtain the fusion parameter table.

4. The method for estimating battery health status value according to claim 2, characterized in that, Based on the fusion parameter table, the first polarization resistance and the second polarization resistance are merged into a target polarization resistance, and the first time constant and the second time constant are merged into a target time constant, to obtain a parameter feature table, including: A second initial parameter table is constructed using the candidate temperature, the health status value of each battery group, the target ohmic internal resistance, the target polarization internal resistance, and the target time constant. The target ohmic internal resistance in the second initial parameter table is determined as the target ohmic internal resistance in the fusion parameter table, the target polarization internal resistance in the second initial parameter table is determined as the sum of the first polarization internal resistance and the second polarization internal resistance, and the target time constant in the second initial parameter table is determined as the sum of the first time constant and the second time constant, thus obtaining the parameter feature table.

5. The method for estimating battery health status value according to claim 1, characterized in that, The process of determining initial model parameters based on the charging current and the charging voltage, correcting the initial model parameters based on a preset correction coefficient to obtain reference model parameters, and determining a reference time constant based on the reference model parameters, the charging current, and the charging voltage includes: Obtain correction coefficients, wherein the correction coefficients include a first coefficient and a second coefficient; Based on the charging current and the charging voltage, the initial ohmic internal resistance and the initial polarization internal resistance are obtained. The initial ohmic resistance is corrected based on the first coefficient to obtain the reference ohmic resistance; Based on the second coefficient, the initial polarization resistance is corrected to obtain the reference polarization resistance; A reference time constant is obtained based on the reference ohmic internal resistance, the reference polarization internal resistance, the charging current, and the charging voltage.

6. The method for estimating battery health status value according to claim 5, characterized in that, The process of obtaining the correction coefficient includes: The calibration temperature and calibration voltage of the battery are obtained. The calibration temperature and calibration voltage are the temperature and voltage of the battery during the calibration process. The calibration process includes calibration current and calibration time. Based on the calibration current and the calibration voltage, the calibration ohmic internal resistance and the calibration polarization internal resistance are obtained. The target parameters corresponding to the rated health values ​​in the parameter characteristic table with the target temperature being the calibration temperature are determined as reference parameters, including reference ohmic internal resistance and reference polarization internal resistance; The ratio of the reference ohmic internal resistance to the calibrated ohmic internal resistance is determined as the first coefficient; The ratio of the reference polarization resistance to the calibrated polarization resistance is determined as the second coefficient.

7. The method for estimating battery health status value according to claim 5, characterized in that, The charging voltage includes a first reference voltage, a second reference voltage, and a third reference voltage. The step of obtaining the initial ohmic internal resistance and the initial polarization internal resistance based on the charging current and the charging voltage includes: The ratio of the first voltage difference to the charging current is determined to be the initial ohmic internal resistance, and the first voltage difference is the difference between the second reference voltage and the first reference voltage; The ratio of the second voltage difference to the charging current is determined to be the initial polarization internal resistance, and the second voltage difference is the difference between the third reference voltage and the second reference voltage; Wherein, the first reference voltage is the voltage of the battery before charging, the second reference voltage is the voltage of the battery when the battery is charged for a first preset time, and the third reference voltage is the voltage of the battery when the battery is charged for a second preset time, and the second preset time is longer than the first preset time.

8. The method for estimating battery health status value according to claim 7, characterized in that, The target polarization internal resistance is the sum of the first polarization internal resistance and the second polarization internal resistance; the target time constant is the sum of the first time constant and the second time constant; the charging voltage further includes a fourth reference voltage, a fifth reference voltage, and a sixth reference voltage; obtaining the reference time constant based on the reference ohmic internal resistance, the reference polarization internal resistance, the charging current, and the charging voltage includes: Obtain a reference parameter table, wherein the reference parameter table is a fusion parameter table corresponding to the charging temperature, and the reference parameter table is used to represent the correspondence between the health status value of each group of batteries and the candidate parameters at the charging temperature, wherein the candidate parameters are any one of the target ohmic internal resistance, the first polarization internal resistance, the second polarization internal resistance, the first time constant and the second time constant; Based on the first polarization resistance and the second polarization resistance in the reference parameter table, the reference polarization resistance is divided into a first reference resistance and a second reference resistance. The difference between the fourth reference voltage and the sum of the first voltages is determined to be the first deviation voltage, the sum of the first voltages being the sum of the first reference voltage and the ohmic voltage, and the ohmic voltage being the product of the charging current and the reference ohmic internal resistance; The difference between the fifth reference voltage and the sum of the first voltages is determined to be the second deviation voltage; The difference between the sixth reference voltage and the sum of the first voltages is determined to be the third deviation voltage; The first candidate constant and the second candidate constant are calculated based on the charging current, the first reference internal resistance, the second reference internal resistance, the first deviation voltage, the second deviation voltage, and the third deviation voltage. The sum of the first candidate constant and the second candidate constant is determined as the reference time constant; Wherein, the fourth reference voltage is the voltage of the battery when the battery is charged for a third preset time, the fifth reference voltage is the voltage of the battery when the battery is charged for a fourth preset time, the sixth reference voltage is the voltage of the battery when the battery is charged for a fifth preset time, the third preset time is longer than the first preset time, the fourth preset time is longer than the third preset time and shorter than the fifth preset time, and the fifth preset time is shorter than the second preset time.

