Solid-state battery management method and device, electronic equipment and storage medium

Abstract

The invention provides a solid-state battery management method and device, electronic equipment and a storage medium, and relates to the technical field of solid-state batteries. The method comprises the following steps: applying a preset excitation signal to the solid-state battery, and determining interface impedance response data of the solid-state battery under the preset excitation signal; and determining the dendritic crystal growth risk level of the solid-state battery according to the interface impedance response data. The dendritic crystal growth risk level is determined by applying the preset excitation signal and collecting the interface impedance response data of the solid-state battery, so that the dendritic crystal risk of the solid-state battery is effectively monitored in real time, real-time monitoring and grading identification of the dendritic crystal risk are achieved, early warning can be conducted in time at the early stage of dendritic crystals, short circuit and thermal runaway caused by extension of the dendritic crystals are avoided, and the service life of the solid-state battery is prolonged. And the running safety and reliability of the solid-state battery are improved.

Description

Technical Field

[0001] This invention relates to the field of solid-state battery technology, and more specifically, to a solid-state battery management method and apparatus, electronic device, and storage medium. Background Technology

[0002] With the development of electric vehicles, energy storage systems, and other fields, solid-state batteries have gradually attracted attention due to their high safety and high energy density. However, solid-state batteries still face the risk of dendrite formation and propagation during charging and discharging. Once dendrites penetrate the electrodes and solid electrolyte, they may cause internal short circuits and thermal runaway, becoming a key issue restricting the reliability and safety of solid-state batteries.

[0003] Currently, battery management systems in related technologies mainly rely on macroscopic parameters such as terminal voltage and temperature to assess battery status. However, these signals often lag behind the actual dendrite growth process, making it difficult to identify risks during the dendrite initiation stage in a timely manner. This results in solid-state batteries often only being detected when dendrites have developed to a relatively severe stage in practical applications, leading to missed opportunities for early intervention and increasing the probability of battery failure and safety accidents. Therefore, to improve the operational safety and reliability of solid-state batteries, there is an urgent need for an effective means to monitor dendrite risks in solid-state batteries in real time. Summary of the Invention

[0004] The problem addressed by this invention is: how to monitor dendrite risk in solid-state batteries in real time and effectively.

[0005] To address the aforementioned problems, this invention provides a solid-state battery management method and apparatus, an electronic device, and a storage medium.

[0006] In a first aspect, the present invention provides a solid-state battery management method, comprising: A preset excitation signal is applied to a solid-state battery, and the interface impedance response data of the solid-state battery under the preset excitation signal is determined; Based on the interface impedance response data, the dendrite growth risk level of the solid-state battery is determined.

[0007] Optionally, the preset excitation signal includes a first excitation signal for detecting changes in ohmic impedance, a second excitation signal for detecting changes in charge transfer impedance, and a third excitation signal for detecting changes in diffusion impedance; wherein the first excitation signal, the second excitation signal, and the third excitation signal are AC signals with different frequencies. The step of applying a preset excitation signal to the solid-state battery and determining the interface impedance response data of the solid-state battery under the preset excitation signal includes: The first excitation signal, the second excitation signal, and the third excitation signal are applied to the solid-state battery respectively. The first interface impedance response data of the solid-state battery under the first excitation signal is determined, the second interface impedance response data of the solid-state battery under the second excitation signal is determined, and the third interface impedance response data of the solid-state battery under the third excitation signal is determined.

[0008] Optionally, determining the dendrite growth risk level of the solid-state battery based on the interface impedance response data includes: If the first interface impedance response data does not meet the first preset impedance change condition, the dendrite growth risk level is determined to be no dendrite risk. If the first interface impedance response data meets the first preset impedance change condition, and the second interface impedance response data and the third interface impedance response data meet the second preset impedance change condition, the dendrite growth risk level is determined to be the initial dendrite growth risk.

[0009] Optionally, the first preset impedance change condition includes: The first interface impedance response data contains adjacent sampled data where the impedance change rate is greater than a first preset change rate threshold; wherein, the first preset change rate threshold is determined based on the temperature of the solid-state battery within a preset pressure range; And / or, the second preset impedance change condition includes: The second interface impedance response data contains adjacent sampled data where the impedance change rate is greater than the second preset change rate threshold, and the impedance curve obtained by fitting the third interface impedance response data has an interval where the slope is greater than the preset slope threshold; wherein, the second preset change rate threshold and / or the preset slope threshold are determined based on the temperature of the solid-state battery within a preset pressure range.

