Battery expansion force determination method and device, storage medium, electronic device and program product

Abstract

The invention discloses a battery expansion force determination method and device, a storage medium, an electronic device and a program product, and relates to the technical field of battery expansion force prediction.The battery expansion force determination method comprises the steps that index data corresponding to battery expansion force calculation indexes are obtained from battery operation data, the battery expansion force calculation indexes at least comprise a battery state of health (SOH) index, a temperature index of a cyclic aging process and a temperature index of a storage aging process, and the index data at least comprise first index data of the SOH index, second index data of the temperature index of the cyclic aging process and third index data of the temperature index of the storage aging process; the first index data, the second index data and the third index data are calculated through the expansion force prediction model, the predicted battery expansion force is obtained, the technical problem that the battery reliability is not high due to the fact that the battery expansion force cannot be effectively evaluated is solved, effective evaluation of the battery expansion force is achieved, and then the battery reliability is improved.

Description

Technical Field

[0001] This application relates to the field of battery expansion force prediction technology, and more specifically, to a method, apparatus, storage medium, electronic device, and program product for determining battery expansion force. Background Technology

[0002] Currently, with the rapid development of lithium battery technology, monitoring battery expansion force under different operating conditions has become crucial for ensuring battery safety and extending its lifespan. Traditional monitoring methods, such as physical contact measurement and optical image analysis, can only meet basic monitoring needs for battery expansion force and cannot effectively observe it in complex scenarios. For example, when facing alternating operating conditions with large temperature fluctuations or frequent changes in state of charge, batteries often need to operate under extreme temperature changes and rapid state of charge transitions. This leads to significant changes in the rate and properties of internal chemical reactions, making battery expansion force difficult to monitor. Furthermore, these traditional measurement methods have long testing cycles, are highly dependent on environmental conditions, and provide limited monitoring data, failing to effectively assess battery expansion force under complex operating conditions and affecting battery reliability. Therefore, related technologies suffer from the technical problem of low battery reliability due to the inability to effectively assess battery expansion force.

[0003] No effective solution has yet been proposed to address the technical problem of low battery reliability caused by the inability to effectively assess battery expansion force in related technologies. Summary of the Invention

[0004] This application provides a method, apparatus, storage medium, electronic device, and program product for determining battery expansion force, in order to at least solve the technical problem in the related art that the inability to effectively assess battery expansion force leads to low battery reliability.

[0005] According to one embodiment of this application, a method for determining battery expansion force is provided, comprising: obtaining index data corresponding to battery expansion force calculation indicators from battery operating data; wherein, the battery expansion force calculation indicators include at least: battery state of health (SOH) index, temperature index of the cycle aging process, and temperature index of the storage aging process, and the index data includes at least first index data of the SOH index, second index data of the temperature index of the cycle aging process, and third index data of the temperature index of the storage aging process; and calculating the first index data, the second index data, and the third index data using an expansion force prediction model to obtain a predicted battery expansion force.

[0006] In an exemplary embodiment, the predicted battery expansion force is obtained by calculating the first index data, the second index data, and the third index data using an expansion force prediction model, including: determining a calculation function corresponding to the expansion force prediction model, wherein the calculation function includes at least a first sub-function corresponding to the SOH index, a second sub-function of the temperature index of the cycle aging process, and a third sub-function of the temperature index of the storage aging process; and calculating the predicted battery expansion force based on the calculation function using the first index data, the second index data, and the third index data.

[0007] In an exemplary embodiment, calculating the predicted battery expansion force based on the calculation function using the first index data, the second index data, and the third index data includes: substituting the first index data into the first sub-function to obtain a first function value of the first sub-function; substituting the second index data into the second sub-function to obtain a second function value of the second sub-function; and substituting the third index data into the third sub-function to obtain a third function value of the third sub-function; and obtaining the predicted battery expansion force based on the first function value, the second function value, and the third function value.

[0008] In an exemplary embodiment, the second sub-function is determined based on the temperature coefficient of the cyclic aging process and the number of cycles of the cyclic aging process. The second index data is substituted into the second sub-function to obtain the second function value of the second sub-function, including: obtaining the current number of cycles from the second index data; and using the second sub-function to calculate the temperature coefficient of the cyclic aging process and the current number of cycles to obtain the second function value.

[0009] In an exemplary embodiment, the second sub-function is represented as f2 = k2 × lnc, where k2 is the temperature coefficient of the cyclic aging process and c is the current cycle number.

