Battery state prediction method and device, electronic equipment, storage medium and product

Abstract

The embodiment of the invention discloses a battery state prediction method and device, electronic equipment, a storage medium and a product, and the method comprises the steps: obtaining the current discharge voltage of a battery and the charging and discharging information of the battery in response to the condition that the voltage change of the battery meets a change condition; determining the discharge capacity of the battery based on the current discharge voltage and the battery charge and discharge information; determining the health state of the battery based on the discharge capacity and the initial rated capacity of the battery; based on the health state of the battery, correcting the thermodynamic characteristic curve of the battery to obtain a corrected thermodynamic characteristic curve; and predicting the current battery state of the battery based on the current discharge voltage and the corrected thermodynamic characteristic curve. Therefore, the health state and the residual capacity of the battery can be accurately predicted.

Description

Technical Field

[0001] This application relates to the field of battery testing, and in particular to battery state prediction methods, devices, electronic devices, storage media, and products. Background Technology

[0002] Currently, with the development of battery technology, batteries have gradually become the power source for various electrical devices such as vehicles and drones. Therefore, battery performance is a key factor in the overall reliability of the electronic system. Unexpected battery lifespan termination often leads to the failure of the entire electronic device system. Thus, predicting and analyzing battery degradation can provide timely and effective maintenance measures and battery replacement decisions, which is of great significance for improving system reliability and preventing catastrophic accidents. However, battery lifespan degradation occurs throughout the entire battery lifespan, therefore, battery lifespan assessment is necessary.

[0003] Related technologies assume that under the same internal and external operating conditions, the state of charge-open circuit voltage (SOC-OCV) curve of a battery remains unchanged before and after aging. Therefore, the used capacity can be calculated by integrating ampere-hours and recording the corresponding OCV to obtain the battery's lifespan and actual remaining mileage. However, during battery use, the SOC-OCV curve changes before and after aging. Therefore, the prediction methods in related technologies, based on an unchanging SOC-OCV curve, cannot accurately predict the capacity of aged batteries, easily leading to the problem of low SOC capacity without timely warning. Summary of the Invention

[0004] The main objective of this application is to provide a battery state prediction method, apparatus, electronic device, storage medium, and product that can accurately predict the health status and remaining capacity of an aged battery.

[0005] The technical solution of this application embodiment is implemented as follows:

[0006] In a first aspect, embodiments of this application provide a battery state prediction method, which includes: in response to a voltage change in the battery satisfying a change condition, acquiring the current discharge voltage and battery charge / discharge information of the battery; determining the discharge capacity of the battery based on the current discharge voltage and the battery charge / discharge information; determining the health state of the battery based on the discharge capacity and the initial rated capacity of the battery; correcting the thermodynamic characteristic curve of the battery based on the health state of the battery to obtain a corrected thermodynamic characteristic curve; and predicting the current battery state of the battery based on the current discharge voltage and the corrected thermodynamic characteristic curve.

[0007] Based on the above technical means, when the battery voltage decay meets the change conditions, the battery discharge capacity is determined and the battery health status is calculated. The SOC-OCV curve of the battery is corrected based on the health status, and the current state of the battery is predicted based on the corrected curve. This enables accurate prediction of the health status and remaining capacity of the aged battery, reducing the possibility of electronic devices losing power or cars breaking down due to inaccurate prediction results and failure to provide early warning of low battery levels. This improves the safety of electronic devices.

[0008] In the above scheme, the battery charge / discharge information includes at least the full charge cutoff voltage and the full discharge cutoff voltage of the battery; determining the discharge capacity of the battery based on the current discharge voltage and the battery charge / discharge information includes: in response to the battery charge / discharge information indicating that the battery meets the charge / discharge conditions, determining the discharge capacity of the battery based on at least one of the full charge cutoff voltage, the full discharge cutoff voltage, and the current discharge voltage; in response to the battery charge / discharge information indicating that the battery does not meet the charge / discharge conditions, obtaining the predicted health state of the battery, and determining the discharge capacity of the battery based on the predicted health state and the battery charge / discharge information.

[0009] Based on the aforementioned technical means, the battery's health status is calculated by checking whether the battery meets the charging and discharging conditions. Different calculation methods are used under different usage conditions to obtain the accurate life status of the battery, thereby determining the degree of battery aging and more accurately determining the remaining capacity of the battery.

[0010] In the above scheme, the discharge capacity includes at least a first discharge capacity, a second discharge capacity, and a third discharge capacity; the step of determining the discharge capacity of the battery based on at least one of the full charge cutoff voltage, the full discharge cutoff voltage, and the current discharge voltage in response to the battery charge / discharge information indicating that the battery meets the charge / discharge conditions includes: in response to the battery charge / discharge information indicating that the battery meets the full charge / discharge conditions, discharging the battery from the full charge cutoff voltage to the discharge capacity corresponding to the full discharge cutoff voltage, and determining this as the first discharge capacity of the battery; in response to the battery charge / discharge information indicating that the battery meets the full discharge conditions, determining the second discharge capacity of the battery based on the discharge capacity of the battery discharging from the current discharge voltage to the discharge capacity corresponding to the full discharge cutoff voltage; and in response to the battery charge / discharge information indicating that the battery meets the full charge conditions, charging the battery from the full discharge cutoff voltage to the capacity corresponding to the full charge cutoff voltage, and determining this as the third discharge capacity of the battery.

[0011] In the above scheme, the discharge capacity of the battery under different states is calculated by whether the battery's usage status meets the conditions of full charge and / or full discharge. The discharge capacity under different states is calculated based on the discharge capacity under different states, avoiding the problem of inaccurate health status calculation caused by calculating the discharge capacity under different states in one way.

[0012] In the above scheme, the battery charging and discharging information also includes the battery's voltage decay cutoff point; the discharge capacity includes at least a fourth discharge capacity; determining the battery's discharge capacity based on the predicted health state and the battery charging and discharging information includes: in response to the predicted health state meeting health conditions, determining the battery's discharge capacity from the completion of charging to the voltage decay cutoff point as the battery's fourth discharge capacity; or, determining the fourth discharge capacity based on the battery's target discharge capacity from the completion of charging to the target voltage and the discharge capacity from the target voltage to the voltage decay cutoff point.

[0013] In the above scheme, the discharge capacity further includes a fifth discharge capacity; the method further includes: in response to the predicted health state not meeting the health conditions, determining the discharge capacity of the battery from the completion of charging to the predicted cutoff voltage as the fifth discharge capacity of the battery; or, determining the fifth discharge capacity based on the target discharge capacity of the battery from the completion of charging to the target voltage and the discharge capacity from the target voltage to the predicted cutoff voltage.

[0014] Based on the aforementioned technical means, when the battery does not meet the conditions for full charge and / or full discharge, the calculation method for determining the discharge capacity by predicting the battery's predicted health state improves the accuracy of the health state calculation. In the above scheme, determining the battery's health state based on the discharge capacity and the battery's initial rated capacity includes: calculating the ratio between the first discharge capacity and the initial rated capacity to obtain the battery's health state.

[0015] In the above scheme, the method further includes: obtaining the initial discharge capacity of the battery in the initial state from the current discharge voltage to the full discharge cutoff voltage; correspondingly, determining the health status of the battery based on the discharge capacity and the initial rated capacity of the battery includes: calculating the health status of the battery based on the second discharge capacity, the initial discharge capacity and the initial rated capacity.

[0016] By using the aforementioned technical means, the health status of a battery can be determined through different usage states, thereby improving the accuracy of battery health status assessment.

[0017] In the above scheme, the method further includes: in response to the voltage change of the battery not meeting the change condition, obtaining the current operating condition of the battery and the corresponding degradation table of the battery; wherein, the degradation table is obtained based on a preset battery aging model and includes at least the simulated health state of the battery under different operating conditions; in the degradation table, the simulated health state corresponding to the current operating condition is determined as the health state of the battery.