[0010] Optionally, after determining the dendrite growth risk level of the solid-state battery, the solid-state battery management method further includes: In response to the dendrite growth risk level of the solid-state battery being at the initial dendrite growth risk level, a preset clamping force is applied to the solid-state battery to adjust the interfacial contact state between the electrodes and the solid electrolyte of the solid-state battery.

[0011] Optionally, the solid-state battery comprises multiple stacked battery cells; the step of applying a preset excitation signal to the solid-state battery and determining the interface impedance response data of the solid-state battery under the preset excitation signal includes: A preset excitation signal is applied to each of the battery cells, and the interface impedance response data of each battery cell under the preset excitation signal is determined. The step of determining the dendrite growth risk level of the solid-state battery based on the interface impedance response data includes: Based on the interface impedance response data, the dendrite growth risk level of each of the battery cells is determined.

[0012] Optionally, in response to the dendrite growth risk level of the solid-state battery being the initial dendrite growth risk, applying a preset clamping force to the solid-state battery to adjust the interfacial contact state between the electrodes and the solid electrolyte includes: In response to the dendrite growth risk level of at least one of the cell cells of the solid-state battery being in the early stage of dendrite growth, the preset clamping force is applied to the solid-state battery.

[0013] In a second aspect, the present invention provides a solid-state battery management device, comprising: An excitation response module is used to apply a preset excitation signal to a solid-state battery and determine the interface impedance response data of the solid-state battery under the preset excitation signal. The risk assessment module is used to determine the dendrite growth risk level of the solid-state battery based on the interface impedance response data.

[0014] Thirdly, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the solid-state battery management method as described in the first aspect when executing the computer program.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that is read and executed by a processor to implement the solid-state battery management method as described in the first aspect.

[0016] The beneficial effects of the solid-state battery management method, apparatus, electronic device, and storage medium of the present invention are as follows: By applying a preset excitation signal and collecting the interface impedance response data of the solid-state battery under this signal, the present invention determines the current dendrite growth risk level of the solid-state battery. This enables real-time and effective monitoring of dendrite risk in solid-state batteries, allowing for timely identification and warning of the risk when dendrites are in the early stages of growth. This provides a reliable triggering basis for taking corresponding countermeasures, effectively preventing further dendrite expansion that could lead to short circuits and thermal runaway problems caused by dendrites penetrating the electrode and solid electrolyte. Therefore, the present invention not only significantly improves the safety and reliability of solid-state batteries during operation but also enhances the timeliness and convenience of maintenance (or troubleshooting), thereby extending the service life of solid-state batteries, reducing their operating costs, and providing a guarantee for the large-scale promotion and application of solid-state batteries. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a solid-state battery management method according to an embodiment of the present invention; Figure 2 This is a structural block diagram of the solid-state battery management device in an embodiment of the present invention; Figure 3 This is a schematic diagram of the communication connection between the memory and processor of an electronic device in an embodiment of the present invention. Detailed Implementation

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0019] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0020] Combination Figure 1 As shown, this embodiment of the invention provides a solid-state battery management method, including: Step 100: Apply a preset excitation signal to the solid-state battery and determine the interface impedance response data of the solid-state battery under the preset excitation signal.

[0021] Considering that the main hazard of dendrite growth lies in its penetration of the electrode and solid electrolyte, leading to internal short circuits and thermal runaway in solid-state batteries, and that dendrite growth most easily initiates at the solid-solid contact interface formed between the electrode and the solid electrolyte, this embodiment's method monitors the interface impedance of the solid-solid contact interface in real time to determine the current dendrite growth risk level of the solid-state battery. This enables real-time monitoring of the dendrite risk and timely detection of its changes (such as from no dendrite risk to early dendrite growth risk), allowing for timely implementation of appropriate countermeasures to ensure the safety and reliability of solid-state battery operation.

[0022] Specifically, in step 100, to accurately obtain the interface impedance of the solid-state battery, an excitation signal (such as an AC excitation signal of a corresponding frequency) can be applied to the solid-state battery, and the interface impedance data of the solid-state battery under the excitation signal can be collected in real time (denoted as interface impedance response data). The interface impedance response data can be obtained by performing amplitude and phase analysis on the voltage response and current response under the applied excitation signal.

[0023] Thus, the method of this embodiment can reflect the interface impedance in real time and accurately without disassembling the battery or performing destructive sampling. It can also realize online non-destructive testing of the solid-solid interface impedance of solid-state batteries. For example, by applying a preset excitation signal with a small amplitude, the signal will not significantly interfere with the charging and discharging process of the solid-state battery. Therefore, the interface impedance parameters can be collected and analyzed during the normal operation of the solid-state battery, thereby realizing online non-destructive testing, ensuring the continuity and stability of the testing process, as well as the accuracy of the testing results, and providing reliable data support for dendrite risk identification.