[0010] In an exemplary embodiment, the third sub-function is determined based on the temperature coefficient of the storage aging process and the storage time of the storage aging process. Substituting the third index data into the third sub-function to obtain the third function value of the third sub-function includes: obtaining the current storage time from the third index data; and using the third sub-function to calculate the temperature coefficient of the storage aging process and the current storage time to obtain the third function value.

[0011] In an exemplary embodiment, the third sub-function is represented as f3 = k3 × lnt, where k3 is the temperature coefficient of the storage aging process and t is the current storage time.

[0012] In an exemplary embodiment, the calculation function further includes a constant term, and the predicted battery expansion force is obtained based on the first function value, the second function value, and the third function value, including: obtaining a target constant value of the constant term from a preset constant; and obtaining the predicted battery expansion force based on the first function value, the second function value, the third function value, and the target constant value.

[0013] In an exemplary embodiment, the method further includes: obtaining historical index data of the battery expansion force calculation index at a historical temperature and historical battery expansion force at the historical temperature from historical battery operating data; using the historical battery expansion force as the historical function value of the initial function of the expansion force prediction model, substituting the historical index data into the initial function of the expansion force prediction model to obtain a set of functional equations between the initial function coefficients of the initial function and the historical temperature, wherein the initial function coefficients include the initial temperature coefficient of the cyclic aging process and the initial temperature coefficient of the storage aging process, and the set of functional equations includes: a first sub-equation between the initial temperature coefficient of the cyclic aging process and the historical temperature, and a second sub-equation between the initial temperature coefficient of the storage aging process and the historical temperature; obtaining the temperature coefficient of the cyclic aging process and the temperature coefficient of the storage aging process based on the solution results of the set of functional equations; updating the initial function based on the temperature coefficient of the cyclic aging process and the temperature coefficient of the storage aging process to obtain the calculation function.

[0014] According to another aspect of the embodiments of this application, a device for determining battery expansion force is also provided, comprising: a determining module, configured to obtain index data corresponding to battery expansion force calculation indicators from battery operating data; wherein the battery expansion force calculation indicators include at least: battery state of health (SOH) index, temperature index of the cycle aging process, and temperature index of the storage aging process, and the index data includes at least first index data of the SOH index, second index data of the temperature index of the cycle aging process, and third index data of the temperature index of the storage aging process; and a obtaining module, configured to calculate the first index data, the second index data, and the third index data using an expansion force prediction model to obtain a predicted battery expansion force.

[0015] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, and the computer program is configured to execute the above-described method for determining battery expansion force when it is run.

[0016] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described method for determining battery swelling force through the computer program.

[0017] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the above-described method for determining battery swelling force.

[0018] In this embodiment, index data corresponding to the battery expansion force calculation index is obtained from battery operating data. The battery expansion force calculation index includes at least: the State of Health (SOH) index, the temperature index of the cyclic aging process, and the temperature index of the storage aging process. The index data includes at least a first index data of the SOH index, a second index data of the temperature index of the cyclic aging process, and a third index data of the temperature index of the storage aging process. An expansion force prediction model is used to calculate the first, second, and third index data to obtain the predicted battery expansion force. The key to this embodiment is extracting the SOH index, the temperature index of the cyclic aging process, and the temperature index of the storage aging process from the battery operating data, and using the corresponding index data for prediction to obtain the predicted battery expansion force. This method, by integrating multiple indexes, can comprehensively reflect the expansion force change trend of the battery at different aging stages and temperature environments, solving the technical problem in related technologies where the inability to effectively assess battery expansion force leads to low battery reliability, thereby improving the accuracy and reliability of expansion force prediction. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram illustrating the influencing factors of battery expansion force according to an embodiment of this application;

[0022] Figure 2 This is a flowchart of a method for determining battery expansion force according to an embodiment of this application;

[0023] Figure 3This is a structural block diagram of a battery expansion force determination device according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] The following appropriately discloses an embodiment of a battery according to this application. However, unnecessary detailed descriptions may be omitted. For example, detailed descriptions of well-known matters and repetitive descriptions of practically identical structures may be omitted. This is to avoid making the following description unnecessarily lengthy and to facilitate understanding by those skilled in the art. Furthermore, the following description is provided to enable those skilled in the art to fully understand this application and is not intended to limit the subject matter of the claims.