[0018] Based on the above technical means, when the battery does not meet the calculation conditions, the SOH is predicted by the aging model. This avoids the situation where the SOC-OCV curve cannot be updated when the calculation is not possible, which would lead to a lack of warning about the battery capacity after aging and cause the electronic device to suddenly lose power.

[0019] In the above scheme, the step of correcting the thermodynamic characteristic curve of the battery based on the battery's health state to obtain a corrected thermodynamic characteristic curve includes: determining the degree of battery degradation based on the battery's health state and the battery's initial health state; and adjusting the trend of the battery's thermodynamic characteristic curve in the directions of battery capacity and voltage based on the degree of degradation to obtain a corrected thermodynamic characteristic curve.

[0020] Based on the above technical means, and adhering to the principle that the overall SOC-OCV curve of a metal battery without a negative electrode remains unchanged, the SOC-OCV curve of the battery is corrected so as to quickly determine the remaining capacity of the battery after aging.

[0021] In the above scheme, predicting the current battery state based on the current discharge voltage and the modified thermodynamic characteristic curve includes: predicting the current capacity of the battery based on the current discharge voltage and the modified thermodynamic characteristic curve; correspondingly, the method further includes: determining the remaining usable energy of the battery based on the current capacity of the battery and the initial rated capacity.

[0022] Based on the above-mentioned technical means, it is possible not only to calculate the remaining capacity of the battery after aging, but also to calculate the remaining usable energy of the battery, thus determining the battery condition from multiple dimensions and providing users with more accurate battery data.

[0023] Secondly, embodiments of this application provide a battery state prediction device, the device comprising: an acquisition module, configured to acquire the current discharge voltage and battery charge / discharge information of the battery in response to a voltage change of the battery satisfying a change condition; a first determination module, configured to determine the discharge capacity of the battery based on the current discharge voltage and the battery charge / discharge information; a second determination module, configured to determine the health state of the battery based on the discharge capacity and the initial rated capacity of the battery; a correction module, configured to correct the thermodynamic characteristic curve of the battery based on the health state of the battery to obtain a corrected thermodynamic characteristic curve; and a prediction module, configured to predict the current capacity of the battery based on the current discharge voltage and the corrected thermodynamic characteristic curve.

[0024] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor. The memory stores a computer program that can run on the processor, and when the processor executes the program, it implements the steps in the above-described battery state prediction method.

[0025] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps in the above-described battery state prediction method.

[0026] Fifthly, embodiments of this application provide a computer program product, including a computer program or instructions, which, when executed by a processor, implement the steps in the above-described battery state prediction method.

[0027] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0028] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application. Obviously, the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0029] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0030] Figure 1 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 1 ;

[0031] Figure 2 This is a schematic diagram of the SOC-OCV curve of a metal battery without a negative electrode provided in the embodiments of this application;

[0032] Figure 3 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 2 ;

[0033] Figure 4 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 3 ;

[0034] Figure 5 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 4 ;

[0035] Figure 6 This is a schematic diagram of the modified SOC-OCV curve provided in the embodiments of this application;

[0036] Figure 7 This is a flowchart illustrating the battery life and capacity prediction method provided in the embodiments of this application;

[0037] Figure 8 This is a schematic diagram of the SOC-OCV curve of a metal battery with multiple anomaly points provided in an embodiment of this application;

[0038] Figure 9 This is a schematic diagram of the composition structure of a battery state prediction device provided in an embodiment of this application. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the specific technical solutions of this application will be further described in detail below with reference to the accompanying drawings of the embodiments of this application. The following embodiments are used to illustrate this application, but are not intended to limit the scope of this application.

[0040] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this application is for descriptive purposes only and is not intended to be limiting of the application.

[0041] In the following description, references to "some embodiments," "this embodiment," "this embodiment," and examples, etc., describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subset of all possible embodiments and may be combined with each other without conflict.

[0042] If the application documents contain similar descriptions such as "first / second", the following explanation shall be added: In the following description, the terms "first / second / third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first / second / third" may be interchanged in a specific order or sequence where permitted, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein.

[0043] In the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three kinds of relationships. For example, object A and / or object B can represent three situations: object A exists alone, object A and object B exist simultaneously, and object B exists alone.

[0044] Currently, new energy batteries are increasingly widely used in daily life and industry. They are not only used in energy storage systems such as hydropower, thermal power, wind power, and solar power plants, but also extensively used in electric vehicles such as electric bicycles, electric motorcycles, and electric cars, as well as in aerospace and other fields. With the continuous expansion of the application areas of power batteries, the market demand is also constantly increasing. In this application embodiment, the battery involved can be a battery cell. A battery cell refers to a basic unit capable of converting chemical energy into electrical energy, which can be used to manufacture battery modules or battery packs to supply power to electrical devices. A battery cell can be a rechargeable battery, which refers to a battery cell that can be recharged after discharge to activate the active materials and continue to be used. Battery cells can be lithium-ion batteries, sodium-ion batteries, sodium-lithium-ion batteries, lithium metal batteries, sodium metal batteries, lithium-sulfur batteries, magnesium-ion batteries, nickel-metal hydride batteries, nickel-cadmium batteries, lead-acid batteries, etc., and this application embodiment is not limited to these.

[0045] In this embodiment, the battery may also be a single physical module comprising one or more battery cells to provide higher voltage and capacity. When there are multiple battery cells, the multiple battery cells are connected in series, parallel, or mixed via a busbar.

[0046] When batteries are used in electronic devices, in order to ensure that the electronic devices do not suddenly lose power, it is necessary to accurately predict the remaining energy of the battery so as to prompt the electronic devices to be charged, avoid sudden power outages or breakdowns in new energy vehicles, and improve the safety of electronic devices.

[0047] However, related technologies assume that under the same internal and external operating conditions, the SOC-OCV curve of a battery remains unchanged before and after aging. Therefore, the used capacity can be calculated by integrating ampere-hours and recording the corresponding OCV to obtain the battery's lifespan and actual remaining mileage. However, during battery use, even under the same internal and external operating conditions, the SOC-OCV curve changes before and after aging, and the degree of change intensifies with increasing aging. Therefore, the prediction methods in related technologies cannot accurately predict the capacity of aging batteries, easily leading to the problem of low SOC capacity without timely warning.

[0048] Traditional lithium-ion batteries suffer from active lithium loss, negative electrode material loss, and potentially positive electrode material loss. Sodium metal batteries, however, differ from traditional lithium-ion batteries. Sodium metal batteries are mostly negative electrode-less, coupled with stable positive electrode structural materials, resulting in a different degradation mode compared to lithium-ion batteries. The SOC-OCV curve exhibited after aging shows significant changes in the low SOC range, making it impossible to predict SOC-OCV using existing BMS control strategies. Therefore, this application proposes new lifetime prediction and remaining capacity prediction strategies for metal batteries with stable positive electrode materials.

[0049] Based on the aforementioned technical issues, the applicant believes that the health status of a battery can be determined based on its charging and discharging status. Given that sodium metal battery cathode materials have good structural stability and no obvious structural decay, ensuring that the overall SOC-OCV curve remains unchanged, the SOC-OCV curve of the battery can be corrected based on its health status. The corrected SOC-OCV curve can then be used to predict the battery's state, such as its current capacity and remaining energy.

[0050] Based on the above inventive concept, this application provides a battery state prediction method. The battery state prediction method can be applied to the processor of an electronic device powered by a battery, or it can be applied to a battery management system (BMS).

[0051] The battery state prediction method provided in this application, in response to the battery voltage change meeting the change condition, obtains the current discharge voltage and battery charge / discharge information of the battery, determines the discharge capacity of the battery based on the current discharge voltage and battery charge / discharge information, determines the health state of the battery based on the discharge capacity and the initial rated capacity of the battery, corrects the thermodynamic characteristic curve of the battery based on the health state of the battery to obtain a corrected thermodynamic characteristic curve, and predicts the battery state based on the current discharge voltage and the corrected thermodynamic characteristic curve, such as the current capacity and remaining energy of the battery.