9. The method for estimating battery health status value according to any one of claims 1 to 8, characterized in that, The process of obtaining a first candidate health value based on the reference ohmic resistance, the reference polarization resistance, the reference time constant, and the parameter characteristic table includes: Among multiple parameter feature tables, the parameter feature table with the target temperature being the charging temperature is selected as the charging feature table; The health status value corresponding to the reference ohmic internal resistance in the charging characteristic table is determined as the first health value. The health status value corresponding to the reference polarization internal resistance in the charging characteristic table is determined as the second health value; The health status value corresponding to the reference time constant in the charging characteristic table is determined as the third health value; The first health value, the second health value, and the third health value are weighted and fused to obtain the first candidate health value.

10. The method for estimating battery health status value according to claim 9, characterized in that, The step of weightedly fusing the first health value, the second health value, and the third health value to obtain the first candidate health value includes: The ratio of the difference in ohmic internal resistance to the initial value of ohmic internal resistance is determined as the first amplitude value, wherein the difference in ohmic internal resistance is the difference between the maximum ohmic internal resistance value and the minimum ohmic internal resistance value, the maximum ohmic internal resistance is the maximum value among the target ohmic internal resistances corresponding to all health status values ​​in the charging characteristic table, the minimum ohmic internal resistance is the minimum value among the target ohmic internal resistances corresponding to all health status values ​​in the charging characteristic table, and the initial value of ohmic internal resistance is the target ohmic internal resistance corresponding to the rated health value in the charging characteristic table; The ratio of the polarization resistance difference to the initial polarization resistance is determined as the second amplitude value, wherein the polarization resistance difference is the difference between the maximum polarization resistance and the minimum polarization resistance, the maximum polarization resistance is the maximum value among the target polarization resistances corresponding to all health status values ​​in the charging characteristic table, the minimum polarization resistance is the minimum value among the target polarization resistances corresponding to all health status values ​​in the charging characteristic table, and the initial polarization resistance is the target polarization resistance corresponding to the rated health value in the charging characteristic table; The ratio of the time constant difference to the initial time constant is determined as the third amplitude value, wherein the time constant difference is the difference between the maximum time constant value and the minimum time constant value, the maximum time constant is the maximum value among the target time constants corresponding to all health status values ​​in the charging feature table, the minimum time constant is the minimum value among the target time constants corresponding to all health status values ​​in the charging feature table, and the initial time constant is the target time constant corresponding to the rated health value in the charging feature table; The ratio of the square of the first amplitude value to the sum of squares of amplitude values ​​is determined as the first weight, and the sum of squares of amplitude values ​​is the sum of the squares of the first amplitude value, the squares of the second amplitude value, and the squares of the third amplitude value; The ratio of the square of the second amplitude value to the sum of the squares of the amplitude values ​​is determined as the second weight; The ratio of the square of the third amplitude value to the sum of the squares of the amplitude values ​​is determined as the third weight; The first candidate health value is obtained by summing the first intermediate value, the second intermediate value, and the third intermediate value. The first intermediate value is the product of the first weight and the first health value, the second intermediate value is the product of the second weight and the second health value, and the third intermediate value is the product of the third weight and the third health value.

11. The method for estimating battery health status value according to claim 1, characterized in that, The determination of reference weights based on the charging temperature includes: In response to the charging temperature being lower than a preset temperature threshold, the charging temperature is substituted into a preset weighting calculation formula to calculate a reference weight. In response to the charging temperature being greater than or equal to the preset temperature threshold, a standard weight value of 1 is determined as a reference weight.

12. The method for estimating battery health status value according to any one of claims 1 to 8, characterized in that, The step of weighted summing of the first candidate health value and the second candidate health value based on the reference weight to obtain the final health value of the battery includes: Calculate the product of the first candidate health value and the reference weight to obtain the first product value; Calculate the product of the second candidate health value and the weight difference to obtain the second product value, wherein the weight difference is the difference between the standard weight value 1 and the reference weight; The final health value is obtained by summing the first product value and the second product value.

13. A battery management system, characterized in that, The system includes a processor and a memory, the processor being communicatively connected to the memory, the memory storing program instructions executable by the processor, the program instructions being executed by the processor to cause the battery management system to perform the battery health state estimation method as described in any one of claims 1 to 12.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores processor-executable program instructions, which, when executed by the processor, cause the processor to perform the method for estimating the battery state of health value as described in any one of claims 1 to 12.

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