[0027] The battery in this application is a secondary battery, also known as a rechargeable battery or storage battery, which refers to a battery that can be used again after being discharged by recharging to activate the active materials.

[0028] Typically, a secondary battery includes an electrode assembly, an electrolyte, and an outer casing. The electrode assembly consists of a positive electrode, a negative electrode, and a separator. The electrode assembly and electrolyte are assembled inside the outer casing. During charging and discharging, active ions (such as lithium ions) move back and forth between the positive and negative electrodes, inserting and extracting. The separator, positioned between the positive and negative electrodes, primarily prevents short circuits while allowing active ions to pass through. The electrolyte, located between the positive and negative electrodes, mainly serves to conduct active ions.

[0029] During the lifespan of a lithium battery, the formation and development of expansion force is a complex process, underpinned by numerous intertwined influencing mechanisms. For example... Figure 1 As shown, cell aging expansion and the battery's spatial structure are the two core factors contributing to expansion force. These factors work together within the battery to determine its safety and stability at different stages of use. Specifically, cell aging expansion can be subdivided into two types: hard expansion and soft expansion. Hard expansion is primarily driven by the relaxation effect of pre-stress, involving factors such as the compaction degree of the cell material, the initial pre-tightening force setting, and temperature changes and depth of discharge (DOD) experienced during use and aging. Soft expansion is closely related to the battery's chemical system. During charging and discharging, gases such as hydrogen, oxygen, and carbon monoxide are generated inside the cell due to electrolyte decomposition and side reactions of the positive and negative electrode materials. The accumulation of these gases leads to soft expansion. Furthermore, the battery's spatial structure (including group margin, area, and number of layers) also has a significant impact on expansion force.

[0030] This application emphasizes a method for calculating expansion force from the perspective of the influence of byproducts generated by the decay of SOH (State of Health, battery health). For details, please refer to the following content. This embodiment provides a method for determining battery expansion force. Figure 2 This is a flowchart of a method for determining battery expansion force according to an embodiment of this application. The process includes the following steps:

[0031] Step S202: Obtain the index data corresponding to the battery expansion force calculation index from the battery operation data;

[0032] The battery expansion force calculation index includes at least the following: battery health state (SOH) index, temperature index of the cycle aging process, and temperature index of the storage aging process. The index data includes at least the first index data of the SOH index, the second index data of the temperature index of the cycle aging process, and the third index data of the temperature index of the storage aging process.

[0033] Step S204: The expansion force prediction model is used to calculate the first index data, the second index data, and the third index data to obtain the predicted battery expansion force.

[0034] Through the above steps, the corresponding index data for calculating battery expansion force is obtained from battery operating data. The battery expansion force calculation index includes at least: the State of Health (SOH) index, the temperature index during cyclic aging, and the temperature index during storage aging. The index data includes at least a first index data for the SOH index, a second index data for the temperature index during cyclic aging, and a third index data for the temperature index during storage aging. An expansion force prediction model is used to calculate the first, second, and third index data to obtain the predicted battery expansion force. The key to this embodiment is extracting the SOH index, the temperature index during cyclic aging, and the temperature index during storage aging from battery operating data, and using the corresponding index data for prediction to obtain the predicted battery expansion force. This method, by integrating multiple indexes, can comprehensively reflect the expansion force change trend of the battery at different aging stages and temperature environments, solving the technical problem in related technologies where the inability to effectively assess battery expansion force leads to low battery reliability, thereby improving the accuracy and reliability of expansion force prediction.

[0035] In an exemplary embodiment, the expansion force prediction model is used to calculate the first index data, the second index data, and the third index data to obtain the predicted battery expansion force. This includes: determining the calculation function corresponding to the expansion force prediction model, wherein the calculation function includes at least a first sub-function corresponding to the SOH index, a second sub-function corresponding to the temperature index of the cycle aging process, and a third sub-function corresponding to the temperature index of the storage aging process; and calculating the first index data, the second index data, and the third index data based on the calculation function to obtain the predicted battery expansion force. This embodiment further refines the calculation process of the expansion force prediction model, defining the calculation function in detail, specifically including sub-functions corresponding to the SOH index, the temperature index of the cycle aging process, and the temperature index of the storage aging process. It accurately considers various influencing factors, transforms the calculation into a structured process, enhances the interpretability of the model itself, and improves the prediction accuracy and versatility of the model.

