Battery health evaluation method, apparatus, vehicle, and storage medium

Abstract

This application discloses a method, apparatus, vehicle, and storage medium for evaluating battery health, and belongs to the battery technology field. The method includes obtaining target operating condition information and target cumulative charge / discharge capacity of a target battery under target operating conditions; determining a target battery health coefficient corresponding to the target operating condition information from battery health coefficients corresponding to each of a plurality of operating condition information intervals; and determining the health of a target battery based on the target cumulative charge / discharge capacity and target battery health coefficient. The target operating condition information includes at least one of battery temperature, battery charge state, and charging mode, and the battery health coefficient is used to indicate the degree of influence of different operating condition information on battery health. This application aims to improve the accuracy of battery health evaluation by obtaining battery health evaluation results in accordance with the influence of different operating conditions on battery health and cumulative charge / discharge capacity under different operating conditions, thereby further completing the battery health evaluation method.

Description

Technical Field

[0001] This application relates to the field of battery technology, and particularly to a method, apparatus, vehicle, and storage medium for evaluating the state of health of a battery.

Background Art

[0002] As one of the energy supply methods for new energy vehicles, batteries are widely used in the power field due to advantages such as low operating costs and little environmental pollution. In order to ensure the power supply performance of the battery and improve the safety of vehicle operation, usually, in order to avoid the impact of battery degradation on the user's vehicle use experience and improve the use safety of the battery, it is necessary to evaluate the state of health of the battery.

[0003] In related technologies, mainly by determining the cumulative charge-discharge capacity of the battery and determining the cumulative charge-discharge capacity as the health degree of the battery, the evaluation of the state of health of the battery is realized.

[0004] However, in the above method, the evaluation method is too idealized and the influencing factors considered are too single, so the accuracy of the evaluation result is relatively low.

Summary of the Invention

[0005] This application provides a method, apparatus, vehicle, and storage medium for evaluating the state of health of a battery, which can improve the accuracy of the evaluation result of the state of health of the battery. The above technical solution is as follows.

[0006] In one aspect, a method for evaluating the state of health of a battery is provided. The method includes: obtaining the target operating condition information of the target battery and the target cumulative charge-discharge capacity under the target operating conditions of the target battery; determining a target battery health coefficient corresponding to the target operating condition information from battery health coefficients corresponding to a plurality of operating condition information intervals; and determining the health degree of the target battery based on the target cumulative charge-discharge capacity and the target battery health coefficient. The above target operating condition information includes at least one of battery temperature, battery charge state, and charging mode, the charging mode includes a fast charging mode and a slow charging mode, the battery health coefficient is used to indicate the degree of influence of different operating condition information on the battery health state, and the health level is used to indicate the health state of the target battery.

[0007] Selectively, the above-mentioned multiple operating condition information intervals are operating condition information intervals corresponding to the target chemical system features, which are chemical system features of the target battery, and here, the operating condition information intervals corresponding to different chemical system features are different.

[0008] Selectively, the above chemical system features include at least one of the electrode material, electrolyte material, and electrode piece process parameters.

[0009] Selectively, the battery health coefficients corresponding to each of the above multiple operating condition information intervals are obtained by simulating the entire battery lifecycle. Here, the above simulation process is This involves obtaining a target temperature range, which is the temperature range that causes a decrease in battery life; a target charge state range, which is the charge state range that causes a decrease in battery life; and a target charge mode, which includes multiple charge modes. Dividing the above target temperature interval to obtain multiple sub-temperature intervals, and dividing the above target charge state interval to obtain multiple sub-charge state intervals, By combining the above-mentioned sub-temperature intervals, sub-charged state intervals, and multiple charging modes, multiple operating condition information intervals are obtained, each containing one sub-temperature interval, one sub-charged state interval, and one charging mode. This includes determining a battery health factor corresponding to each of the above-mentioned operating condition information intervals by a life simulation model, based on the above-mentioned multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the above-mentioned multiple operating condition information intervals.

[0010] Selectively determining the battery health coefficient corresponding to each of the above-mentioned operating condition information intervals by a life simulation model, based on the above-mentioned multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the above-mentioned multiple operating condition information intervals, is: For each of the above-mentioned multiple operating condition information intervals, the battery health coefficient corresponding to each of the multiple operating condition data in the above-mentioned operating condition information interval is determined by the above-mentioned life simulation model, This includes determining the battery health coefficient corresponding to the operating condition information interval based on the battery health coefficient corresponding to each of the above multiple operating condition data and the cumulative charge / discharge capacity corresponding to the above operating condition information interval, Each operating condition data indicates one temperature, one charge state, and one charging mode.

[0011] Selectively, the target temperature interval, target charge state interval, and target charging mode are temperature intervals, charge state intervals, and charging modes corresponding to target chemical system characteristics, respectively, where the target chemical system characteristics are the chemical system characteristics of the target battery, and the temperature intervals, charge state intervals, and charging modes corresponding to different chemical system characteristics are different.

[0012] In another embodiment, a device for evaluating the health status of a battery is provided. The above device is A battery information acquisition module for obtaining target operating condition information for a target battery and target cumulative charge / discharge capacity under the target operating conditions of the target battery, A battery health coefficient determination module for determining a target battery health coefficient corresponding to the target operating condition information from battery health coefficients corresponding to each of multiple operating condition information intervals, Includes a battery health determination module for determining the health of the target battery based on the target cumulative charge / discharge capacity and the target battery health coefficient, The above target operating condition information includes at least one of battery temperature, battery charge state, and charging mode, the charging mode includes a fast charging mode and a slow charging mode, the battery health coefficient is used to indicate the degree of influence of different operating condition information on the battery health state, and the health level is used to indicate the health state of the target battery.

[0013] Selectively, the above-mentioned multiple operating condition information intervals are operating condition information intervals corresponding to the target chemical system features, which are chemical system features of the target battery, and here, the operating condition information intervals corresponding to different chemical system features are different.

[0014] Selectively, the above chemical system features include at least one of the electrode material, electrolyte material, and electrode piece process parameters.