[0024] Step 200: Determine the dendrite growth risk level of the solid-state battery based on the interface impedance response data.

[0025] Specifically, in step 200, based on the interface impedance response data of the solid-state battery under a preset excitation signal obtained in step 100, the dendrite risk level of the solid-state battery (such as no dendrite risk transition, early dendrite growth risk, etc.) is determined by at least one judgment method. For example, a threshold comparison judgment method is used, comparing the real-time acquired interface impedance response data (such as interface impedance response data under a specific frequency excitation signal) with a preset corresponding risk threshold, and directly determining the corresponding dendrite growth risk level based on the preset numerical range it falls into (i.e., different preset numerical ranges correspond to different dendrite growth risk levels); or a mapping table lookup method is used, pre-establishing a database containing the correspondence between different interface impedance response data and dendrite risk levels through experiments, and by matching the real-time acquired interface impedance response data in this database, the closest risk level judgment can be obtained, thus determining the dendrite growth risk level of the solid-state battery; or an intelligent model judgment method is used, such as comparing the real-time acquired interface impedance response data... The data is input into a pre-trained dendrite risk classification model, which outputs a probability distribution or direct classification result of the dendrite growth risk level to determine the dendrite growth risk level (e.g., determining the risk level corresponding to the highest probability in the probability distribution as the current dendrite growth risk level of the solid-state battery, or determining the risk level corresponding to the direct classification result as the current dendrite growth risk level of the solid-state battery); or by combining one or more of the above determination methods, a comprehensive determination of the dendrite growth risk level of the solid-state battery can be achieved, avoiding misjudgments or omissions caused by a single determination method being limited by specific operating conditions, measurement noise, or parameter fluctuations. Furthermore, through cross-validation and fusion of multi-source determination results, the robustness and accuracy of dendrite risk identification can be effectively improved; and so on. In this way, the method enables real-time, hierarchical, and flexible identification of dendrite growth risk (or degree of dendrite growth) in solid-state batteries. Compared with the lagging judgment based solely on changes in terminal voltage or capacity, the method in this embodiment can provide early warning when dendrites in solid-state batteries are still in the early stages of growth. This provides early triggering conditions and data support for taking corresponding countermeasures, significantly improving the operational safety and reliability of solid-state batteries and effectively reducing the probability of dendrite-induced short circuits in solid-state batteries.

[0026] In summary, the method of this embodiment applies a preset excitation signal and collects the interface impedance response data of the solid-state battery under this signal. Based on this, it determines the current dendrite growth risk level of the solid-state battery, enabling real-time and effective monitoring of dendrite risk. This allows for timely identification and warning of the risk when dendrites are in the early stages of growth, providing a reliable trigger for appropriate countermeasures and effectively preventing further dendrite expansion that could lead to short circuits and thermal runaway through the electrodes and solid electrolyte. Therefore, this method not only significantly improves the safety and reliability of solid-state batteries during operation but also enhances the timeliness and convenience of maintenance (or troubleshooting), thereby extending the lifespan of solid-state batteries, reducing their operating costs, and ensuring their large-scale application.

[0027] Optionally, the preset excitation signals include a first excitation signal for detecting changes in ohmic impedance, a second excitation signal for detecting changes in charge transfer impedance, and a third excitation signal for detecting changes in diffusion impedance; wherein the first excitation signal, the second excitation signal, and the third excitation signal are AC signals with different frequencies. Applying a preset excitation signal to a solid-state battery and determining the interface impedance response data of the solid-state battery under the preset excitation signal includes: A first excitation signal, a second excitation signal, and a third excitation signal are applied to the solid-state battery respectively. The first interface impedance response data of the solid-state battery under the first excitation signal, the second interface impedance response data of the solid-state battery under the second excitation signal, and the third interface impedance response data of the solid-state battery under the third excitation signal are determined.

[0028] Specifically, the preset excitation signals include a first excitation signal for detecting changes in the ohmic impedance of the solid-state battery, a second excitation signal for detecting changes in the charge transfer impedance of the solid-state battery, and a third excitation signal for detecting changes in the diffusion impedance of the solid-state battery. The first, second, and third excitation signals are AC signals with different frequencies. Ohmic impedance primarily reflects the resistance characteristics generated by the internal conductors, electrolyte, and solid-solid interface contact within the solid-state battery. Its changes can directly indicate the interface contact state and the impact of dendrite growth on the interface pathway. Charge transfer impedance reflects the electrochemical reaction rate at the electrode-solid electrolyte interface. When dendrite growth is present and accompanied by dead zone deposition, this impedance will increase significantly. Diffusion impedance reflects the ease with which migratable ions (such as lithium ions) transport and diffuse between the electrode and electrolyte. When dendrites disrupt electrode uniformity or block ion channels, the slope of the diffusion impedance curve will increase significantly. For example, the frequencies of the first excitation signal, the second excitation signal, and the third excitation signal decrease sequentially. For instance, the first excitation signal (corresponding to high frequency) may be an AC signal with a frequency of approximately 10 kHz, the second excitation signal (corresponding to intermediate frequency) may be an AC signal with a frequency of approximately 1 kHz, and the third excitation signal (corresponding to low frequency) may be an AC signal with a frequency of approximately 1 Hz.