[0036] Furthermore, the above calculation function will be described below in conjunction with optional embodiments, but it is not intended to limit the technical solution of the embodiments of this application.

[0037] In one embodiment, the expansion force F can be expressed as:

[0038] F=f1+f2+f3=k1×f(SOH)+k2×lnc+k3×lnt+k4.

[0039] Where SOH represents the battery health status, indicating the degree of battery capacity degradation, t represents the storage time, c represents the number of cycles, k1 and k4 are constants, k2 represents the temperature coefficient of the cyclic aging process, and k3 represents the temperature coefficient of the storage aging process.

[0040] Optionally, under specified cross-conditions, such as "45℃, 100% SoC, storage for 14 days", "45℃, 0-100% SoC, step charge / 1C, cycle for 14 days", and a preload force of "0% SoC, 160 kg f", the battery is placed within a 0.66 mm silicone frame, a preset preload force is applied, and then it is stored or cycle-charged according to the set temperature and state of charge (SoC). During this period, the predicted values ​​are calculated using an expansion force prediction model, and measured expansion force data are collected through interval testing. Comparative analysis is then performed to verify the accuracy of the model, effectively evaluating the battery's expansion force performance under specific conditions and providing data support for optimizing battery design and improving safety.

[0041] Optionally, for k2 and k3, the cyclic expansion force data at different temperatures (such as 25℃, 45℃, 60℃) can be input into the above calculation function to establish temperature relationship equations (corresponding to the above function equation set), simulate the relationship between k2 and temperature and the relationship between k3 and temperature, and then solve the temperature relationship equations to obtain k2 and k3.

[0042] Alternatively, k2 and k3 can also be obtained by solving the equation that conforms to the Arrhenius formula, k2 = Ae -Ea / RT k3=Ae -Ea / RT Where A represents the pre-factor (also known as the frequency factor), Ea represents the activation energy (in J / mol or kJ / mol), which is the minimum energy required for the internal reaction of the battery to occur. R represents the ideal gas constant (e.g., 8.314 J / mol). -1 K -1 T represents temperature (in K). For example, with other data remaining constant, the relationship between k2 and temperature and the relationship between k3 and temperature are simulated using historical temperatures as variables. Then, k2 and k3 corresponding to the actual temperature are determined based on the relationships between k2 and temperature and k3 and temperature.

[0043] Optionally, in one embodiment, error correction can be performed on the predicted battery expansion force. For example, if the difference between the predicted battery expansion force and the historical battery expansion force under similar operating conditions exceeds a certain level, the temperature coefficient in the calculation function is readjusted. Specifically, for the above-mentioned expansion force prediction model, after initially calculating the predicted battery expansion force, parameters such as SOH, cycle number c, storage time t, and ambient temperature T (e.g., 45℃ / 14d / 100% SoC storage) are acquired in real time and automatically compared with the measured expansion force curves under similar operating conditions in the historical test database. If the deviation between the current predicted value (i.e., the predicted battery expansion force) and the historical measured average exceeds a certain level (e.g., ±8%), an online parameter fine-tuning action is triggered, dynamically correcting k2 and k3, thereby continuously optimizing the model's performance and enhancing its generalization ability.

[0044] Optionally, during the test data collection process, relevant SOH parameters and measured expansion forces can be collected. See Table 1 for details.

[0045] Table 1

[0046]

[0047] In an exemplary embodiment, the predicted battery expansion force is obtained by calculating the first index data, the second index data, and the third index data based on the calculation function. This includes: substituting the first index data into the first sub-function to obtain a first function value of the first sub-function; substituting the second index data into the second sub-function to obtain a second function value of the second sub-function; and substituting the third index data into the third sub-function to obtain a third function value of the third sub-function. The predicted battery expansion force is then obtained based on the first function value, the second function value, and the third function value. This embodiment describes the process of predicting expansion force using sub-functions in the calculation function. Specifically, it calculates the influence values ​​of SOH, cycle aging temperature, and storage aging temperature separately, and then combines these three function values ​​to obtain the final expansion force prediction result. This quantifies the effect of different factors on expansion force, captures the dynamic changes in expansion force during the complex aging process of the battery, and improves the accuracy of expansion force prediction.

[0048] Optionally, the first sub-function is represented as f1 = k1 × f(SOH).