[0052] Thus, in this embodiment of the application, when the battery voltage decay meets the change condition, the battery discharge capacity is determined and the battery health status is calculated. Based on the health status, the SOC-OCV curve of the battery is corrected, and based on the corrected curve, the current capacity of the battery is predicted. This can accurately predict the health status and remaining capacity of the aged battery, reducing the possibility of electronic devices losing power or cars breaking down due to inaccurate prediction results and failure to provide early warning of low battery. This improves the safety of using electronic devices.

[0053] The battery state prediction method disclosed in this application, once the battery cell is located, can be used in electronic devices such as vehicles, ships, or aircraft, but is not limited to such use. A power system comprising the device can be constructed using batteries disclosed in this application. This helps to mitigate and automatically regulate the deterioration of cell expansion force, replenish electrolyte consumption, and improve battery performance stability and battery life.

[0054] The battery state prediction method disclosed in this application predicts that the predicted battery can be used as a power source for electrical devices. These devices can be, but are not limited to, mobile phones, tablets, laptops, electric toys, power tools, electric vehicles, electric cars, ships, spacecraft, etc. Electric toys can include stationary or mobile electric toys, such as game consoles, electric car toys, electric ship toys, and electric airplane toys, etc. Spacecraft can include airplanes, rockets, space shuttles, and spacecraft, etc.

[0055] This application provides a battery state prediction method to improve the accuracy and efficiency of battery state prediction. The executing entity can be a processor of a battery-powered electronic device (e.g., a car) or a BMS (Battery Management System). The technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0056] See Figure 1 , Figure 1 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 1 The battery state prediction method is implemented through steps S101 to S105:

[0057] Step S101: In response to the battery voltage change satisfying the change condition, obtain the current discharge voltage of the battery and the battery charge / discharge information.

[0058] In some embodiments, the low SOC range of the SOC-OCV curve exhibited by a metal battery without a negative electrode (such as a sodium metal battery) after aging will show significant changes. Figure 2 This is a schematic diagram of the SOC-OCV curve of a metal battery without a negative electrode provided in the embodiments of this application, as shown below. Figure 2As shown, 201 is the discharge curve of a metal battery without a negative electrode. At low cell capacity, i.e., low SOC range (i.e., relatively low battery capacity), the discharge curve shows a clear inflection point 2011. Before and after the inflection point 2011, the curve slope is very steep, indicating that the battery has virtually no capacity and requires charging and a warning. Figure 2 As shown, when batteries are used in new energy vehicles, the battery voltage drops rapidly from A volts (V) to BV after the inflection point. Without advance prediction or warning, driving becomes extremely dangerous, and breakdowns are possible at any time. Therefore, this embodiment of the application can predict and warn about the battery capacity during the steep slope before the inflection point, providing accurate battery capacity and remaining mileage, thus improving driving safety.

[0059] It should be noted that there may be at least one inflection point in the low SOC range. At this time, capacity prediction can be performed on the steep slope segment before each inflection point, and an early warning can be issued when the capacity is lower than the preset value (e.g., 20%).

[0060] Here, determining whether a battery has entered a steep discharge curve can be based on changes in battery voltage. A voltage change meeting the condition means that for every 1% decrease in the battery's State of Charge (SOC), the voltage decay exceeds 300mV, indicating that the battery discharge curve has entered a steep discharge curve. Therefore, after the battery enters this steep range, the current discharge voltage and charge / discharge information can be obtained. This information includes whether the battery is discharging from a fully charged state, the battery's thermodynamic characteristic curve (SOC-OCV curve), and the battery's full charge cutoff voltage and full discharge cutoff voltage. The full charge cutoff voltage refers to the battery voltage when its capacity is 100%, indicating a fully charged battery. The full discharge cutoff voltage refers to the battery voltage when its capacity is 0%, indicating a fully discharged battery. The full discharge cutoff voltage can be manually set. To avoid situations where the battery capacity is depleted without warning, the full discharge cutoff voltage can be set to a value greater than AV. At this point, the battery still has capacity and will not rapidly decrease below AV, potentially causing electronic devices to lose power or the car to break down.

[0061] In some embodiments, battery charge / discharge information may be information about the current use of the battery or historical information about the battery, such as information about the last time the battery was used.

[0062] In some embodiments, such as Figure 2As shown, there is also a large slope segment 2012 in the high SOC range (i.e., when the battery capacity is sufficient). To avoid implementing this scheme in the large slope segment 2012, the change condition can also limit the battery voltage. For example, the change condition can also be that when the battery voltage is less than CV (when the battery voltage is less than CV, the large slope segment 2012 is avoided), the voltage decay is greater than 300mV for every 1% decrease in the battery's SOC. When the battery voltage change meets the change condition, the current discharge voltage and battery charge / discharge information of the battery are obtained.

[0063] Step S102: Determine the discharge capacity of the battery based on the current discharge voltage and the battery charge / discharge information.

[0064] In some embodiments, based on battery charge and discharge information, the current usage state of the battery can be determined, and the battery's discharge capacity can be determined based on the current usage state. For example, if the battery usage meets the full charge and discharge conditions, that is, if the battery usage can discharge from a fully charged state to a fully discharged state, or if the battery's last usage was from a fully charged state to a fully discharged state, that is, when the battery voltage discharges from the full charge cutoff voltage to the full discharge cutoff voltage, then the discharge capacity of the battery from the full charge cutoff voltage to the full discharge cutoff voltage can be determined as the battery's discharge capacity.

[0065] In some embodiments, if the battery meets the full discharge condition during this use, that is, the battery discharges from the current discharge voltage to the full discharge cutoff voltage or the battery discharged from the current discharge voltage to the full discharge cutoff voltage during the last use, the discharge capacity from the current discharge voltage to the full discharge cutoff voltage is determined as the battery's discharge capacity.

[0066] In some embodiments, when the battery does not meet the full charge and discharge conditions, the discharge capacity of the battery can be determined by ampere-hour integration, accumulating the capacity of the battery from the full charge cutoff voltage to the full discharge cutoff voltage.

[0067] Step S103: Determine the health status of the battery based on the discharge capacity and the initial rated capacity of the battery.

[0068] In this embodiment, the battery health status refers to the battery's state of health (SOH), which characterizes the battery's storage capacity. After battery aging, even if the battery's SOC is 100%, the capacity of the aged battery at 100% SOC is less than the battery's initial rated capacity. Therefore, it is necessary to calculate the battery's current SOH to correct the battery's SOC-OCV curve in order to obtain a more accurate SOC corresponding to the voltage after the battery's capacity changes due to aging.

[0069] The initial rated capacity of a battery refers to its capacity when it is not in use. The battery's state of discharge (SOH) can be determined by calculating the ratio of its discharge capacity to its initial rated capacity.

[0070] For example, if a battery is used under full charge and discharge conditions, the SOH of the battery is determined by calculating the ratio of the battery's discharge capacity to its initial rated capacity. If a battery is used under full discharge conditions, the SOH of the battery is calculated based on the ratio of the battery's discharge capacity from the current discharge voltage to the full discharge cutoff voltage to the rated discharge capacity of the battery when it is not in use, from the current discharge voltage to the full discharge cutoff voltage.

[0071] In some embodiments, the battery health status is used to determine the battery capacity at full charge (100% SOC), and then to determine the current remaining capacity of the battery based on the current discharge voltage of the battery.

[0072] Step S104: Based on the health status of the battery, the thermodynamic characteristic curve of the battery is corrected to obtain the corrected thermodynamic characteristic curve.

[0073] In some embodiments, the positive electrode material of a metal battery without a negative electrode has good structural stability and no obvious structural decay, which can ensure that the overall SOC-OCV curve remains unchanged. Therefore, after determining the health state of the battery, the battery degradation can be determined. For example, if the rated capacity of the battery is 100 ampere-hours (Ah), the current full charge and discharge capacity is 80 Ah, the battery health state is 80%, and the degradation degree is 20%, then the SOC-OCV curve of the battery can be corrected, for example, by compressing it by 20%, to obtain a corrected thermodynamic characteristic curve.