[0029] In step 100, a first excitation signal, a second excitation signal, and a third excitation signal can be applied to the solid-state battery respectively. The interface impedance response data of the solid-state battery under different excitation signals is collected in real time by the corresponding sensors built into the solid-state battery. The first interface impedance response data of the solid-state battery under the first excitation signal, the second interface impedance response data under the second excitation signal, and the third interface impedance response data under the third excitation signal are obtained. These data can be used to refine the interface state of the solid-state battery from different levels, realize multi-dimensional identification and comprehensive judgment of dendrite risk, avoid misjudgment or omission due to unilateral detection error, thereby significantly improving the accuracy and reliability of dendrite risk identification and providing more scientific and robust data support for subsequent early warning and protection measures. In some embodiments, an impedance spectrum (i.e., a set of impedance characteristics obtained under different frequency excitations, used to comprehensively characterize the frequency response characteristics of the electrochemical process at the interface of a solid-state battery) can be formed based on the first interface impedance response data, the second interface impedance response data, and the third interface impedance response data. This allows the changes in ohmic impedance, charge transfer impedance, and diffusion impedance to be presented intuitively in a single curve. By fitting and analyzing the impedance spectrum, not only can the impedance components corresponding to different physical processes be identified, but also their trends of change with time or operating conditions can be identified, thereby achieving refined modeling and dynamic monitoring of the interface state of the solid-state battery.

[0030] Optionally, the acquisition (collection) of interface impedance response data can be achieved using an EIS (Electrochemical Impedance Spectroscopy) sensor installed within the solid-state battery. For example, based on a preset excitation signal applied to the solid-state battery, the voltage and current responses of the solid-state battery under this excitation signal are simultaneously acquired by the EIS sensor, and then the corresponding interface impedance response data (or impedance spectrum) is calculated through amplitude and phase analysis. Thus, by integrating an EIS sensor inside the battery, interference from external test wiring can be avoided, enabling real-time, online acquisition of interface impedance parameters, thereby improving the accuracy and stability of the data and providing a guarantee for the rapid identification and reliable determination of dendrite risk.

[0031] Optionally, the dendrite growth risk level of the solid-state battery can be determined based on the interface impedance response data, including: If the first interface impedance response data does not meet the first preset impedance change condition, the dendrite growth risk level is determined to be no dendrite risk. If the impedance response data of the first interface meets the first preset impedance change condition, and the impedance response data of the second interface and the impedance response data of the third interface meet the second preset impedance change condition, the dendrite growth risk level is determined to be the initial dendrite growth risk.

[0032] Specifically, when determining the dendrite growth risk level of a solid-state battery based on interface impedance response data, the system first checks whether the first interface impedance response data meets the first preset impedance change condition (e.g., the rate of change of impedance corresponding to adjacent sampling points in the first interface impedance response data is greater than the first preset rate of change threshold). If this condition is not met, it indicates that the ohmic impedance of the solid-state battery at high-frequency characteristic frequencies has not undergone significant abrupt changes, and the interface contact state remains stable, thus determining the current dendrite growth risk level as no dendrite risk. If the condition is met, the system can further combine the second and third interface impedance response data for comprehensive verification to determine whether the second and third interface impedance response data meet the second preset impedance change condition (e.g., the rate of change of impedance corresponding to adjacent sampling points in the second interface impedance response data exceeds the second preset rate of change threshold, and the impedance curve fitted based on the third interface impedance response data has a slope greater than the preset slope threshold). This allows the system to determine whether the charge transfer impedance and diffusion impedance simultaneously exhibit abnormal changes, thereby comprehensively determining whether the solid-state battery has entered the initial dendrite growth risk state. In this way, dendrite risk can be accurately identified at the initial dendrite growth stage, avoiding misjudgments or omissions caused by single impedance data.

[0033] The first preset rate of change threshold, the second preset rate of change threshold, and the preset slope threshold can be determined according to actual needs or according to the design parameters of the solid-state battery, the current operating status, the operating environment parameters, etc., to ensure the flexibility and applicability of risk assessment.