[0015] Selectively, the battery health coefficients corresponding to each of the above multiple operating condition information intervals are obtained by simulating the entire battery lifecycle. Here, the above simulation process is This involves obtaining a target temperature range, which is the temperature range that causes a decrease in battery life; a target charge state range, which is the charge state range that causes a decrease in battery life; and a target charge mode, which includes multiple charge modes. Dividing the above target temperature interval to obtain multiple sub-temperature intervals, and dividing the above target charge state interval to obtain multiple sub-charge state intervals, By combining the above-mentioned sub-temperature intervals, sub-charged state intervals, and multiple charging modes, multiple operating condition information intervals are obtained, each containing one sub-temperature interval, one sub-charged state interval, and one charging mode. This includes determining a battery health factor corresponding to each of the above-mentioned operating condition information intervals by a life simulation model, based on the above-mentioned multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the above-mentioned multiple operating condition information intervals.

[0016] Selectively determining the battery health coefficient corresponding to each of the above-mentioned operating condition information intervals by a life simulation model, based on the above-mentioned multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the above-mentioned multiple operating condition information intervals, is: For each of the above-mentioned multiple operating condition information intervals, the battery health coefficient corresponding to each of the multiple operating condition data in the above-mentioned operating condition information interval is determined by the above-mentioned life simulation model, This includes determining the battery health coefficient corresponding to the operating condition information interval based on the battery health coefficient corresponding to each of the above multiple operating condition data and the cumulative charge / discharge capacity corresponding to the above operating condition information interval, Each operating condition data indicates one temperature, one charge state, and one charging mode.

[0017] Selectively, the target temperature interval, target charge state interval, and target charging mode are temperature intervals, charge state intervals, and charging modes corresponding to target chemical system characteristics, respectively, where the target chemical system characteristics are the chemical system characteristics of the target battery, and the temperature intervals, charge state intervals, and charging modes corresponding to different chemical system characteristics are different.

[0018] In another embodiment, the present invention provides a vehicle including a memory for storing a computer program and a processor for executing the computer program stored in the memory to implement the steps of the battery health evaluation method described above.

[0019] In another embodiment, a computer-readable storage medium is provided, which stores a computer program and, when the computer program is executed by a processor, enables the implementation of the steps of the battery health evaluation method described above.

[0020] In another aspect, there is provided a computer program product including instructions that, when executed on a computer, cause the computer to perform the steps of the battery health state evaluation method described above.

[0021] The technical solution provided by the present application can bring at least the following beneficial effects.

[0022] The target operating condition information includes at least one of battery temperature, battery charge state, and charging mode. These battery temperature, battery charge state, and charging mode all affect the health state of the battery, and the degree of influence on the battery health state by different operating condition information is different. Therefore, by determining the target battery health coefficient corresponding to the target operating condition information and further determining the health degree of the target battery based on the target cumulative charge-discharge capacity and the target battery health coefficient, the evaluation of the health state of the target battery is realized. That is, when evaluating the health state of the target battery, in accordance with the influence of different operating conditions on the battery health state and the cumulative charge-discharge capacity under different operating conditions, the evaluation result of the battery health state is integrally obtained, the evaluation method of the battery health state is made more complete, and the accuracy of the evaluation of the battery health state is improved.

Brief Description of the Drawings

[0023] To more clearly illustrate the technical solution in the embodiments of the present application, the necessary drawings used in the embodiments are briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings based on these drawings without creative labor. [Figure 1] It is a schematic diagram of the execution environment provided by the embodiment of the present application. [Figure 2] It is a flowchart of the battery health state evaluation method provided by the embodiment of the present application. [Figure 3] It is a schematic structural diagram of the battery health state evaluation device provided by the embodiment of the present application. [Figure 4] It is a schematic structural diagram of the computer device provided by the embodiment of the present application. [Figure 5] This is a schematic diagram of the structure of a vehicle provided by an embodiment of the present invention. [Modes for carrying out the invention]

[0024] To further clarify the purpose, technical proposal, and advantages of the embodiments of this application, the embodiments will be described in more detail below in conjunction with the drawings.

[0025] Before providing a detailed interpretation and explanation of the battery health evaluation method provided by the embodiment of this application, we will first introduce the application scenarios and execution environments for the embodiment of this application.

[0026] The embodiments of the present invention are mainly applicable to scenarios in which the health status of a vehicle battery is evaluated. This evaluation scenario may be a closed test scenario, such as a test stand for a vehicle battery, or an open usage scenario, such as a scenario in which the health status of a battery is evaluated in a normal usage environment.

[0027] To explain, as the energy supply core of a new energy vehicle, the battery's performance directly impacts the user's perception of its use. In daily use, the battery's charging and discharging process can be understood as a process in which electrical ions (e.g., lithium ions) repeatedly move between the positive and negative electrodes. As the battery's usage time increases, the long-term circulation of electrical ions causes some electrical ions to be gradually consumed due to the degradation of the active material, and some electrical ions to be unable to freely shuttle between the positive and negative electrodes due to decreased activity. As a result, after long-term charging and discharging, the battery's available electrical capacity decreases, and degradation occurs.

[0028] Therefore, it is possible to accurately determine the battery's health status in real time and prompt the user to perform maintenance or replacement of the battery in a timely manner if the battery deteriorates. Furthermore, it is possible to correct the State of Power (SOP) related to the battery's external discharge power and the State of Charge (SOC) related to range estimation in real time according to the battery's health status, thereby improving the calculation accuracy of SOP and SOC.

[0029] From another perspective, it is possible to accurately determine the battery's health in real time, prompt users for timely maintenance or replacement of the battery, guarantee the battery's power supply efficiency, ensure the user experience, and prevent the misuse of degraded batteries, thereby improving the safety of both the battery and the vehicle.

[0030] In related technologies, the State of Health (SOH) of a battery can be determined by accumulating methods such as the battery's charge / discharge capacity or calendar life, and the SOH can be used to characterize the battery's degradation and decay status, i.e., its health. However, such methods tend to consider too few factors, and the calculation results are overly idealized. For example, the daily usage scenarios of batteries are relatively complex, and the effects of different operating conditions (e.g., different battery temperatures, different battery charge states, different battery charging modes) on the decay of battery capacity differ greatly. Therefore, the battery health status calculated using the above methods cannot accurately reflect the current health status of the battery.

[0031] Based on these considerations, the embodiment of the present invention provides a battery health evaluation method that comprehensively obtains battery health evaluation results by taking into full consideration the complex scenarios in the battery usage process, and by matching the impact of different operating conditions on battery health and the cumulative charge / discharge capacity under different operating conditions, thereby further refining the battery health evaluation method and improving the accuracy of battery health evaluation.