[0074] Step S105: Based on the current discharge voltage and the corrected thermodynamic characteristic curve, predict the current battery state of the battery.

[0075] In some embodiments, the current state of the battery may include information such as the current capacity of the battery, the current remaining energy (SOE) of the battery, and the state of water (SOW) of the battery.

[0076] In this embodiment of the application, after obtaining the corrected thermodynamic characteristic curve, the current capacity of the battery can be determined based on the current discharge voltage of the battery, and a warning can be issued to the user when the current capacity of the battery is lower than the capacity threshold.

[0077] In this embodiment, when the battery voltage decay meets the change condition, the battery discharge capacity is determined and the battery health status, i.e., the battery life, is calculated. Based on the health status, the SOC-OCV curve of the battery is corrected, and the current capacity of the battery is predicted based on the corrected curve. This can accurately predict the health status and remaining capacity of the aged battery, reducing the possibility of electronic devices losing power or cars breaking down due to inaccurate prediction results and failure to provide early warning of low battery. This improves the safety of using electronic devices.

[0078] In some embodiments, battery charge and discharge information includes at least the battery's full charge cut-off voltage and full discharge cut-off voltage, which can be obtained based on the battery's historical usage data, such as data from the previous charge and discharge. Here, the full charge cut-off voltage can refer to the battery voltage when the battery capacity is 100%, indicating that the battery is fully charged, and the full discharge cut-off voltage can refer to the battery voltage when the battery capacity is 0%, indicating that the battery is fully discharged.

[0079] Figure 3 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 2 ,like Figure 3 As shown, step S102 can be achieved through steps S301 to S302:

[0080] Step S301: In response to the battery charging and discharging information indicating that the battery meets the charging and discharging conditions, determine the discharge capacity of the battery based on at least one of the full charge cutoff voltage, the full discharge cutoff voltage and the current discharge voltage.

[0081] In the embodiments of this application, the battery charge and discharge information indicates that the battery meets the charge and discharge conditions. This can be because the battery is being discharged from a fully charged state to a fully discharged state during the current or previous use, or the battery is being discharged from a fully charged state to the current discharge voltage during the current or previous use, or the battery is being discharged from the current discharge voltage to the full discharge cutoff voltage during the current or previous use. The battery's discharge capacity can be calculated using at least one of the full charge cutoff voltage, the full discharge cutoff voltage, and the current discharge voltage.

[0082] In some embodiments, the battery's health status varies depending on its operating conditions. Therefore, under different operating conditions, the battery's discharge capacity may include at least a first discharge capacity, a second discharge capacity, and a third discharge capacity. Correspondingly, step S301 can be implemented through steps S3011 to S3013:

[0083] Step S3011: In response to the battery charging and discharging information indicating that the battery meets the full charge and discharge conditions, the battery is discharged from the full charge cutoff voltage to the discharge capacity corresponding to the full discharge cutoff voltage, and determined as the first discharge capacity of the battery.

[0084] In some embodiments, the discharge capacity corresponding to the battery's discharge from a fully charged state to a fully discharged state, i.e., from the full charge cutoff voltage to the full discharge cutoff voltage, can be determined as the battery's first discharge capacity C1, which can be obtained directly based on the battery's usage data.

[0085] Correspondingly, assuming the battery meets the conditions for full charge and discharge, step S103 can be achieved through step S1031:

[0086] Step S1031: Calculate the ratio between the first discharge capacity and the initial rated capacity to obtain the health status of the battery.

[0087] In some embodiments, the initial rated capacity of the battery is C0, and the state of health (SOH1) of the battery under full charge and discharge conditions can be calculated using formula (1):

[0088] SOH1=C1 / C0 (1);

[0089] Step S3012: In response to the battery charging and discharging information indicating that the battery meets the full discharge condition, the second discharge capacity of the battery is determined based on the discharge capacity corresponding to the discharge from the current discharge voltage to the full discharge cutoff voltage.

[0090] In some embodiments, battery charge and discharge information indicates that the battery meets the full discharge condition, that is, the voltage can be discharged to the full discharge cutoff voltage. This can be the battery being discharged to the full discharge cutoff voltage during the current or previous use. The discharge capacity corresponding to the battery being discharged from the current discharge voltage to the full discharge cutoff voltage during the current or previous use is determined as the battery's second discharge capacity C2.

[0091] In some embodiments, based on the condition that the battery meets the full discharge condition, the battery state prediction method provided in this application embodiment may further include step S1:

[0092] Step S1: Obtain the initial discharge capacity of the battery in the initial state, from the current discharge voltage to the full discharge cutoff voltage.

[0093] Here, the initial state of the battery refers to the battery in an unused state, i.e., when the battery's state of health (SOH) is 100%. The initial discharge capacity C3 is obtained based on the battery's charge and discharge information, corresponding to the discharge from the current discharge voltage to the full discharge cutoff voltage. The initial discharge capacity C3 can be obtained based on the battery's historical usage data.

[0094] Correspondingly, step S103 can be achieved through step S1032:

[0095] Step S1032: Calculate the health status of the battery based on the second discharge capacity, the initial discharge capacity, and the initial rated capacity.

[0096] In some embodiments, the initial rated capacity of the battery is C0, and the state of health SOH2 of the battery under fully discharged conditions can be calculated by formula (2):

[0097]

[0098] Step S3013: In response to the battery charging and discharging information indicating that the battery meets the full charge condition, the battery is charged from the full discharge cutoff voltage to the capacity corresponding to the full charge cutoff voltage, and this capacity is determined as the third discharge capacity of the battery.

[0099] In some embodiments, battery charge / discharge information characterizing that the battery meets the full charge condition can mean that the battery can be charged from the voltage V1 corresponding to the open-circuit voltage of 0% SOC as the starting charging voltage to the full charge cutoff voltage V2, combined with Figure 2 The voltage V1 corresponding to 0% SOC can be BV, and the full charge cutoff voltage V2 can be DV. The charging capacity from the full discharge cutoff voltage BV to the full charge cutoff voltage DV can be determined as the third discharge capacity C4 of the battery.

[0100] Correspondingly, step S103 can be achieved through step S1033:

[0101] Step S1033: Calculate the ratio between the third discharge capacity and the initial rated capacity to obtain the health status of the battery.

[0102] In some embodiments, the initial rated capacity of the battery is C0, and the state of health (SOH3) of the battery under full charge conditions can be calculated using formula (3):

[0103] SOH3=C4 / C0 (3);

[0104] Step S302: In response to the battery charging and discharging information indicating that the battery does not meet the charging and discharging conditions, obtain the predicted health status of the battery, and determine the discharge capacity of the battery based on the predicted health status and the battery charging and discharging information.

[0105] In some embodiments, battery charge and discharge information can indicate that the battery does not meet the charge and discharge conditions, meaning that the battery was not used from a fully charged state and did not have the opportunity to reach a fully discharged state. In other words, the battery was not used from 100% SOC and will not be used at 0% SOC. In this case, the health status of the battery can be predicted based on aging models, and the current discharge capacity of the battery can be calculated based on the predicted health status.

[0106] Here, the health status of the battery can be predicted based on an aging model using data such as the number of battery cycles and the battery's historical operating temperature.

[0107] In some embodiments, before battery use, this type of battery is tested under different temperatures and operating conditions (e.g., cycle count) to determine the battery degradation rate under different conditions, thereby obtaining a battery degradation table. The predicted state of health of the battery is predicted by looking up the table. For example, the battery degradation table can determine that at a temperature of around 25 degrees Celsius, the battery degradation after 500 cycles is 10%, and at a temperature of around 45 degrees Celsius, the degradation after 500 cycles is 15%. Based on the battery's usage, the predicted state of health of the battery can be obtained by looking up the table.