[0034] Optionally, determining the dendrite growth risk level of a solid-state battery based on interface impedance response data further includes: if the first interface impedance response data meets the first preset impedance change condition, and the second and third interface impedance response data do not meet the second preset impedance change condition, the solid-state battery is determined to be in a suspected dendrite state and enters a continuous monitoring mode. In the continuous monitoring mode, the changing trend of the solid-state battery's interface impedance continues to be acquired in real time. If, during subsequent monitoring, the second and third interface impedance response data are determined to meet the second preset impedance change condition, the determination is updated to an initial dendrite growth risk; however, if the second and third interface impedance response data still do not meet the second preset impedance change condition after multiple sampling cycles, the determination can be re-established as a no-dendrite-risk state. Thus, by introducing a suspected dendrite state and a continuous monitoring mode, misjudgments caused by instantaneous fluctuations or measurement noise can be avoided, improving the robustness and accuracy of risk identification, thereby making solid-state battery dendrite monitoring more reliable and practical for engineering applications.

[0035] Optionally, when determining the dendrite growth risk level of a solid-state battery based on the corresponding interface impedance response data and corresponding judgment conditions (such as the aforementioned preset impedance change conditions), the specific implementation of the corresponding judgment conditions can be flexibly defined and implemented based on various judgment methods, such as the threshold comparison judgment method, the mapping table lookup method, or the intelligent model judgment method. For example, when using the threshold comparison judgment method, the corresponding judgment conditions are specified as one or more quantified comparison rules, which determine the interval of the interface impedance response data and its corresponding dendrite growth risk level through comparison; when using the mapping table lookup method, the core logic of the corresponding judgment conditions is integrated and instantiated into the preset interface impedance response data-dendrite risk level correspondence in the database; when using the intelligent model judgment method, the complex logical judgment process based on the corresponding judgment conditions is inherently carried and executed by a pre-trained dendrite risk classification model; and so on.

[0036] Optionally, the first preset impedance change condition includes: there are adjacent sampled data in the first interface impedance response data where the impedance change rate is greater than the first preset change rate threshold; wherein, the first preset change rate threshold is determined based on the temperature of the solid-state battery within a preset pressure range.

[0037] Specifically, considering the significant impact of dendrite growth on the ohmic impedance of solid-state batteries, the first preset impedance change condition can be set as follows: there exists adjacent sampled data in the first interface impedance response data where the impedance change rate is greater than the first preset change rate threshold. That is, there exists adjacent sampled points in the first interface impedance response data where the impedance change rate is greater than the first preset change rate threshold. The impedance change rate of adjacent sampled data is (Z1-Z2) / Z2, where Z1 is the impedance value corresponding to the later sampled point in the adjacent sampled data, and Z2 is the impedance value corresponding to the earlier sampled point in the adjacent sampled data. For the acquired first interface impedance response data, the impedance values ​​corresponding to all adjacent sampled points are compared. If the calculated impedance change rate exceeds the set first preset change rate threshold, it is considered that an abnormal change has occurred at the high-frequency characteristic frequency (corresponding to the first excitation signal), and the first interface impedance response data satisfies the first preset impedance change condition. However, if the calculated impedance change rate of all adjacent sampled points is less than or equal to the first preset change rate threshold, the first interface impedance response data does not satisfy the first preset impedance change condition.

[0038] In this context, considering that the interface impedance of solid-state batteries is significantly affected by pressure and temperature—for example, when the solid-state battery pressure is within a preset pressure range (such as the normal pressure range, i.e., the set pressure range for normal operation of the solid-state battery)—the impedance typically decreases with increasing temperature and may increase with decreasing temperature. Therefore, the first preset rate of change threshold can be determined based on the temperature of the solid-state battery within the preset pressure range. For example, within the preset pressure range, there are preset values ​​for the first preset rate of change threshold corresponding to different temperatures. This allows for rapid acquisition and dynamic adjustment of the first preset rate of change threshold during practical applications, avoiding the complexity of real-time calculations, improving the efficiency and stability of solid-state battery assessment under different operating conditions, and thus ensuring the timeliness and accuracy of dendrite risk identification.

[0039] The pressure and temperature of solid-state batteries can be monitored in real time by setting up appropriate pressure and temperature sensors.

[0040] Optionally, the second preset impedance change condition includes: The second interface impedance response data contains adjacent sampled data where the impedance change rate is greater than the second preset change rate threshold, and the impedance curve obtained by fitting the third interface impedance response data has an interval where the slope is greater than the preset slope threshold; wherein, the second preset change rate threshold and / or the preset slope threshold are determined based on the temperature of the solid-state battery within the preset pressure range.