[0032] Referring to Figure 1, which is a schematic diagram of an execution environment shown based on an exemplary embodiment, the execution environment includes at least one battery 101, a sensor 102, and a processor 103, the sensor 102 being able to communicate with at least one battery 101 and the processor 103, respectively. The communication connection may be wired or wireless, and the embodiments of this application are not limited to these.

[0033] Selectively, the battery 101, sensor 102, and processor 103 may be installed independently or integrated within the same device (for example, integrated within the same vehicle).

[0034] Battery 101 may include multiple battery packs for supplying electrical energy to the vehicle.

[0035] Sensor 102 is used to detect operating condition information of battery 101, and for example, sensor 102 may include a temperature sensor for detecting the battery temperature of battery 101. Sensor 102 may further include a State of Charging (SOC) sensor for determining the battery charge state of battery 101. Sensor 102 may further include a voltage-current sensor for determining the voltage-current to charge battery 101, which is used for the battery's charging mode and / or for determining the battery's cumulative charge-discharge capacity. Cumulative charge-discharge capacity may be understood as the battery's cumulative charge-discharge electrical capacity (AH, ampere-hour).

[0036] In some embodiments, the sensor 102 and the battery 101 may be integrated to form a vehicle battery system, and the processor 103 acquires operating condition information of the battery 101 from the sensor 102 in the battery system.

[0037] The processor 103 acquires battery operating condition information from the sensor 102 and is used to determine a battery health coefficient corresponding to the operating condition information. For example, the processor 103 stores the correspondence between multiple operating condition information intervals and battery health coefficients, and further determines the battery health coefficient corresponding to the operating condition information based on the operating condition information of the battery 101.

[0038] For example, the processor 103 can determine the operating condition information interval to which the operating condition information belongs based on the battery operating condition information, and can also determine the battery health coefficient corresponding to the operating condition information interval as the battery health coefficient corresponding to the operating condition information.

[0039] After determining the battery health coefficient corresponding to the operating condition information, the processor 103 can determine the battery's health based on the battery health coefficient corresponding to the operating condition information and the cumulative charge / discharge capacity under the operating conditions corresponding to the operating condition information.

[0040] Selectively, the processor 103 may determine the health status of the battery 101 and then report the currently determined battery health status to the vehicle's control system in real time.

[0041] The processor 103 is the main entity that executes the battery health evaluation method provided by the embodiment of the present application. The processor 103 may be a general-purpose CPU (Central Processing Unit), an NP (Network Processor), a microprocessor, or one or more integrated circuits for realizing the method of the present application, such as an ASIC (Application-Specific Integrated Circuit), a PLD (Programmable Logic Device), or a combination thereof. The PLD may be a CPLD (Complex Programmable Logic Device), an FPGA (Field-Programmable Gate Array), a GAL (Generic Array Logic), or any combination thereof.

[0042] As those skilled in the art will understand, the processor 103 described above is merely an example, and other existing or potentially emerging processors that are applicable to the embodiments of this application should be included in the claims of the embodiments of this application and are incorporated herein by reference.

[0043] It should be noted that the application scenarios and execution environments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments and do not limit the technical solutions provided by the embodiments. As will be apparent to those skilled in the art, the technical solutions provided by the embodiments of this application are similarly applicable to similar technical problems as new application scenarios emerge and execution environments change.

[0044] Next, the battery health evaluation method provided by the embodiment of the present application will be explained in detail.

[0045] Figure 2 is a flowchart of a method for evaluating the battery health status provided by an embodiment of the present invention. The method is applied to the above-mentioned processor. Referring to Figure 2, the method includes the following steps.

[0046] Step 201: Obtain target operating condition information for the target battery and target cumulative charge / discharge capacity under the target operating conditions for the target battery. The target operating condition information includes at least one of the following: battery temperature, battery charge state, and charging mode. The charging mode includes fast charging mode and slow charging mode.

[0047] In some embodiments, the sensor may, after acquiring target operating condition information for the battery and the target cumulative charge / discharge capacity under the target operating conditions, transmit the target operating condition information and the target cumulative charge / discharge capacity to the processor. Here, the target operating condition is the operating condition indicated by the target operating condition information.

[0048] Here, the fast charging mode may refer to a charging mode in which the charging voltage, current, and / or power are equal to or greater than a preset threshold, the slow charging mode may refer to a charging mode in which the charging voltage, current, and / or power are less than a preset threshold, or the fast charging mode and slow charging mode may refer to the fast charging mode and slow charging mode of a battery in the relevant industry standard, and the embodiments of this application are not limited thereto, and the preset threshold can be determined based on experimental data, the provisions of the relevant protocol.

[0049] For example, fast charging mode refers to a charging mode with a charging power of 40 kilowatts (kW) or more, while slow charging mode refers to a charging mode with a charging power of less than 40 kW.

[0050] Step 202: From the battery health coefficients corresponding to each of the multiple operating condition information intervals, a target battery health coefficient corresponding to the target operating condition information is determined, and the battery health coefficient is used to indicate the degree of influence of different operating condition information on the battery health state.

[0051] In the embodiment of the present invention, one operating condition information interval corresponds to one battery health coefficient, and different operating condition information intervals correspond to different battery health coefficients. Based on these, the operating condition information interval to which the target operating condition information belongs can be determined from the plurality of operating condition information intervals, and the battery health coefficient corresponding to the operating condition information interval in which the target operating condition information is located can be determined as the target battery health coefficient corresponding to the target operating condition information.

[0052] In some embodiments, the multiple operating condition information intervals may be operating condition information intervals corresponding to target chemical system features, which are chemical system features of the target battery, where different operating condition information intervals correspond to different chemical system features.

[0053] What needs to be explained is that, because there may be differences in battery life and sensitivity to changes in operating conditions among batteries with different chemical system characteristics, there are also differences in the corresponding operating condition intervals for batteries with different chemical system characteristics. Taking battery temperature intervals as an example, because there are differences in sensitivity to changes in battery temperature among batteries with different chemical system characteristics, there are also differences in the battery temperature intervals corresponding to batteries with different chemical system characteristics.