[0108] In some embodiments, the battery charge / discharge information also includes the battery's voltage decay cutoff point. Here, the voltage decay cutoff point can refer to the condition that the battery voltage decay meets, for example, in conjunction with... Figure 2 The voltage decay cutoff point can be defined as follows: when the battery voltage is less than CV, for every 1% decrease in the battery's SOC, the voltage decay exceeds 300mV. At this point, the battery's SOC-OCV curve enters a steep slope segment, indicating low battery capacity, requiring a warning. The discharge capacity can also include a fourth discharge capacity. Correspondingly, step S302 can be implemented through either step S3021 or step S3022.

[0109] Step S3021: In response to the predicted health state meeting the health conditions, the discharge capacity of the battery from the completion of charging to the voltage decay cutoff point is determined as the fourth discharge capacity of the battery.

[0110] In some embodiments, the predicted health status meeting the health condition can mean that the predicted health status of the battery is greater than or equal to 90%, that is, the aging of the battery is not serious. In this case, the cumulative discharge capacity accumulated from the completion of charging to the voltage decay cutoff point after the battery is fully charged can be determined as the fourth discharge capacity C5 of the battery.

[0111] Step S3022: Determine the fourth discharge capacity based on the target discharge capacity of the battery from the completion of charging to the target voltage, and the discharge capacity from the target voltage to the voltage decay cutoff point.

[0112] In some embodiments, when the predicted state of health of the battery is greater than or equal to 90%, a fourth discharge capacity C5 can be calculated based on the discharge capacity from a target voltage to the voltage decay cutoff point, and the target discharge capacity of the battery from the completion of charging to the target voltage. For example, if the battery capacity is 100Ah and the discharge capacity to 3V is 50Ah, the cumulative capacity C5 from 3V to the voltage decay cutoff point can be obtained. 5-1 The fourth discharge capacity C5 is obtained as shown in formula (4):

[0113] C5 = 50Ah + C 5-1 (4);

[0114] Correspondingly, step S103 can be achieved through step S1034:

[0115] Step S1034: Calculate the ratio between the fourth discharge capacity and the initial rated capacity to obtain the health status of the battery.

[0116] In some embodiments, the initial rated capacity of the battery is C0, and the state of health (SOH4) of the battery under predicted health conditions greater than or equal to 90% can be calculated using formula (5):

[0117] SOH4=C5 / C0 (5);

[0118] In some embodiments, step S302 can also be implemented by step S3023 or step S3024:

[0119] Step S3023: In response to the predicted health state not meeting the health conditions, the discharge capacity of the battery from the completion of charging to the predicted cutoff voltage is determined as the fifth discharge capacity of the battery.

[0120] In some embodiments, when the predicted state of health is less than 90%, the battery capacity has decreased significantly compared to the initial state. Based on the predicted state of health, the cutoff voltage at the current aging state of the battery, i.e., the voltage corresponding to a SOC of 0%, can be predicted. In this case, the cumulative discharge capacity from charging to discharging up to the predicted cutoff voltage after the battery has completed charging can be determined as the battery's fifth discharge capacity C6.

[0121] Step S3024: Determine the fifth discharge capacity based on the target discharge capacity of the battery from the completion of charging to the target voltage, and the discharge capacity from the target voltage to the predicted cutoff voltage.

[0122] In some embodiments, when the predicted state of health of the battery is less than 90%, the fifth discharge capacity C6 can be calculated based on the discharge capacity from a target voltage to the predicted cutoff voltage, and the target discharge capacity of the battery from the completion of charging to the target voltage.

[0123] Correspondingly, step S103 can be achieved through step S1035:

[0124] Step S1035: Calculate the ratio between the fifth discharge capacity and the initial rated capacity to obtain the health status of the battery.

[0125] In some embodiments, the initial rated capacity of the battery is C0, and the state of health (SOH4) of the battery when the predicted health condition is less than 90% can be calculated by formula (6):

[0126] SOH5=C6 / C0 (6);

[0127] This application embodiment calculates the battery's health status based on its current usage state. Different calculation methods are used under different usage states to obtain the battery's accurate lifespan status, thereby determining the degree of battery aging and more accurately determining the battery's remaining capacity.

[0128] Figure 4 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 3 ,like Figure 4 As shown, when the battery voltage change does not meet the change conditions, the battery state prediction method provided in this application embodiment further includes steps S401 and S402:

[0129] Step S401: In response to the battery voltage change not meeting the change condition, obtain the current operating condition of the battery and the corresponding degradation table of the battery; wherein, the degradation table is obtained based on a preset battery aging model and includes at least the simulated health state of the battery under different operating conditions.

[0130] Here, the fact that the battery voltage change does not meet the change condition indicates that the battery voltage decay is not significant, and the empirical SOH can be calculated based on the aging model.

[0131] In some embodiments, the degradation table is obtained based on a preset battery aging model, which includes at least the simulated health state of the battery under different usage conditions. For example, the battery degradation table can determine that at a temperature of about 25 degrees Celsius, the battery degradation after 500 cycles is 10%, and the simulated health state is 90%; at a temperature of about 45 degrees Celsius, the battery degradation after 500 cycles is 15%, and the simulated health state is 85%.

[0132] Here, the current operating conditions can be the temperature range of the battery's historical operating temperature, such as between 20-30 degrees Celsius, and the battery's cycle count, that is, the number of times the battery has been discharged from a fully charged state to a fully discharged state.

[0133] In some embodiments, after each battery's state of health (SOH) is calculated, the parameters of the battery's aging model are updated, and the corresponding degradation table for that battery is updated using the updated aging model, so that the determination of the battery's health status through the degradation table is more accurate.

[0134] Step S402: In the attenuation table, determine the simulated health state corresponding to the current operating condition as the health state of the battery.

[0135] In this embodiment of the application, after determining the current operating conditions of the battery, the health status of the battery can be determined by looking up the degradation table.

[0136] In this embodiment, when the battery does not meet the calculation conditions, the SOH is predicted by the aging model. This avoids the situation where the SOC-OCV curve cannot be updated when the calculation is not possible, which would result in no warning for the battery capacity after aging and cause the electronic device to suddenly lose power.

[0137] In some embodiments, since the positive electrode structure of sodium metal batteries has good stability and no obvious structural decay, the overall SOC-OCV curve can be kept unchanged. Therefore, the SOC-OCV curve can be corrected based on the health status of the battery. Figure 5 This is a flowchart illustrating an optional battery state prediction method provided in an embodiment of this application. Figure 4 ,like Figure 5 As shown, step S104 can also be achieved through steps S501 and S502:

[0138] Step S501: Determine the degree of battery degradation based on the battery's health status and its initial health status.

[0139] In some embodiments, the initial health state of the battery is 100%. After determining the health state of the battery, the degree of battery degradation can be determined. For example, if the health state of the battery is 94%, the degree of degradation is 6%, which means that the battery capacity has decreased by 6% compared to the battery's rated capacity.

[0140] Step S502: Based on the degree of attenuation, adjust the trend of the thermodynamic characteristic curve of the battery in the directions of battery capacity and voltage respectively to obtain a corrected thermodynamic characteristic curve.

[0141] In the embodiments of this application, the positive electrode material of the metal battery without a negative electrode has good structural stability and no obvious structural decay, which can ensure that the overall SOC-OCV curve is not deformed. Therefore, after determining the degree of battery decay, the SOC-OCV curve of the battery can be corrected. For example, the SOC-OCV curve can be compressed by 6% in the direction of battery capacity and voltage to obtain a corrected thermodynamic characteristic curve.

[0142] In some embodiments, the corrected thermodynamic characteristic curve and the initial thermodynamic characteristic curve of the battery have the same open-circuit voltage when the SOC is 100%.

[0143] Figure 6 This is a schematic diagram of the modified SOC-OCV curve provided in the embodiments of this application, as shown below. Figure 6 As shown in Figure 601, the thermodynamic characteristic curve of the battery is shown in Figure 602.