[0041] Specifically, considering the impact of dendrite growth on the charge transfer impedance and diffusion impedance of solid-state batteries, the second preset impedance change condition can be set as follows: there are adjacent sampled data in the second interface impedance response data where the impedance change rate is greater than the second preset change rate threshold, and the impedance curve fitted based on the third interface impedance response data has an interval where the slope is greater than the preset slope threshold. Based on the collected (acquired) second interface impedance response data, the impedance values ​​corresponding to all adjacent sampled points are compared. If the calculated impedance change rate exceeds the set second preset change rate threshold, it is considered that an abnormal change has occurred at the mid-frequency characteristic frequency (corresponding to the second excitation signal). At the same time, based on the collected (acquired) third interface impedance response data, the corresponding impedance curve is fitted. If there is an interval in the impedance curve where the slope is greater than the preset slope threshold, it is determined that the second interface impedance response data and the third interface impedance response data meet the second preset impedance change condition. If the first interface impedance response data meets the first preset impedance change condition, and the second interface impedance response data and the third interface impedance response data meet the second preset impedance change condition, then the dendrite growth risk level is determined to be the initial dendrite growth risk.

[0042] In this context, considering that the charge transfer impedance and diffusion impedance of solid-state batteries are also significantly affected by pressure and temperature—for example, when the solid-state battery pressure is within a preset pressure range (such as the normal pressure range, i.e., the set pressure range for normal operation of the solid-state battery)—charge transfer impedance and diffusion impedance typically decrease when the temperature increases, while they may increase when the temperature decreases. Therefore, either the second preset rate of change threshold or the preset slope threshold can be determined based on the temperature of the solid-state battery within the preset pressure range. For example, within the preset pressure range, preset values ​​for the second preset rate of change threshold and the preset slope threshold corresponding to different temperatures are provided. This allows for rapid acquisition and dynamic adjustment of the second preset rate of change threshold and the preset slope threshold during practical applications, avoiding the complexity of real-time calculations, improving the efficiency and stability of solid-state battery judgment under different operating conditions, and thus ensuring the timeliness and accuracy of dendrite risk identification.

[0043] Optionally, after determining the dendrite growth risk level of the solid-state battery, the solid-state battery management method further includes: In response to the dendrite growth risk level of the solid-state battery being the initial dendrite growth risk, a preset clamping force is applied to the solid-state battery to adjust the interfacial contact state between the electrodes and the solid electrolyte.

[0044] Specifically, after determining the dendrite growth risk level of the solid-state battery, based on the determined dendrite growth risk level, if there is no dendrite risk, the solid-state battery can maintain normal operation without additional measures; however, if the dendrite growth risk level is at the initial stage of dendrite growth, a preset clamping force can be applied to the solid-state battery by controlling the corresponding clamping actuator. This is used to adjust the interface contact state between the electrode and the solid electrolyte, improve the uniformity of the interface contact between the electrode and the solid electrolyte, suppress current concentration and further dendrite expansion caused by poor local contact, and ensure the continued safe and stable operation of the solid-state battery. The actuator can be a mechanical clamping mechanism, a deformation control mechanism, or a clamping mechanism with clamping adjustment function located at the corresponding position on the solid-state battery, used to achieve timely intervention in the early stage of dendrite growth, significantly improving the operational safety and reliability of the solid-state battery. The preset clamping force can be set according to actual needs.

[0045] It is worth noting that for solid-state batteries, applying a preset clamping force during the initial dendrite growth stage can effectively improve the interfacial contact between the electrode and the solid electrolyte, mitigating current concentration caused by poor local contact and thus inhibiting further dendrite expansion (or growth). However, in the middle or even late stages of dendrite growth, when the dendrites have formed a clear penetrating trend or have already pierced the electrode-solid electrolyte interface, simply applying clamping force is often insufficient to reverse dendrite development. At this point, the dendrites may continue to grow until they cause internal short circuits and thermal runaway in the solid-state battery. Therefore, the method in this embodiment, by timely identifying and applying a preset clamping force during the initial stage of dendrite growth, can achieve early intervention of risks. Compared to taking passive measures in the middle and late stages, this is more effective and timely, significantly improving the safety and reliability of solid-state batteries during operation and reducing the battery scrap rate due to dendrite failure.

[0046] Optionally, the solid-state battery includes multiple stacked battery cells; step 100 includes: A preset excitation signal is applied to each battery cell to determine the interface impedance response data of each battery cell under the preset excitation signal. Step 200 includes: Based on the interfacial impedance response data, the dendrite growth risk level of each cell is determined.