[0054] For example, a battery with chemical system characteristics A is a high-temperature resistant battery developed based on actual usage needs, and its sensitivity to high temperatures is relatively weak, meaning that the battery can still maintain relatively stable operation and safety even at high temperatures. Therefore, the battery temperature range corresponding to this battery may be [-30°C, 80°C]. A battery with chemical system characteristics B is a low-temperature resistant battery developed based on actual usage needs, and its sensitivity to low temperatures is relatively weak, meaning that the battery can still maintain relatively stable operation and safety even at low temperatures. Therefore, the battery temperature range corresponding to this battery may be [-60°C, 40°C].

[0055] To make it easier to understand, after vehicle production and assembly are complete, the chemical system characteristics of the assembled battery have already been determined, and therefore the corresponding operating condition information interval for that battery has also been determined.

[0056] In some embodiments, the chemical system features may include at least one of the electrode material, electrolyte material, and electrode piece process parameters.

[0057] To explain, electrode material refers to the positive and negative electrode materials of a battery; for example, the positive electrode is a lithium alloy metal oxide and the negative electrode is a graphite material. Electrolyte material refers to the medium used in the battery, which is used to provide ions necessary for the normal operation of the battery; for example, organic solvents, potassium salts, etc. Electrode process parameters refer to the relevant process parameters in the battery electrode production process; for example, electrode electrochemical process, slurry composition, mixing process requirements, etc.

[0058] In some embodiments, the battery health coefficients corresponding to each of the multiple operating condition information intervals may be built into the processor after other electronic devices have simulated the entire battery lifecycle, or they may be obtained by the processor simulating the entire battery lifecycle. The simulation process may include the following steps (1) to (4). That is, the entire battery lifecycle can be simulated by the following steps (1) to (4) and the battery health coefficients corresponding to each of the multiple operating condition information intervals can be obtained.

[0059] (1) Obtain the target temperature range, target charge state range, and target charging mode. The target temperature range refers to the temperature range that causes a decrease in battery life, the target charge state range refers to the charge state range that causes a decrease in battery life, and the target charging mode includes multiple charging modes.

[0060] Here, the target charging mode may be understood as the charging current interval that causes battery life degradation, which refers to the loss of battery function and actual capacity due to the battery's core being sensitive to changes in temperature, state of charge (SOC), and current during the battery usage process.

[0061] In some embodiments, the target temperature interval, target charge state interval, and target charging mode are the temperature interval, charge state interval, and charging mode corresponding to the target chemical system characteristics, respectively, and the target chemical system characteristics are the chemical system characteristics of the target battery, where the temperature interval, charge state interval, and charging mode corresponding to different chemical system characteristics are different.

[0062] Since different chemical system characteristics correspond to different temperature intervals, charge state intervals, and charging modes, a correspondence table between chemical system characteristics and temperature intervals, charge state intervals, and charging modes can be constructed in advance. Furthermore, from this correspondence table, the temperature intervals, charge state intervals, and charging modes corresponding to the target chemical system characteristics can be obtained, and the obtained temperature intervals, charge state intervals, and charging modes can be determined as the target temperature intervals, target charge state intervals, and target charging modes.

[0063] For example, by simulating the entire lifecycle of batteries with different chemical system characteristics based on a vehicle battery test bench, it is possible to determine the temperature ranges, charge state ranges, and charging modes that cause battery life degradation for different chemical system characteristics, thereby obtaining a correspondence table between the battery's chemical system characteristics and the temperature ranges, charge state ranges, and charging modes.

[0064] (2) Divide the target temperature interval to obtain multiple sub-temperature intervals, divide the target charge state interval to obtain multiple sub-charge state intervals.

[0065] In some embodiments, a target temperature interval can be divided according to a temperature division policy to obtain multiple sub-temperature intervals, and a target charge state interval can be divided according to a charge state division policy to obtain multiple sub-charge state intervals.

[0066] Here, the temperature partitioning policy and the charge state partitioning policy may be the same or different. In practical applications, the temperature partitioning policy and the charge state partitioning policy can also be adjusted according to actual needs.

[0067] To make it clear, when temperature intervals and charge state intervals differ from those corresponding to different chemical system characteristics, there are also distinctions in the number and boundaries of sub-temperature intervals and sub-charge state intervals corresponding to different chemical system characteristics, and the temperature partitioning policy and charge state partitioning policy corresponding to different chemical system characteristics may be determined according to the needs, and the embodiments of this application are not limited thereto.

[0068] For example, assuming the target temperature range is [-30°C, 80°C], the sensitivity of battery A to different temperatures will differ, and furthermore, the rate of degradation of battery A's lifespan will differ at different temperatures. For example, battery A is a battery with relatively low sensitivity to high temperatures, meaning that battery A can still maintain relatively stable operating performance and safety even at high temperatures. Based on this, the target temperature range corresponding to battery A can be divided according to the differences in battery A's sensitivity to temperature, thereby obtaining three sub-temperature ranges: [-30°C, 0°C], [0°C, 25°C], and [25°C, 80°C].

[0069] (3) Combine the multiple sub-temperature intervals, the multiple sub-charge state intervals, and the multiple charging modes to obtain multiple operating condition information intervals, each containing one sub-temperature interval, one sub-charge state interval, and one charging mode.

[0070] For example, the sub-temperature intervals are [-30°C, 0°C), [0°C, 25°C], and [25°C, 80°C], the sub-charge state intervals are [0, 25%], [25%, 75%], and [75%, 100%], and the charging modes are fast charging mode and slow charging mode. By combining these three sub-temperature intervals, three sub-charge state intervals, and two charging modes, 18 operating condition information intervals are obtained, each containing one sub-temperature interval, one sub-charge state interval, and one charging mode. For example, one of these operating condition information intervals is one where the sub-temperature interval is [-30°C, 0°C], the sub-charge state interval is [25%, 75%], and the charging mode is slow charging mode.

[0071] (4) Based on the multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the multiple operating condition information intervals, a battery health factor corresponding to each of the multiple operating condition information intervals is determined by a life simulation model.

[0072] In several embodiments, the battery lifecycle can be simulated in different operating condition information intervals based on a life simulation model, and the battery health coefficient corresponding to each of these multiple operating condition information intervals can be determined based on the battery lifecycle in those intervals.

[0073] Since the principle for determining the battery health coefficient corresponding to each of the multiple operating condition information intervals is the same, we will now introduce one of these operating condition information intervals as an example.