[0144] Based on the principle that the overall SOC-OCV curve of a metal battery without a negative electrode remains unchanged, this application corrects the SOC-OCV curve of the battery to quickly determine the remaining capacity of the battery after aging.

[0145] In some embodiments, after obtaining the corrected SOC-OCV curve, step S105 can be implemented through step S1051:

[0146] Step S1051: Based on the current discharge voltage and the corrected thermodynamic characteristic curve, predict the current capacity of the battery.

[0147] In this embodiment of the application, after obtaining the modified thermodynamic characteristic curve, the SOC of the battery corresponding to the current discharge voltage, i.e. the current capacity, can be found in the modified thermodynamic characteristic curve based on the current discharge voltage.

[0148] In some embodiments, after predicting the remaining battery capacity, information such as the remaining range of the vehicle and the remaining usable energy of the battery can be calculated based on the remaining battery capacity. Therefore, the battery state prediction method provided in this application embodiment may further include step S10:

[0149] Step S10: Determine the remaining usable energy of the battery based on its current capacity and initial rated capacity.

[0150] In some embodiments, after determining the current capacity SOH of the battery, the remaining usable energy SOE of the battery can be calculated based on the initial rated capacity of the battery, as shown in formula (7):

[0151] SOE=SOH*C0 (7)

[0152] The embodiments of this application can not only calculate the remaining capacity of the battery after aging, but also calculate the remaining usable energy and moisture content of the battery, which can determine the battery condition from multiple dimensions and provide users with more accurate battery data.

[0153] The following section presents an application of a battery state prediction method in a real-world scenario.

[0154] Based on the methods for predicting the remaining life of batteries in related technologies, it is believed that the SOC-OCV curve of a battery does not change before and after aging under the same internal and external working environment. Therefore, the battery capacity used can be calculated by ampere-hour integration, and the corresponding OCV can be recorded. Combined with the change in battery capacity (ΔCAP, Δcapacity) corresponding to ΔOCV, the cell life can be predicted. The battery aging model can be used to predict and correct the overall battery life state and the actual remaining range of the battery.

[0155] However, the SOC-OCV curves of batteries change during use and before and after aging. Therefore, the prediction methods in related technologies cannot accurately predict the capacity of aging batteries, which can easily lead to the problem of low SOC capacity without timely warning.

[0156] Traditional lithium-ion batteries suffer from the loss of active lithium, anode material loss, and potentially cathode material loss. Sodium metal batteries, however, differ from traditional lithium-ion batteries. Sodium metal batteries are mostly anode-less, coupled with stable cathode materials, resulting in a different degradation pattern compared to lithium-ion batteries. This leads to significant curve anomalies, with the SOC-OCV curve showing marked changes in the low SOC range due to the loss of active sodium. Furthermore, the cathode material exhibits good structural stability without significant structural decay, ensuring the overall curve remains unchanged. Therefore, sodium metal batteries cannot use existing BMS control strategies to predict SOC-OCV. This application proposes a new lifetime and remaining capacity prediction strategy for sodium metal batteries with stable cathode materials.

[0157] Figure 7 This is a flowchart illustrating the battery life and capacity prediction method provided in this application embodiment. The battery life and capacity prediction method provided in this application embodiment can be implemented through steps S701 to S710:

[0158] S701. When the battery meets the calculation conditions and has full charge and discharge conditions, the life status is determined by the discharge capacity of full charge and discharge and the initial rated capacity of the battery.

[0159] In some embodiments, the battery meeting the calculation condition may refer to the battery voltage decay meeting the condition, for example, when the voltage is less than X2 volts (V), the voltage change exceeds X2mV for every 1% SOC. Figure 6 These are comparison graphs of the discharge curves of a sodium metal battery before and after aging, provided in the embodiments of this application. 601 is the discharge curve of the battery in its fresh state (unused or minimally used), and 602 is the discharge curve of the battery after aging. Figure 6 It can be seen that the discharge curve of sodium metal batteries changes before and after aging. Curve 601 shows that sodium batteries in a fresh state have an inflection point during the rapid capacity decline phase, and may have multiple inflection points. Figure 6 Only the case with one inflection point is shown.

[0160] based on Figure 6 The battery meeting the calculation conditions can mean that when the voltage is less than CV, the voltage change exceeds 200mV or 300-200mV for every 1% SOC. At this time, the slope of the discharge curve is large, indicating that the battery capacity is small and the device (such as a car) using the battery needs to be reminded.

[0161] In some embodiments, having full charge / discharge conditions means that the battery is fully charged when the voltage exceeds a preset maximum calibration threshold and lasts for a certain preset time; and the battery discharge voltage exceeds the cutoff voltage. In this case, the battery capacity C1 released from the full charge state to the cutoff voltage can be determined. Based on C1 and the battery's rated initial capacity C0, the battery's life state SOH1 is calculated. SOH1 can be achieved by formula (8):

[0162] SOH1=C1 / C0 (8);

[0163] S702. When the battery meets the calculation conditions and has the condition of being fully discharged, the life status is determined by the current discharge voltage and discharge cutoff voltage of the battery.

[0164] In some embodiments, the presence of a full discharge condition indicates that the battery was not used from a fully charged state. In this case, the current discharge voltage of the battery can be determined. Based on the current discharge voltage and the cutoff voltage, the capacity C2 of the battery discharged from the current discharge voltage to the cutoff voltage and the capacity C3 of the battery discharged from the current discharge voltage to the cutoff voltage when it is in a fresh state can be determined. The lifespan state SOH2 can be determined, and SOH2 can be achieved by formula (9):

[0165]

[0166] S703 When the battery meets the calculation conditions and has full charge conditions, the lifespan status is determined by the charging capacity from full discharge to full charge.

[0167] When the battery has the opportunity to charge from the voltage corresponding to 0% SOC (open circuit voltage) as the initial charging condition V1 to the full charge cutoff voltage V2, if Figure 2 The voltage V1 corresponding to 0% SOC can be BV, the full charge cutoff voltage V3 can be DV, and the charging capacity from V2 to V3 is C4. Then the lifetime state SOH3 can be achieved by formula (10):

[0168] SOH3=C4 / C0 (10);

[0169] S704. When the battery meets the calculation conditions, does not have full charge and discharge conditions, and the predicted SOH of the battery meets the lifetime conditions, the lifetime status is determined by accumulating the capacity discharged to the voltage decay cutoff point through ampere-hour integration.

[0170] Here, when the battery meets the calculation conditions but does not have the conditions for full charge and discharge, it is necessary to predict the battery's life state through an aging model to obtain the predicted SOH of the battery. When the predicted SOH is greater than or equal to 90%, the cumulative capacity C5 can be accumulated from the start of charging to the voltage decay cutoff point after the battery is fully charged. The life state SOH4 can be realized by formula (11):

[0171] SOH4=C5 / C0 (11);

[0172] Here, C5 can also be calculated based on the discharge capacity from a certain voltage to the voltage decay cutoff point. For example, if the discharge capacity of the battery from full charge to 3.0V is 50Ah and the total battery capacity is 100Ah, the cumulative capacity from 3.0V to the voltage decay cutoff point can be recorded as C5'. At this time, C5 = 50Ah + C5', and then the lifetime state SOH4 can be calculated using formula (10).

[0173] S705. When the battery meets the calculation conditions, does not have full charge and discharge conditions, and the predicted SOH of the battery meets the lifespan conditions, the lifespan status is determined by accumulating the capacity discharged to the voltage cutoff point through ampere-hour integration.

[0174] In some embodiments, when the predicted SOH is less than 90%, the cumulative capacity C6 from the start of charging to the voltage cutoff point can be accumulated after the battery is fully charged. The lifetime state SOH5 can be achieved by formula (12):

[0175] SOH5=C6 / C0 (12);

[0176] Here, C6 can also be calculated based on the discharge capacity from a certain voltage to the voltage cutoff point. For example, the discharge capacity of the battery from full charge to 3.0V is 50Ah, and the total battery capacity is 100Ah. The cumulative capacity from 3.0V to the voltage decay point can be recorded as C6'. At this time, C6 = 50Ah + C6', and then the lifetime state SOH5 can be calculated using formula (12).