[0049] Optionally, during the expansion force calculation, the collected DC internal resistance (DCIR) data can be used as an indirect characterization parameter of the byproduct accumulation level. This DCIR, along with SOH, serves as the function parameter of the first sub-function, i.e., f1 = k1 × f(SOH, DCIR). This further establishes a quantitative correlation between electrochemical aging characteristics and mechanical response, making expansion force prediction no longer dependent on a single SOH, thus improving the model accuracy of the expansion force prediction model. For example, when SOH decreases to 85% and DCIR increases by 15%, K1 can be increased accordingly to simulate the additional mechanical stress caused by the thickening of the SEI film (solid electrolyte interface film) and lithium deposition. It should be noted that the SEI film continues to grow and thicken during battery cycling. It is mainly composed of electrolyte reduction products, is brittle and hard, and expands in volume. Simultaneously, overcharging or low-temperature charging easily induces uneven deposition of lithium metal on the negative electrode surface (lithium dendrites). Both of these factors increase the local volumetric strain of the electrode material, compressing the separator and electrode layer, generating additional mechanical stress, which in turn leads to an abnormal increase in the overall expansion force of the cell, and may even induce an internal short circuit. Therefore, considering SEI thickening and lithium deposition as secondary driving factors of expansion force can more accurately reflect the mechanical evolution mechanism during battery aging.

[0050] In an exemplary embodiment, the second sub-function is determined based on the temperature coefficient of the cyclic aging process and the number of cycles in the cyclic aging process. The second index data is substituted into the second sub-function to obtain a second function value, including: obtaining the current number of cycles from the second index data; and using the second sub-function to calculate the temperature coefficient of the cyclic aging process and the current number of cycles to obtain the second function value. Furthermore, this embodiment proposes a calculation strategy that incorporates the number of cycles as a variable into the second sub-function for the cyclic aging process. This method considers the cumulative effect of the number of charge-discharge cycles on the expansion force during the battery's service life. By dynamically adjusting the temperature coefficient of the cyclic aging process, it achieves accurate simulation of the change in battery expansion force with increasing cycle count, thereby improving the prediction accuracy and applicability of the model in practical applications.

[0051] In an exemplary embodiment, the second sub-function is represented as f2 = k2 × lnc, where k2 is the temperature coefficient of the cyclic aging process and c is the current cycle number. This embodiment defines the specific form of the second sub-function in detail, using the temperature coefficient k2 and the current cycle number c to express the change law of expansion force during battery cycling. The introduction of this function enables the model to quantitatively describe the expansion force characteristics of the battery at different temperatures and cycle numbers, facilitating the safety assessment of the battery under complex operating conditions.

[0052] In an exemplary embodiment, the third sub-function is determined based on the temperature coefficient of the storage aging process and the storage time of the storage aging process. Substituting the third index data into the third sub-function yields the third function value, including: obtaining the current storage time from the third index data; and using the third sub-function to calculate the temperature coefficient of the storage aging process and the current storage time to obtain the third function value. This embodiment introduces the concept of a third sub-function, focusing on the impact of battery storage time and storage temperature on expansion force. By using the storage time t and the temperature coefficient k3 of the storage aging process as input parameters, the evolution of battery expansion force under static storage conditions can be accurately predicted.

[0053] In an exemplary embodiment, the third sub-function is expressed as f3 = k3 × lnt, where k3 is the temperature coefficient of the storage aging process and t is the current storage time. This embodiment provides a specific mathematical expression for the third sub-function, clearly illustrating the relationship between the temperature coefficient k3 of the storage aging process and the current storage time t. This provides a quantitative basis for accurately predicting the changes in the expansion force of the battery during the storage aging process, helping battery manufacturers and users to plan battery storage strategies more rationally and reduce the risk of expansion and performance loss caused by improper storage.

[0054] In an exemplary embodiment, the calculation function further includes a constant term, and the predicted battery expansion force is obtained based on the first function value, the second function value, and the third function value, including: obtaining a target constant value of the constant term from a preset constant; and obtaining the predicted battery expansion force based on the first function value, the second function value, the third function value, and the target constant value. The target constant value is, for example, k4 as described above. This embodiment further introduces the concept of a constant term as one of the additional factors affecting the expansion force. By comprehensively considering SOH, cycle aging, storage aging, and a fixed constant term, this embodiment can provide more comprehensive and detailed expansion force prediction results, improving the stability and practicality of the model. When dealing with batteries with significant individual differences, the addition of the constant term can better reflect the influence of the battery's own characteristics on the expansion force.