[0074] In several embodiments, for any one of the multiple operating condition information intervals, a life simulation model determines a battery health coefficient corresponding to each of the multiple operating condition data in that interval, where each operating condition data indicates one temperature, one charge state, and one charging mode. Based on the battery health coefficients corresponding to each of the multiple operating condition data and the cumulative charge / discharge capacity corresponding to that operating condition information interval, the battery health coefficient corresponding to that operating condition information interval is determined.

[0075] As one example, the operating condition information interval includes multiple operating condition data, and the cumulative charge / discharge capacity corresponding to the operating condition information interval includes the cumulative charge / discharge capacity corresponding to each of the multiple operating condition data. In this case, the operating condition information interval is input into a life simulation model, the battery health status corresponding to each of the multiple operating condition data output from the life simulation model is obtained, and then a battery health coefficient corresponding to each operating condition data is determined based on the battery health status corresponding to each operating condition data and the cumulative charge / discharge capacity corresponding to each operating condition data. Furthermore, a battery health coefficient corresponding to the operating condition information interval is determined based on the battery health coefficients corresponding to each of the multiple operating condition data.

[0076] In some embodiments, for any one of the operating condition data within the operating condition information interval, the battery health corresponding to that operating condition data is divided by the cumulative charge / discharge capacity corresponding to that operating condition data to obtain the battery health coefficient corresponding to that operating condition data. Next, the average value of the battery health coefficients corresponding to each of the multiple operating condition data within the operating condition information interval is determined as the battery health coefficient corresponding to the operating condition information interval.

[0077] Selectively, an electronic device or processor performing the above simulation process may include multiple databases, also called cumulative ampere-hour databases, for storing cumulative ampere-hours. Different operating condition information intervals correspond to different cumulative ampere-hour databases, and each database is used to store the cumulative charge / discharge capacity (also called cumulative charge / discharge AH ​​or cumulative charge / discharge ampere-hours) corresponding to each operating condition data in each operating condition information interval. Therefore, for each operating condition information interval in multiple operating condition information intervals, the cumulative charge / discharge capacity corresponding to each operating condition data included in that operating condition information interval can be obtained from the cumulative ampere-hour database corresponding to that operating condition information interval, and the battery health coefficient corresponding to that operating condition information interval can be determined based on the cumulative charge / discharge capacity corresponding to each operating condition data.

[0078] Furthermore, considering the possibility of randomness in a single operating condition data, and in order to avoid the impact of random data on the accuracy of the battery health coefficient, multiple battery health coefficients are determined for any single operating condition information interval based on multiple operating condition data within that interval. Subsequently, a comprehensive battery health coefficient corresponding to that operating condition information interval can be obtained based on these multiple battery health coefficients. This avoids the problem of excessively large random errors due to a single operating condition data, thereby improving the accuracy of the battery health coefficient corresponding to each operating condition information interval.

[0079] In some embodiments, the life simulation model can be constructed based on the chemical system characteristics of the battery, and different life simulation models are available for different chemical system characteristics. Based on these, when determining the battery health coefficient for multiple operating condition information intervals corresponding to the target chemical system characteristics, a life simulation model corresponding to the target chemical system characteristics can be determined, and furthermore, the battery health coefficient for multiple operating condition information intervals corresponding to the target chemical system characteristics is determined by the life simulation model corresponding to the target chemical system characteristics.

[0080] As an example, an LFP (LiFePO4, lithium iron phosphate) battery is developed for the high-temperature market, and a life simulation model is constructed to match the chemical system characteristics of the battery. The battery temperature interval is divided into three sub-temperature intervals: [10°C, 25°C], [25°C, 35°C], and [35°C, 60°C]. The charged state interval is divided into three sub-charged state intervals: [5%, 30%], [30%, 80%], and [80%, 100%]. The charging mode is divided into a fast charging mode and a slow charging mode. By combining the three sub-temperature intervals, the three sub-charged state intervals, and the two charging modes, 18 operating condition information intervals are obtained. Next, based on the operating condition data within each of the 18 operating condition information intervals and the cumulative charge / discharge capacity corresponding to each operating condition data, the battery health coefficient corresponding to each of the 18 operating condition information intervals is determined by the life simulation model corresponding to the battery, and μ1 to μ18 are obtained.

[0081] It should be noted that the simulation process provided by the embodiment of this application can also be applied to scenarios where battery health coefficients are compared and analyzed under different operating conditions.

[0082] Exemplarily, a battery system S1 is developed for a low-temperature region. The chemical system characteristics of the battery system S1 take more into account the influence of a low-temperature environment such as an environment at or below 0°C on the battery life. That is, the battery system S1 is a low-temperature-resistant battery system, and a life simulation model 1 is constructed based on the chemical system characteristics of the battery system S1. Also, a battery system S2 developed for a normal-temperature environment is selected. That is, the battery system S2 is a non-low-temperature-resistant battery system, and a life simulation model 2 is constructed based on the chemical system characteristics of the battery system S2. Assuming that a certain operation condition information interval is -20°C < T < 0°C and 30% ≤ SOC ≤ 80%, the battery health factor μ1 corresponding to the said operation condition information interval of the battery system S1 is determined by the life simulation model 1. Similarly, the battery health factor μ2 corresponding to the said operation condition information interval of the battery system S2 is determined by the life simulation model 2. As can be seen from the simulation results, μ1 < μ2.

[0083] Also exemplarily, a battery system is charged in different charging modes. Here, the rapid charging mode charges with a step current of a rapid charging power map map, and the slow charging mode charges with a rated output power of 6.6 kw. A life simulation model is constructed based on the chemical system characteristics of the battery. Currently, assuming that there are two operation condition information intervals, the sub-temperature intervals included in these two operation condition information intervals are both 20°C < T < 25°C, the sub-state-of-charge intervals included in these two operation condition information intervals are both 30% ≤ SOC ≤ 80%, and the charging modes included in these two operation condition information intervals are both the rapid charging mode and the slow charging mode. The battery health factors corresponding to these two operation condition information intervals, that is, the battery health factor μslow charge corresponding to the slow charging mode and the battery health factor μrapid charge corresponding to the rapid charging mode, are determined by the said life simulation model. As can be seen from the result comparison, μslow charge < μrapid charge.