[0177] S706. When the battery does not meet the calculation conditions, the life status is determined based on the operating condition calculation and aging model.

[0178] In some embodiments, the battery not meeting the calculation conditions may mean that the battery voltage degradation is not significant, and empirical SOH6 can be calculated based on the aging model.

[0179] In some embodiments, a battery degradation table can be obtained based on a preset battery aging model, which includes at least the simulated health status of the battery under different operating conditions. For example, the battery degradation table can determine that at a temperature of about 25 degrees Celsius, the battery degradation after 500 cycles is 10%, and the simulated health status is 90%; at a temperature of about 45 degrees Celsius, the battery degradation after 500 cycles is 15%, and the simulated health status is 85%.

[0180] Here, the empirical SOH6 can be obtained by looking up the degradation table based on the battery's current operating conditions. The current operating conditions can be the temperature range of the battery's historical operating temperature, such as between 20-30 degrees Celsius, and the battery's cycle count, i.e., the number of times the battery has been discharged from a fully charged state to a fully discharged state.

[0181] S707, Determine the current lifespan status of the battery.

[0182] The current lifespan state is determined based on the conditions under which the battery operates. The State of Health (SOH) under different conditions in steps S701 to S706 can be the same or different. The current lifespan state of the battery is determined from the multiple SOH values ​​obtained in steps S701 to S706 based on the conditions under which the battery operates.

[0183] S708, Update the battery life status.

[0184] S709, Update the OCV curve of the battery.

[0185] In some embodiments, sodium metal batteries experience a loss of active sodium during use, and the cathode material exhibits good structural stability with no significant structural decay, ensuring the overall curve remains unchanged. Therefore, the degree of battery degradation can be determined by comparing the battery's current lifespan with its lifespan in a fresh state. Based on this degradation level, the battery's OCV curve can be compressed proportionally to obtain an updated OCV curve. For example, if the battery is determined to have degraded by 6%, the OCV curve can be compressed by 6% to obtain an updated OCV curve.

[0186] The OCV curve in this embodiment is the SOC-OCV curve of the battery positive electrode.

[0187] S710, based on ampere-hour integral, polarization model and updated OCV curve, determines battery SOC.

[0188] In this embodiment of the application, the battery SOC can be obtained by using the updated OCV curve and the current battery voltage.

[0189] S711. Based on the updated OCV curve, determine the battery SOE and SOW.

[0190] The embodiments of this application can improve the accuracy of SOH prediction, provide early warning of OCV / SOE / SOW and other information, and improve the safety of battery products.

[0191] In some embodiments, when one or more mutation points can be found at the positive electrode, if multiple mutation points are within the warranty period, multiple judgments need to be made on multiple inflection points. Figure 8 This is a schematic diagram of the SOC-OCV curve of a metal battery with multiple anomaly points provided in an embodiment of this application, as shown below. Figure 8 As shown, there are multiple inflection points in the low SOC stage, such as X1, X2, and X3. The inflection point voltage is determined after multiple battery cycles. The existence of multiple inflection points leads to multiple steep slope segments, and SOH can be predicted based on the different inflection point conditions using the method described above.

[0192] Based on the foregoing embodiments, this application provides a battery state prediction device, which includes various units and modules included in each unit. It can be implemented by a processor in a computer device; of course, it can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0193] Figure 9 This is a schematic diagram of the composition structure of a battery state prediction device provided in an embodiment of this application, as shown below. Figure 9 As shown, the battery state prediction device 900 includes: an acquisition module 910, a first determination module 920, a second determination module 930, a correction module 940, and a prediction module 950, wherein:

[0194] The module 910 is used to acquire the current discharge voltage and charge / discharge information of the battery in response to a voltage change condition. The first determination module 920 is used to determine the discharge capacity of the battery based on the current discharge voltage and the charge / discharge information. The second determination module 930 is used to determine the health status of the battery based on the discharge capacity and the initial rated capacity of the battery. The correction module 940 is used to correct the thermodynamic characteristic curve of the battery based on its health status to obtain a corrected thermodynamic characteristic curve. The prediction module 950 is used to predict the current battery state based on the current discharge voltage and the corrected thermodynamic characteristic curve.

[0195] In some embodiments, the battery charge / discharge information includes at least the full charge cutoff voltage and the full discharge cutoff voltage of the battery; the first determining module 920 is further configured to, in response to the battery charge / discharge information indicating that the battery meets the charge / discharge conditions, determine the discharge capacity of the battery based on at least one of the full charge cutoff voltage, the full discharge cutoff voltage, and the current discharge voltage; and in response to the battery charge / discharge information indicating that the battery does not meet the charge / discharge conditions, obtain the predicted health state of the battery, and determine the discharge capacity of the battery based on the predicted health state and the battery charge / discharge information.

[0196] In some embodiments, the discharge capacity includes at least a first discharge capacity, a second discharge capacity, and a third discharge capacity; the first determining module 920 is further configured to, in response to the battery charge-discharge information indicating that the battery meets the full charge-discharge conditions, determine the discharge capacity of the battery from the full charge cutoff voltage to the discharge capacity corresponding to the full discharge cutoff voltage as the first discharge capacity of the battery; in response to the battery charge-discharge information indicating that the battery meets the full discharge conditions, determine the second discharge capacity of the battery based on the discharge capacity of the battery from the current discharge voltage to the discharge capacity corresponding to the full discharge cutoff voltage; and in response to the battery charge-discharge information indicating that the battery meets the full charge conditions, determine the capacity of the battery from the full discharge cutoff voltage to the discharge capacity corresponding to the full charge cutoff voltage as the third discharge capacity of the battery.

[0197] In some embodiments, the battery charge / discharge information further includes the battery's voltage decay cutoff point; the discharge capacity includes at least a fourth discharge capacity; the first determining module 920 is further configured to, in response to the predicted health state meeting health conditions, determine the battery's discharge capacity from the completion of charging to the voltage decay cutoff point as the battery's fourth discharge capacity; or, determine the fourth discharge capacity based on the battery's target discharge capacity from the completion of charging to the target voltage and the discharge capacity from the target voltage to the voltage decay cutoff point.

[0198] In some embodiments, the discharge capacity further includes a fifth discharge capacity; the first determining module 920 is further configured to, in response to the predicted health state not meeting the health conditions, determine the discharge capacity of the battery from the completion of charging to the predicted cutoff voltage as the fifth discharge capacity of the battery; or, determine the fifth discharge capacity based on the target discharge capacity of the battery from the completion of charging to the target voltage and the discharge capacity from the target voltage to the predicted cutoff voltage; wherein the predicted cutoff voltage is determined based on the predicted health state.

[0199] In some embodiments, the second determining module 930 is further configured to calculate the ratio between the first discharge capacity and the initial rated capacity to obtain the health status of the battery.

[0200] In some embodiments, the apparatus further includes: a first acquisition module, configured to acquire the initial discharge capacity of the battery in an initial state, from the current discharge voltage to the full discharge cutoff voltage;

[0201] Correspondingly, the second determining module 930 is also used to calculate the health status of the battery based on the second discharge capacity, the initial discharge capacity, and the initial rated capacity.

[0202] In some embodiments, the apparatus further includes: a second acquisition module, configured to acquire the current operating condition of the battery and a corresponding degradation table of the battery in response to the voltage change of the battery not meeting the change condition; wherein the degradation table is obtained based on a preset battery aging model and includes at least the simulated health state of the battery under different operating conditions; and a third determination module, configured to determine the simulated health state corresponding to the current operating condition as the health state of the battery in the degradation table.

[0203] In some embodiments, the correction module 940 further includes determining the degree of battery degradation based on the battery's health state and the battery's initial health state; and adjusting the trend of the battery's thermodynamic characteristic curve in the directions of battery capacity and voltage, respectively, based on the degree of degradation, to obtain a corrected thermodynamic characteristic curve.