[0055] In an exemplary embodiment, the method further includes: obtaining historical index data of the battery expansion force calculation index at a historical temperature and historical battery expansion force at the historical temperature from historical battery operating data; using the historical battery expansion force as the historical function value of the initial function of the expansion force prediction model, substituting the historical index data into the initial function of the expansion force prediction model to obtain a set of functional equations between the initial function coefficients of the initial function and the historical temperature, wherein the initial function coefficients include the initial temperature coefficient of the cyclic aging process and the initial temperature coefficient of the storage aging process, and the set of functional equations includes: a first sub-equation between the initial temperature coefficient of the cyclic aging process and the historical temperature, and a second sub-equation between the initial temperature coefficient of the storage aging process and the historical temperature; obtaining the temperature coefficient of the cyclic aging process and the temperature coefficient of the storage aging process based on the solution results of the set of functional equations; updating the initial function based on the temperature coefficient of the cyclic aging process and the temperature coefficient of the storage aging process to obtain the calculation function.

[0056] This embodiment establishes a functional relationship between historical battery performance data and historical battery expansion force by utilizing historical battery operating data, thereby solving for the temperature coefficients of cyclic aging and storage aging processes. This method uses historical data to calibrate model parameters, which not only enhances the model's predictive ability but also effectively compensates for the limitations of experimental testing. It enables the model to accurately predict expansion force over a wider range of temperatures and aging degrees, providing strong data support for battery design optimization, lifespan assessment, and safety early warning.

[0057] Optionally, in one embodiment, for a "cross-condition" verification scenario (e.g., storing for 14 days followed by a 14-day cycle), a segmented prediction strategy for a storage-cycle composite condition is proposed, combining the following process: The storage time t1 and cycle number c1 of the battery in the previous stage are recorded. When entering the next stage, t1 and c1 are used as initial conditions input into the calculation function, instead of starting from zero. For example, if the battery first undergoes 45℃ / 14d storage (t=14) and then enters the cycle, the model uses SOH (t=14) and K3×14 as initial expansion base values, superimposed with K2×c from the cycle stage, to achieve continuous prediction of "cumulative expansion force".

[0058] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0059] Figure 3 This is a structural block diagram of a battery expansion force determination device according to an embodiment of this application; as shown... Figure 3 As shown, it includes:

[0060] The determination module 32 is used to obtain the index data corresponding to the battery expansion force calculation index from the battery operation data;

[0061] The battery expansion force calculation index includes at least the following: battery health state (SOH) index, temperature index of the cycle aging process, and temperature index of the storage aging process. The index data includes at least the first index data of the SOH index, the second index data of the temperature index of the cycle aging process, and the third index data of the temperature index of the storage aging process.

[0062] Module 34 is used to calculate the predicted battery expansion force by using the expansion force prediction model on the first index data, the second index data, and the third index data.

[0063] The aforementioned device extracts index data corresponding to the battery expansion force calculation index from battery operating data. The battery expansion force calculation index includes at least: the State of Health (SOH) index, the temperature index of the cyclic aging process, and the temperature index of the storage aging process. The index data includes at least a first index data of the SOH index, a second index data of the temperature index of the cyclic aging process, and a third index data of the temperature index of the storage aging process. An expansion force prediction model is used to calculate the first, second, and third index data to obtain the predicted battery expansion force. The key to this embodiment is extracting the SOH index, the temperature index of the cyclic aging process, and the temperature index of the storage aging process from the battery operating data, and using the corresponding index data for prediction to obtain the predicted battery expansion force. This method, by integrating multiple indexes, can comprehensively reflect the expansion force change trend of the battery at different aging stages and temperature environments, solving the technical problem in related technologies where the inability to effectively assess battery expansion force leads to low battery reliability, thereby improving the accuracy and reliability of expansion force prediction.

[0064] In an exemplary embodiment, the obtaining module is further configured to: determine a calculation function corresponding to the expansion force prediction model, wherein the calculation function includes at least a first sub-function corresponding to the SOH index, a second sub-function of the temperature index of the cycle aging process, and a third sub-function of the temperature index of the storage aging process; and calculate the predicted battery expansion force based on the calculation function using the first index data, the second index data, and the third index data.

[0065] In an exemplary embodiment, the obtaining module is further configured to: substitute the first indicator data into the first sub-function to obtain a first function value of the first sub-function, substitute the second indicator data into the second sub-function to obtain a second function value of the second sub-function, and substitute the third indicator data into the third sub-function to obtain a third function value of the third sub-function; and obtain the predicted battery expansion force based on the first function value, the second function value, and the third function value.