[0084] Step 203: Based on the target cumulative charge-discharge capacity and the target battery health factor, determine the health degree of the target battery, and the health degree is used to indicate the health state of the target battery.

[0085] In some embodiments, the target battery health can be obtained by multiplying the target cumulative charge / discharge capacity by the target battery health factor.

[0086] It should be explained that, in different scenarios, there may be distinctions in the determination method for determining the target battery health based on the target cumulative charge / discharge capacity and the target battery health coefficient. For example, in some other embodiments, the range of the battery health value is 0 to 100%, and the battery loss value can be determined based on the target cumulative charge / discharge capacity and the target battery health coefficient, and the difference between 1 and that battery loss value can be determined as the target battery health.

[0087] For example, if the target cumulative charge / discharge capacity is r1 and the target battery health factor is μ2, then the target battery health (SOH) = 1 - r1 * μ2.

[0088] Furthermore, while operating conditions in the battery usage process may change, it is considered that the loss of battery health continuously accumulates under different operating conditions. Therefore, in some embodiments, the cumulative charge / discharge capacity under each operating condition in the battery usage process can be determined, and the target battery health is determined based on the cumulative charge / discharge capacity under each operating condition and the battery health coefficient corresponding to each operating condition.

[0089] For example, the post-shipment usage scenarios of the target battery are q1 to q6, for a total of six operating condition information intervals. The cumulative charge / discharge capacities corresponding to each operating condition information interval are r1 to r6, and the battery health coefficients corresponding to each operating condition information interval are μ1 to μ6. For instance, if the cumulative charge / discharge capacity of the target battery in operating condition information interval q5 is r5, and the battery health coefficient corresponding to operating condition information interval q5 is μ5, then the health of the target battery (SOH) is 1 - (r1*μ1 + r2*μ2 + r3*μ3 + r4*μ4 + r5*μ5 + r6*μ6).

[0090] What needs to be explained is that, as the operating conditions of the target battery constantly change with changes in the environment in which the target battery is used (e.g., vehicle driving time, location, weather), in actual applications, it is possible to determine the battery health of the target battery at different times, thereby making it easier for users to understand the health status of the target battery in a timely manner.

[0091] The embodiments of this application provide a method for evaluating the health status of a battery. Considering that there are differences in the sensitivity of temperature, charge state, and charge mode changes to the degradation of battery life under different chemical system characteristics, in order to better match the battery health coefficient of a target battery to the sensitivity of changes in the operating conditions of the target battery, multiple operating condition information intervals of the target battery are determined based on the chemical system characteristics of the target battery, and further, the battery life cycle is simulated using a life simulation model to obtain battery health coefficients corresponding to different operating condition information intervals. As a result, the battery health coefficient can adequately consider the impact of different operating conditions on the battery health status, thereby improving the accuracy of the battery health coefficient. Furthermore, when target operating condition information of the target battery is obtained, the health of the target battery can be determined based on the target battery health coefficient corresponding to the target operating condition information and the target cumulative charge / discharge capacity under the target operating conditions of the target battery, thereby realizing the evaluation of the health status of the target battery. In other words, when evaluating the health status of a target battery, the system comprehensively considers the impact of changes in complex operating conditions during the actual battery usage process, such as changes in the battery's chemical system characteristics, battery temperature, battery charge state, and battery charge / discharge current (charging mode), on the rate of battery life degradation. Different battery health coefficients corresponding to different operating condition intervals are introduced, and the evaluation results of the battery health status are comprehensively obtained in accordance with the impact of different operating conditions on the battery health status and the cumulative charge / discharge capacity under different operating conditions, thereby improving the accuracy of the battery health status evaluation.

[0092] Figure 3 is a schematic diagram of the structure of a battery health evaluation device provided by an embodiment of the present invention. The battery health evaluation device can implement part or all of the battery health evaluation equipment using software, hardware, or a combination thereof. The battery health evaluation equipment may be a processor or computer equipment related to the execution environment shown in Figure 1. Referring to Figure 3, the device includes a battery information acquisition module 301, a battery health coefficient determination module 302, and a battery health determination module 303.

[0093] The battery information acquisition module 301 is used to acquire target operating condition information for a target battery and target cumulative charge / discharge capacity under the target operating conditions of the target battery. The target operating condition information includes at least one of battery temperature, battery charge state, and charging mode, and the charging mode includes fast charging mode and slow charging mode.

[0094] The battery health coefficient determination module 302 is used to determine a target battery health coefficient corresponding to a target operating condition information from battery health coefficients corresponding to each of multiple operating condition information intervals, and the battery health coefficient is used to indicate the degree of influence of different operating condition information on the battery health state.

[0095] The battery health determination module 303 is used to determine the health of a target battery based on the target cumulative charge / discharge capacity and the target battery health coefficient, and the health status is used to indicate the health state of the target battery.

[0096] Selectively, these multiple operating condition information intervals are operating condition information intervals corresponding to target chemical system features, which are chemical system features of the target battery, and here, operating condition information intervals corresponding to different chemical system features are different.

[0097] Selectively, the chemical system features include at least one of the electrode material, electrolyte material, and electrode piece process parameters.

[0098] Selectively, the battery health coefficients corresponding to each of the multiple operating condition information intervals are obtained by simulating the entire battery lifecycle. Here, the simulation process is To acquire the target temperature range, target charge state range, and target charging mode, Dividing the target temperature interval to obtain multiple sub-temperature intervals, and then dividing the target charge state interval to obtain multiple sub-charge state intervals, By combining the multiple sub-temperature intervals, the multiple sub-charge state intervals, and the multiple charging modes, we obtain multiple operating condition information intervals, each containing one sub-temperature interval, one sub-charge state interval, and one charging mode. This includes determining the battery health coefficient corresponding to each of the multiple operating condition information intervals by a life simulation model based on the multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the multiple operating condition information intervals, Here, the target temperature range refers to the temperature range that causes a decrease in battery life, the target charge state range refers to the charge state range that causes a decrease in battery life, and the target charging mode includes multiple charging modes.

[0099] Selectively determining the battery health coefficient corresponding to each of the multiple operating condition information intervals by a life simulation model, based on the multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the multiple operating condition information intervals, is: For each of the multiple operating condition information intervals, a battery health coefficient corresponding to each of the multiple operating condition data within that operating condition information interval is determined by a life simulation model. This includes determining the battery health coefficient corresponding to the operating condition information interval based on the battery health coefficient corresponding to each of the multiple operating condition data and the cumulative charge / discharge capacity corresponding to the operating condition information interval, Each operating condition data indicates one temperature, one charge state, and one charging mode.