[0047] Specifically, considering that solid-state batteries typically consist of multiple stacked cells, the interface contact conditions and dendrite growth risk levels of different cells may vary due to differences in manufacturing tolerances, stress states, or operating environments. Therefore, it is necessary to monitor each cell individually to ensure the overall operational safety and reliability of the solid-state battery. In step 100, a preset excitation signal is applied to each cell (either simultaneously or sequentially), and the corresponding interface impedance response data is collected to obtain the impedance characteristics at the cell level. Further, in step 200, the dendrite growth risk level of each cell is determined based on its impedance response data, thus confirming the dendrite growth risk level of each cell. This not only improves the precision of solid-state battery risk monitoring but also enhances the targetedness and effectiveness of risk management, ultimately ensuring the safety and reliability of the entire solid-state battery under complex operating environments.

[0048] Optionally, since solid-state batteries consist of multiple stacked cell units, to detect the interface impedance response data of each cell, an EIS sensor can be installed in each cell, forming an EIS sensor array within the solid-state battery. Through this array, a preset excitation signal can be applied to each cell under the coordination of the corresponding control unit, and the corresponding voltage and current responses can be collected synchronously, thereby acquiring the interface impedance response data of each cell in real time. Furthermore, the EIS sensor array can be deployed in a distributed manner, allowing each sensor to operate independently, or it can use a centralized bus connection method, achieving multi-channel measurement through time-division multiplexing to balance detection parallelism and system resource utilization. This enables independent monitoring of each cell within the stacked structure during solid-state battery operation, accurately identifying cells with corresponding dendrite risks, and preventing cell anomalies from being masked by overall data. This improves the granularity and accuracy of dendrite risk monitoring, providing a reliable basis for subsequent targeted protective measures and significantly enhancing the safety and reliability of the solid-state battery stacked structure.

[0049] Optionally, in response to the dendrite growth risk level of the solid-state battery being early dendrite growth risk, applying a preset clamping force to the solid-state battery to adjust the interfacial contact state between the electrodes and the solid electrolyte includes: In response to the dendrite growth risk level of at least one cell of the solid-state battery being in the early stage of dendrite growth, a preset clamping force is applied to the solid-state battery.

[0050] Specifically, after collecting interface impedance response data for each stacked cell of the solid-state battery and determining the dendrite growth risk level, if at least one cell is detected to meet the criteria for initial dendrite growth, the corresponding clamping actuator for the solid-state battery, such as a mechanical clamping device, clamping structure, or deformation control mechanism, is immediately triggered to apply a preset clamping force to the entire solid-state battery. By applying the preset clamping force, the interface contact state of all cells within the solid-state battery stack structure can be improved, thereby uniformly distributing interface pressure, alleviating current concentration caused by poor local contact, and inhibiting further dendrite expansion within cells that have already exhibited abnormalities, thus ensuring the overall operational safety and reliability of the solid-state battery.

[0051] Combination Figure 2 As shown, another embodiment of the present invention provides a solid-state battery management device, comprising: The excitation response module is used to apply a preset excitation signal to the solid-state battery and determine the interface impedance response data of the solid-state battery under the preset excitation signal. The risk assessment module is used to determine the dendrite growth risk level of solid-state batteries based on interface impedance response data.

[0052] The solid-state battery management device of this embodiment is used to implement the solid-state battery management method described above. Its advantages over the prior art are the same as the advantages of the solid-state battery management method over the prior art, and will not be repeated here.

[0053] Combination Figure 3 As shown, another embodiment of the present invention provides an electronic device, including a memory 301 and a processor 302; Memory 301 is used to store computer programs; Processor 302 is used to implement the above solid-state battery management method when executing a computer program.

[0054] Alternatively, an electronic device includes a memory 301 and a processor 302 coupled to the memory 301; the memory 301 is configured to store a computer program; the processor 302 is configured to perform the following operations when the computer program is executed: A preset excitation signal is applied to the solid-state battery, and the interface impedance response data of the solid-state battery under the preset excitation signal is determined. Based on the interface impedance response data, the dendrite growth risk level of the solid-state battery is determined.

[0055] The electronic device in this embodiment can be used to implement the above-described solid-state battery management method. Its advantages over the prior art are the same as the advantages of the above-described solid-state battery management method over the prior art, and will not be repeated here.

[0056] Another embodiment of the present invention provides a computer-readable storage medium storing a computer program, which is read and executed by a processor to implement the above-described solid-state battery management method.