[0066] In an exemplary embodiment, the module, which is determined based on the temperature coefficient of the cyclic aging process and the number of cycles of the cyclic aging process, is further configured to: obtain the current number of cycles from the second index data; and use the second sub-function to calculate the temperature coefficient of the cyclic aging process and the current number of cycles to obtain the second function value.

[0067] In an exemplary embodiment, the second sub-function is represented as f2 = k2 × lnc, where k2 is the temperature coefficient of the cyclic aging process and c is the current cycle number.

[0068] In an exemplary embodiment, the module, which is determined based on the temperature coefficient of the storage aging process and the storage time of the storage aging process, is further configured to: obtain the current storage time from the third index data; and use the third sub-function to calculate the temperature coefficient of the storage aging process and the current storage time to obtain the third function value.

[0069] In an exemplary embodiment, the third sub-function is represented as f3 = k3 × lnt, where k3 is the temperature coefficient of the storage aging process and t is the current storage time.

[0070] In an exemplary embodiment, the calculation function further includes a constant term, and the obtaining module is further configured to: obtain a target constant value of the constant term from a preset constant; and obtain the predicted battery expansion force based on the first function value, the second function value, the third function value, and the target constant value.

[0071] In an exemplary embodiment, the obtaining module is further configured to: obtain historical index data of the battery expansion force calculation index at a historical temperature and historical battery expansion force at the historical temperature from historical battery operating data; use the historical battery expansion force as the historical function value of the initial function of the expansion force prediction model, substitute the historical index data into the initial function of the expansion force prediction model, and obtain a set of functional equations between the initial function coefficients of the initial function and the historical temperature, wherein the initial function coefficients include the initial temperature coefficient of the cyclic aging process and the initial temperature coefficient of the storage aging process, and the set of functional equations includes: a first sub-equation between the initial temperature coefficient of the cyclic aging process and the historical temperature, and a second sub-equation between the initial temperature coefficient of the storage aging process and the historical temperature; obtain the temperature coefficient of the cyclic aging process and the temperature coefficient of the storage aging process based on the solution results of the set of functional equations; update the initial function based on the temperature coefficient of the cyclic aging process and the temperature coefficient of the storage aging process to obtain the calculation function.

[0072] Embodiments of this application also provide a storage medium including a stored program, wherein the program executes any of the methods described above when it is run.

[0073] Optionally, in this embodiment, the storage medium may be configured to store program code for performing the following steps:

[0074] S1, Obtain the index data corresponding to the battery expansion force calculation index from the battery operation data; wherein, the battery expansion force calculation index includes at least: the battery health state (SOH) index, the temperature index of the cycle aging process and the temperature index of the storage aging process, and the index data includes at least the first index data of the SOH index, the second index data of the temperature index of the cycle aging process and the third index data of the temperature index of the storage aging process;

[0075] S2, the expansion force prediction model is used to calculate the first index data, the second index data and the third index data to obtain the predicted battery expansion force.

[0076] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0077] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0078] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0079] S1, Obtain the index data corresponding to the battery expansion force calculation index from the battery operation data; wherein, the battery expansion force calculation index includes at least: the battery health state (SOH) index, the temperature index of the cycle aging process and the temperature index of the storage aging process, and the index data includes at least the first index data of the SOH index, the second index data of the temperature index of the cycle aging process and the third index data of the temperature index of the storage aging process;

[0080] S2, the expansion force prediction model is used to calculate the first index data, the second index data and the third index data to obtain the predicted battery expansion force.

[0081] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0082] Optionally, embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0083] Optionally, embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0084] Optionally, embodiments of this application also provide a computer program, which includes computer instructions stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in any of the above method embodiments.

[0085] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0086] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuits, or multiple modules or steps can be fabricated as a single integrated circuit. Thus, this application is not limited to any particular hardware and software combination.

[0087] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining the expansion force of a battery, characterized in that, include: Obtain the index data corresponding to the battery expansion force calculation index from the battery operation data. The battery expansion force calculation index includes at least: the battery health state (SOH) index, the temperature index of the cycle aging process, and the temperature index of the storage aging process. The index data includes at least the first index data of the SOH index, the second index data of the temperature index of the cycle aging process, and the third index data of the temperature index of the storage aging process. The expansion force prediction model is used to calculate the predicted battery expansion force based on the first index data, the second index data, and the third index data.