[0100] Selectively, the target temperature interval, target charge state interval, and target charging mode are the temperature interval, charge state interval, and charging mode corresponding to the target chemical system characteristics, respectively, where the target chemical system characteristics are the chemical system characteristics of the target battery, and the temperature interval, charge state interval, and charging mode corresponding to different chemical system characteristics are different.

[0101] In the embodiments of this invention, considering that there are differences in the sensitivity of temperature, charge state, and charge mode changes to the degradation of battery life under different chemical system characteristics, in order to better match the battery health coefficient of the target battery to the sensitivity of changes in the operating conditions of the target battery, multiple operating condition information intervals of the target battery are determined based on the chemical system characteristics of the target battery, and further, the battery life cycle is simulated using a life simulation model to obtain battery health coefficients corresponding to different operating condition information intervals. As a result, the battery health coefficient can adequately consider the impact of different operating conditions on the battery health state, thereby improving the accuracy of the battery health coefficient. Furthermore, when target operating condition information of the target battery is obtained, the health of the target battery can be determined based on the target battery health coefficient corresponding to the target operating condition information and the target cumulative charge / discharge capacity under the target operating conditions of the target battery, thereby enabling evaluation of the health state of the target battery. In other words, when evaluating the health status of a target battery, the system comprehensively considers the impact of changes in complex operating conditions during the actual battery usage process, such as changes in the battery's chemical system characteristics, battery temperature, battery charge state, and battery charge / discharge current (charging mode), on the rate of battery life degradation. Different battery health coefficients corresponding to different operating condition intervals are introduced, and the evaluation results of the battery health status are comprehensively obtained in accordance with the impact of different operating conditions on the battery health status and the cumulative charge / discharge capacity under different operating conditions, thereby improving the accuracy of the battery health status evaluation.

[0102] It should be explained that, while the battery health evaluation device provided in the above embodiment is described using only the division of each functional module as an example when evaluating the battery health, in actual applications, the above functions can be completed by assigning them to different functional modules as needed, that is, by dividing the internal structure of the device into different functional modules, all or some of the functions described above can be completed. Furthermore, the embodiments of the battery health evaluation device and the battery health evaluation method provided in the above embodiment belong to the same concept, and their specific implementation process is shown in detail in the embodiment of the method, which will be omitted here.

[0103] Figure 4 is a schematic diagram of the structure of a computer device provided by an embodiment of the present invention. The computer device 400 includes a central processing unit (CPU) 401, a system memory 404 including random access memory (RAM) 402 and read-only memory (ROM) 403, and a system bus 405 connecting the system memory 404 and the central processing unit 401. The computer device 400 further includes a basic input / output system (I / O system) 406 to assist in the transmission of information between devices within the computer, and a mass storage device 407 for storing an operating system 413, applications 414 and other program modules 415.

[0104] The basic input / output system 406 includes a display 408 for displaying information and input devices 409 such as a mouse or keyboard for the user to input information. Here, both the display 408 and the input devices 409 are connected to the central processing unit 401 by an input / output controller 410 connected to a system bus 405. The basic input / output system 406 may further include an input / output controller 410 to receive and process input from several other devices such as a keyboard, mouse, or electronic stylus. Similarly, the input / output controller 410 may further provide output to a display screen, printer, or other type of output device.

[0105] The mass storage device 407 is connected to the central processing unit 401 by a mass storage controller (not shown) connected to the system bus 405. The mass storage device 407 and its associated computer-readable medium provide non-volatile storage to the computer equipment 400. That is, the mass storage device 407 may include a computer-readable medium (not shown), such as a hard disk or a CD-ROM drive.

[0106] Without loss of generality, computer-readable media may include computer storage media and communication media. Computer storage media include volatile and non-volatile, movable and immovable media implemented by any method or technique for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include RAM, ROM, EPROM, EEPROM, flash memory, or other solid-state storage technologies, CD-ROM, DVD, or other optical storage, tape cartridges, magnetic tapes, magnetic disk storage, or other magnetic storage devices. Naturally, those skilled in the art will see that computer storage media are not limited to the above-mentioned types. The system memory 404 and mass storage device 407 described above may be collectively referred to as memory.

[0107] According to various embodiments of the present invention, the computer device 400 may be connected to and run on a remote computer on a network, such as the Internet. That is, the computer device 400 may be connected to a network 412 via a network interface unit 411 connected to a system bus 405, or it may be connected to another type of network or remote computer system (not shown) using the network interface unit 411.

[0108] The above memory further includes one or more programs that are stored in memory and configured to be executed by the CPU.

[0109] Figure 5 is a structural block diagram of a vehicle 500 provided by an embodiment of the present application. Typically, the vehicle 500 includes a processor 501 and memory 502.

[0110] The processor 501 may include one or more processing cores, such as a 4-core processor or an 8-core processor. The processor 501 can be implemented in at least one hardware form from among DSP (Digital Signal Processing), FPGA (Field Programmable Gate Array), and PLA (Programmable Logic Array). The processor 501 may include a main processor and a sub-processor, the main processor being a processor used to process data in the awake state and also called a CPU (Central Processing Unit), and the sub-processor being a low-power processor used to process data in the standby state. In some embodiments, the processor 501 may integrate a GPU (Graphics Processing Unit) responsible for rendering and drawing content displayed on a display screen. In some embodiments, the processor 501 may further include an AI (Artificial Intelligence) processor for processing computational operations related to machine learning.

[0111] The memory 502 may include one or more computer-readable storage media, which may be non-temporary. The memory 502 may further include one or more high-speed random-access memories and non-volatile memories, such as magnetic disk storage devices and flash memory devices. In some embodiments, the non-temporary computer-readable storage media in the memory 502 are used to store at least one instruction to be executed by the processor 501 to implement the battery health evaluation method provided by embodiments of the method of the present application.

[0112] In some embodiments, the present invention further provides a computer-readable storage medium on which a computer program is stored, and which, when the computer program is executed by a processor, implements the steps of the battery health evaluation method in the above embodiments. For example, the computer-readable storage medium may be a ROM, RAM, CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0113] It should be noted that the computer-readable storage medium referred to in the embodiments of this application may be a non-volatile storage medium, or in other words, a non-temporary storage medium.