[0204] In some embodiments, the prediction module 950 is further configured to predict the current capacity of the battery based on the current discharge voltage and the modified thermodynamic characteristic curve; the device further includes: a fourth determination module, configured to determine the remaining usable energy of the battery based on the current capacity of the battery and the initial rated capacity.

[0205] The descriptions of the apparatus embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. In some embodiments, the functions or modules included in the apparatus provided in this disclosure can be used to perform the methods described in the method embodiments above. For technical details not disclosed in the apparatus embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0206] It should be noted that, in the embodiments of this application, if the above-mentioned battery state prediction method is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the related technology, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware, software, or firmware, or any combination of hardware, software, and firmware.

[0207] This application provides an electronic device, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the program, it implements some or all of the steps in the above-described method.

[0208] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements some or all of the steps in the above-described method. The computer-readable storage medium can be transient or non-transient.

[0209] This application provides a computer program including computer-readable code, wherein when the computer-readable code is executed in a computer device, a processor in the computer device performs some or all of the steps in the above-described method.

[0210] This application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the above-described method. This computer program product can be implemented specifically through hardware, software, or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium; in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0211] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above steps / processes do not imply a sequential order of execution; the execution order of each step / process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above embodiments of this application are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0212] This application uses terms such as "upper," "lower," "top," "bottom," "front," "back," "inner," and "outer" to indicate orientation or positional relationships. This is only for the convenience of describing this application and is not intended to indicate or imply that the device referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation on the scope of protection of this application.

[0213] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this application depending on the specific circumstances.

[0214] It should be noted that, in this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0215] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0216] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this application may all be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the integrated unit may be implemented in hardware or in a combination of hardware and software functional units.

[0217] The above are merely embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for predicting battery state, characterized in that, The method includes: In response to the battery voltage change satisfying the change condition, the current discharge voltage and battery charge / discharge information of the battery are obtained; Based on the current discharge voltage and the battery charge / discharge information, the discharge capacity of the battery is determined; Based on the discharge capacity and the initial rated capacity of the battery, determine the health status of the battery; Based on the health status of the battery, the thermodynamic characteristic curve of the battery is corrected to obtain the corrected thermodynamic characteristic curve. Based on the current discharge voltage and the modified thermodynamic characteristic curve, the current battery state of the battery is predicted.

2. The battery state prediction method according to claim 1, characterized in that, The battery charging and discharging information includes at least the full charge cutoff voltage and the full discharge cutoff voltage of the battery; Determining the discharge capacity of the battery based on the current discharge voltage and the battery charge / discharge information includes: In response to the battery charge and discharge information indicating that the battery meets the charge and discharge conditions, the discharge capacity of the battery is determined based on at least one of the full charge cutoff voltage, the full discharge cutoff voltage and the current discharge voltage. In response to the battery charge / discharge information indicating that the battery does not meet the charge / discharge conditions, the predicted health state of the battery is obtained, and the discharge capacity of the battery is determined based on the predicted health state and the battery charge / discharge information.

3. The battery state prediction method according to claim 2, characterized in that, The discharge capacity includes at least a first discharge capacity, a second discharge capacity, and a third discharge capacity; The step of responding to the battery charge / discharge information indicating that the battery meets charge / discharge conditions, and determining the battery's discharge capacity based on at least one of the full charge cutoff voltage, full discharge cutoff voltage, and the current discharge voltage, includes: In response to the battery charging and discharging information indicating that the battery meets the full charge and discharge conditions, the discharge capacity of the battery from the full charge cutoff voltage to the discharge cutoff voltage is determined as the first discharge capacity of the battery. In response to the battery charging and discharging information indicating that the battery meets the full discharge condition, the second discharge capacity of the battery is determined based on the discharge capacity corresponding to the discharge from the current discharge voltage to the full discharge cutoff voltage. In response to the battery charging and discharging information indicating that the battery meets the full charge condition, the capacity of the battery charged from the full discharge cutoff voltage to the capacity corresponding to the full charge cutoff voltage is determined as the third discharge capacity of the battery.

4. The battery state prediction method according to claim 2, characterized in that, The battery charge / discharge information also includes the battery's voltage decay cutoff point; the discharge capacity includes at least a fourth discharge capacity; determining the battery's discharge capacity based on the predicted health status and the battery charge / discharge information includes: In response to the predicted health state meeting the health conditions, the discharge capacity of the battery from the completion of charging to the voltage decay cutoff point is determined as the fourth discharge capacity of the battery; or, The fourth discharge capacity is determined based on the target discharge capacity of the battery from the completion of charging to the target voltage, and the discharge capacity from the target voltage to the voltage decay cutoff point.

5. The battery state prediction method according to claim 4, characterized in that, The discharge capacity further includes a fifth discharge capacity; the method further includes: In response to the predicted health state not meeting the health conditions, the discharge capacity of the battery from the completion of charging to the predicted cutoff voltage is determined as the fifth discharge capacity of the battery; or, The fifth discharge capacity is determined based on the target discharge capacity of the battery from the completion of charging to the target voltage, and the discharge capacity from the target voltage to the predicted cutoff voltage; wherein the predicted cutoff voltage is determined based on the predicted health state.

6. The battery state prediction method according to claim 3, characterized in that, Determining the health status of the battery based on the discharge capacity and the initial rated capacity of the battery includes: The health status of the battery is obtained by calculating the ratio between the first discharge capacity and the initial rated capacity.

7. The battery state prediction method according to claim 3, characterized in that, The method further includes: Obtain the initial discharge capacity of the battery in its initial state, from the current discharge voltage to the full discharge cutoff voltage. Correspondingly, determining the health status of the battery based on the discharge capacity and the battery's initial rated capacity includes: The health status of the battery is calculated based on the second discharge capacity, the initial discharge capacity, and the initial rated capacity.

8. The battery state prediction method according to any one of claims 1 to 7, characterized in that, The method further includes: In response to the battery voltage change not meeting the change condition, the current operating condition of the battery and the corresponding degradation table of the battery are obtained; wherein, the degradation table is obtained based on a preset battery aging model and includes at least the simulated health state of the battery under different operating conditions; In the attenuation table, the simulated health state corresponding to the current operating condition is determined as the health state of the battery.

9. The battery state prediction method according to any one of claims 1 to 8, characterized in that, The process of correcting the thermodynamic characteristic curve of the battery based on its health state to obtain a corrected thermodynamic characteristic curve includes: The degree of battery degradation is determined based on the battery's health status and its initial health status. Based on the degree of attenuation, the trend of the thermodynamic characteristic curve of the battery is adjusted in the directions of battery capacity and voltage, respectively, to obtain a modified thermodynamic characteristic curve.

10. The battery state prediction method according to any one of claims 1 to 9, characterized in that, The prediction of the current battery state based on the current discharge voltage and the corrected thermodynamic characteristic curve includes: Based on the current discharge voltage and the corrected thermodynamic characteristic curve, the current capacity of the battery is predicted; Correspondingly, the method further includes: Based on the battery's current capacity and its initial rated capacity, determine the remaining usable energy of the battery.

11. A battery state prediction device, characterized in that, The device includes: The acquisition module is used to acquire the current discharge voltage and battery charge / discharge information of the battery in response to the battery voltage change meeting the change condition; The first determining module is used to determine the discharge capacity of the battery based on the current discharge voltage and the battery charge / discharge information; The second determining module is used to determine the health status of the battery based on the discharge capacity and the initial rated capacity of the battery; The correction module is used to correct the thermodynamic characteristic curve of the battery based on the health state of the battery, so as to obtain the corrected thermodynamic characteristic curve. The prediction module is used to predict the current battery state of the battery based on the current discharge voltage and the modified thermodynamic characteristic curve.

12. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the battery state prediction method according to any one of claims 1 to 10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the battery state prediction method according to any one of claims 1 to 10.

14. A computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by the processor, they implement the steps in the battery state prediction method according to any one of claims 1 to 10.

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