2. The method for determining battery expansion force according to claim 1, characterized in that, The expansion force prediction model is used to calculate the predicted battery expansion force based on the first index data, the second index data, and the third index data, including: Determine the calculation function corresponding to the expansion force prediction model, wherein the calculation function includes at least a first sub-function corresponding to the SOH index, a second sub-function corresponding to the temperature index of the cyclic aging process, and a third sub-function corresponding to the temperature index of the storage aging process; The predicted battery expansion force is obtained by calculating the first index data, the second index data, and the third index data based on the calculation function.

3. The method for determining battery expansion force according to claim 2, characterized in that, The predicted battery expansion force is obtained by calculating the first index data, the second index data, and the third index data based on the calculation function, including: Substitute the first indicator data into the first sub-function to obtain the first function value of the first sub-function; substitute the second indicator data into the second sub-function to obtain the second function value of the second sub-function; and substitute the third indicator data into the third sub-function to obtain the third function value of the third sub-function. The predicted battery expansion force is obtained based on the first function value, the second function value, and the third function value.

4. The method for determining battery expansion force according to claim 3, characterized in that, The second sub-function is determined based on the temperature coefficient of the cyclic aging process and the number of cycles in the cyclic aging process. Substituting the second index data into the second sub-function yields the second function value of the second sub-function, including: Obtain the current cycle number from the second indicator data; The second sub-function is used to calculate the temperature coefficient of the cyclic aging process and the current number of cycles to obtain the value of the second function.

5. The method for determining battery expansion force according to claim 4, characterized in that, The second sub-function is expressed as f2=k2×lnc, where k2 is the temperature coefficient of the cyclic aging process and c is the current cycle number.

6. The method for determining battery expansion force according to claim 3, characterized in that, The third sub-function is determined based on the temperature coefficient and storage time of the storage aging process. Substituting the third indicator data into the third sub-function yields the third function value, including: Obtain the current storage time from the third indicator data; The third sub-function is used to calculate the temperature coefficient of the storage aging process and the current storage time to obtain the value of the third function.

7. The method for determining battery expansion force according to claim 6, characterized in that, The third sub-function is represented as f3 = k3 × lnt, where k3 is the temperature coefficient of the storage aging process and t is the current storage time.

8. The method for determining battery expansion force according to claim 3, characterized in that, The calculation function further includes a constant term, and the predicted battery expansion force is obtained based on the first function value, the second function value, and the third function value, including: Obtain the target constant value of the constant term from the preset constant; The predicted battery expansion force is obtained based on the first function value, the second function value, the third function value, and the target constant value.

9. The method for determining battery expansion force according to claim 2, characterized in that, The method further includes: Obtain historical index data of the battery expansion force calculation index at historical temperatures from the battery's historical operating data, as well as the historical battery expansion force at the historical temperatures. Using the historical battery expansion force as the historical function value of the initial function of the expansion force prediction model, the historical index data is substituted into the initial function of the expansion force prediction model to obtain a set of functional equations between the initial function coefficients of the initial function and the historical temperature. The initial function coefficients include the initial temperature coefficients of the cyclic aging process and the initial temperature coefficients of the storage aging process. The set of functional equations includes: a first sub-equation between the initial temperature coefficient of the cyclic aging process and the historical temperature, and a second sub-equation between the initial temperature coefficient of the storage aging process and the historical temperature. The temperature coefficients of the cyclic aging process and the storage aging process are obtained from the solution of the set of functional equations. The initial function is updated based on the temperature coefficients of the cyclic aging process and the storage aging process to obtain the calculation function.

10. A device for determining the expansion force of a battery, characterized in that, include: The determination module is used to obtain the index data corresponding to the battery expansion force calculation index from the battery operation data; wherein, the battery expansion force calculation index includes at least: the battery health state (SOH) index, the temperature index of the cycle aging process and the temperature index of the storage aging process, and the index data includes at least the first index data of the SOH index, the second index data of the temperature index of the cycle aging process and the third index data of the temperature index of the storage aging process; The module is used to calculate the predicted battery expansion force by using the expansion force prediction model on the first index data, the second index data, and the third index data.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method according to any one of claims 1 to 9.

12. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method described in any one of claims 1 to 9 through the computer program.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1 to 9.

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