[0114] It should be understood that the steps to implement all or part of the above embodiments can be implemented by software, hardware, firmware, or any combination thereof. If implemented by software, all or part of them can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. The computer instructions may be stored on the computer-readable storage medium.

[0115] In other words, the present invention further provides a computer program product that includes instructions, wherein when the computer executes the computer, the computer performs the steps of the battery health evaluation method described above.

[0116] It should be understood that, as used herein, “at least one” refers to one or more, and “multiple” refers to two or more. In the description of the embodiments of this application, unless otherwise specified, “ / ” means “or.” For example, A / B can mean A or B, and “and / or” in this specification is simply a related relationship that describes related subjects, indicating that there can be three types of relationships. For example, A and / or B can represent three cases: A being present only, A and B being present simultaneously, and B being present only. Furthermore, in order to clearly describe the technical concepts of the embodiments of this application, terms such as “first,” “second,” etc., are used in the embodiments of this application to distinguish identical or similar items that have essentially the same function and operation. As will be understood by those skilled in the art, terms such as “first,” “second,” etc., do not limit the quantity or order of execution, and terms such as “first,” “second,” etc., are not necessarily limited to being different.

[0117] It should be explained that information relating to the embodiments of this application (including, but not limited to, user equipment information and user personal information), data (including, but not limited to, data used for analysis, stored data, and displayed data) and signals must all be obtained with the user's permission or with the full permission of each party involved, and the collection, use, and processing of relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions.

[0118] The above description is an embodiment provided by this Application and does not limit the Application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this Application should be included within the scope of the Claims.

[0119] This application claims priority to the Chinese patent application filed on September 25, 2023, application number 202311250802.3, with the title of invention "Method, apparatus, device and memory medium for evaluating the health status of a battery," the entire contents of which are incorporated herein by reference.

Claims

1. A method for evaluating the health status of a battery, wherein the method is To obtain target operating condition information for the target battery and the target cumulative charge / discharge capacity under the target operating conditions of the target battery, Determining a target battery health coefficient corresponding to the target operating condition information from the battery health coefficients corresponding to each of the multiple operating condition information intervals, This includes determining the health of the target battery based on the target cumulative charge / discharge capacity and the target battery health coefficient, The target operating condition information includes at least one of battery temperature, battery charge state, and charging mode, the charging mode includes a fast charging mode and a slow charging mode, the battery health coefficient is used to indicate the degree of influence of different operating condition information on the battery health state, and the health level is used to indicate the health state of the target battery. method.

2. The aforementioned plurality of operating condition information intervals are operating condition information intervals corresponding to target chemical system features, which are chemical system features of the target battery, and here, operating condition information intervals corresponding to different chemical system features are different. The method according to claim 1.

3. The aforementioned chemical system features include at least one of the electrode material, electrolyte material, and electrode piece process parameters. The method according to claim 2.

4. The battery health coefficients corresponding to each of the aforementioned multiple operating condition information intervals are obtained by simulating the entire lifecycle of the battery. Here, the simulation process is This involves obtaining a target temperature range, which is the temperature range that causes a decrease in battery life; a target charge state range, which is the charge state range that causes a decrease in battery life; and a target charge mode, which includes multiple charge modes. Dividing the aforementioned target temperature interval to obtain multiple sub-temperature intervals, and dividing the aforementioned target charge state interval to obtain multiple sub-charge state intervals, By combining the aforementioned sub-temperature intervals, the aforementioned sub-charged state intervals, and the aforementioned charging modes, a plurality of operating condition information intervals are obtained, each containing one sub-temperature interval, one sub-charged state interval, and one charging mode. The method is characterized by including determining a battery health coefficient corresponding to each of the multiple operating condition information intervals by a life simulation model based on the multiple operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the multiple operating condition information intervals. The method according to any one of claims 1 to 3.

5. Based on the aforementioned plurality of operating condition information intervals and the cumulative charge / discharge capacity corresponding to each of the plurality of operating condition information intervals, determining the battery health coefficient corresponding to each of the plurality of operating condition information intervals by a life simulation model is: For each of the aforementioned plurality of operating condition information intervals, the life simulation model determines the battery health coefficient corresponding to each of the plurality of operating condition data in the aforementioned operating condition information interval. The process includes determining the battery health coefficient corresponding to the operating condition information interval based on the battery health coefficient corresponding to each of the plurality of operating condition data and the cumulative charge / discharge capacity corresponding to the operating condition information interval, Each operating condition data is characterized by indicating one temperature, one charge state, and one charging mode. The method according to claim 4.

6. The target temperature interval, target charge state interval, and target charging mode are, respectively, temperature intervals, charge state intervals, and charging modes corresponding to target chemical system characteristics, and the target chemical system characteristics are the chemical system characteristics of the target battery, wherein the temperature intervals, charge state intervals, and charging modes corresponding to different chemical system characteristics are different. The method according to claim 4.

7. A device for evaluating the health status of a battery, wherein the device is A battery information acquisition module for obtaining target operating condition information of a target battery and target cumulative charge / discharge capacity under the target operating conditions of the target battery, A battery health coefficient determination module for determining a target battery health coefficient corresponding to the target operating condition information from battery health coefficients corresponding to each of multiple operating condition information intervals, Includes a battery health determination module for determining the health of the target battery based on the target cumulative charge / discharge capacity and the target battery health coefficient, The target operating condition information includes at least one of battery temperature, battery charge state, and charging mode, the charging mode includes a fast charging mode and a slow charging mode, the battery health coefficient is used to indicate the degree of influence of different operating condition information on the battery health state, and the health level is used to indicate the health state of the target battery. Device.

8. The aforementioned plurality of operating condition information intervals are operating condition information intervals corresponding to target chemical system features, which are chemical system features of the target battery, and here, operating condition information intervals corresponding to different chemical system features are different. The apparatus according to claim 7.

9. A vehicle comprising: a memory for storing a computer program; and a processor for executing the computer program stored in the memory to realize the steps of the method according to any one of claims 1 to 6, vehicle.

10. A computer-readable storage medium, wherein a computer program is stored in it, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are realized. storage medium.

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