[0057] Alternatively, a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following operations: A preset excitation signal is applied to the solid-state battery, and the interface impedance response data of the solid-state battery under the preset excitation signal is determined. Based on the interface impedance response data, the dendrite growth risk level of the solid-state battery is determined.

[0058] The technical solutions of the embodiments of the present invention, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This computer 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.) or processor to execute all or part of the steps of the methods of the embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, external hard drives, ROM, RAM, magnetic disks, or optical disks.

[0059] The computer-readable storage medium of this embodiment can be used to implement the above-described solid-state battery management method. Its advantages over the prior art are the same as those of the above-described solid-state battery management method over the prior art, and will not be repeated here.

[0060] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A solid-state battery management method, characterized in that, include: A preset excitation signal is applied to a solid-state battery, and the interface impedance response data of the solid-state battery under the preset excitation signal is determined; Based on the interface impedance response data, the dendrite growth risk level of the solid-state battery is determined.

2. The solid-state battery management method as described in claim 1, characterized in that, The preset excitation signals include a first excitation signal for detecting changes in ohmic impedance, a second excitation signal for detecting changes in charge transfer impedance, and a third excitation signal for detecting changes in diffusion impedance; wherein the first excitation signal, the second excitation signal, and the third excitation signal are AC signals with different frequencies. The step of applying a preset excitation signal to the solid-state battery and determining the interface impedance response data of the solid-state battery under the preset excitation signal includes: The first excitation signal, the second excitation signal, and the third excitation signal are applied to the solid-state battery respectively. The first interface impedance response data of the solid-state battery under the first excitation signal is determined, the second interface impedance response data of the solid-state battery under the second excitation signal is determined, and the third interface impedance response data of the solid-state battery under the third excitation signal is determined.

3. The solid-state battery management method as described in claim 2, characterized in that, The step of determining the dendrite growth risk level of the solid-state battery based on the interface impedance response data includes: If the first interface impedance response data does not meet the first preset impedance change condition, the dendrite growth risk level is determined to be no dendrite risk. If the first interface impedance response data meets the first preset impedance change condition, and the second interface impedance response data and the third interface impedance response data meet the second preset impedance change condition, the dendrite growth risk level is determined to be the initial dendrite growth risk.

4. The solid-state battery management method as described in claim 3, characterized in that, The first preset impedance change condition includes: The first interface impedance response data contains adjacent sampled data where the impedance change rate is greater than a first preset change rate threshold; wherein, the first preset change rate threshold is determined based on the temperature of the solid-state battery within a preset pressure range; And / or, the second preset impedance change condition includes: The second interface impedance response data contains adjacent sampled data where the impedance change rate is greater than the second preset change rate threshold, and the impedance curve obtained by fitting the third interface impedance response data has an interval where the slope is greater than the preset slope threshold; wherein, the second preset change rate threshold and / or the preset slope threshold are determined based on the temperature of the solid-state battery within a preset pressure range.

5. The solid-state battery management method according to any one of claims 1-4, characterized in that, After determining the dendrite growth risk level of the solid-state battery, the solid-state battery management method further includes: In response to the dendrite growth risk level of the solid-state battery being at the initial dendrite growth risk level, a preset clamping force is applied to the solid-state battery to adjust the interfacial contact state between the electrodes and the solid electrolyte of the solid-state battery.

6. The solid-state battery management method as described in claim 5, characterized in that, The solid-state battery comprises multiple stacked battery cells; the step of applying a preset excitation signal to the solid-state battery and determining the interface impedance response data of the solid-state battery under the preset excitation signal includes: A preset excitation signal is applied to each of the battery cells, and the interface impedance response data of each battery cell under the preset excitation signal is determined. The step of determining the dendrite growth risk level of the solid-state battery based on the interface impedance response data includes: Based on the interface impedance response data, the dendrite growth risk level of each of the battery cells is determined.

7. The solid-state battery management method as described in claim 6, characterized in that, The method of applying a preset clamping force to the solid-state battery to adjust the interfacial contact state between the electrodes and the solid electrolyte in response to the dendrite growth risk level of the solid-state battery being the initial dendrite growth risk includes: In response to the dendrite growth risk level of at least one of the cell cells of the solid-state battery being in the early stage of dendrite growth, the preset clamping force is applied to the solid-state battery.

8. A solid-state battery management device, characterized in that, include: An excitation response module is used to apply a preset excitation signal to a solid-state battery and determine the interface impedance response data of the solid-state battery under the preset excitation signal. The risk assessment module is used to determine the dendrite growth risk level of the solid-state battery based on the interface impedance response data.

9. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to implement the solid-state battery management method as described in any one of claims 1-7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is read and executed by a processor to implement the solid-state battery management method as described in any one of claims 1-7.

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