A single battery state evaluation method, device, equipment and storage medium

Abstract

The application relates to the technical field of battery state evaluation, and discloses a single battery state evaluation method, device, equipment and storage medium. In the method, a magnetization response evaluation method under the action of a static magnetic field is used to directly obtain the calculated magnetic susceptibility of a single battery and map the state of charge; then, a structural defect imaging method under the action of an alternating magnetic field is used to convert internal conductivity abnormalities into surface temperature distribution abnormalities by using eddy current heat effect, so that the single battery can be subjected to non-invasive spatial positioning and visual imaging; then, an ion dynamics evaluation method under the action of a pulse magnetic field is used to extract an open-circuit voltage relaxation time constant, so as to evaluate the battery health state; finally, a multi-source information fusion method is used to jointly infer the state of charge, the defect image and the relaxation constant, and output a high-confidence state evaluation result, so that the single battery can be comprehensively and accurately evaluated.

Description

Technical Field

[0001] This invention relates to the field of battery state assessment technology, specifically to a method, apparatus, device, and storage medium for assessing the state of a single battery cell. Background Technology

[0002] Against the backdrop of rapid development in energy storage technology, lithium-ion batteries, as core energy storage components, are widely used in electric vehicles, energy storage power stations, and consumer electronics. To ensure the safety and reliability of battery systems, accurate, rapid, and non-destructive state assessment of individual battery cells is of paramount importance. Key state parameters of a battery include its state of charge, state of health, and the integrity of its internal physical structure; these parameters directly affect the battery's performance, lifespan, and safety.

[0003] One method for assessing the state of a single cell in related technologies is electrochemical impedance spectroscopy (EIS). This method involves applying a small AC signal to the cell and measuring the change in impedance of a single cell with frequency, thereby obtaining electrochemical information about the cell's internal structure.

[0004] However, the electrochemical impedance spectroscopy method disclosed in related technologies can only obtain the overall frequency domain response information of the battery, which is difficult to meet the requirements of current energy storage power stations for comprehensive evaluation of battery status. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and storage medium for assessing the state of a single battery cell, in order to solve the problem that the single battery cell state assessment methods disclosed in related technologies are difficult to meet the requirements of current energy storage power stations for comprehensive assessment of battery state.

[0006] In a first aspect, the present invention provides a method for evaluating the state of a single battery cell, the method comprising: Based on the collected response signals of the target single cell under the action of a static magnetic field, the state of charge data of the corresponding single cell is obtained by using the magnetization response evaluation method; the response signals include voltage response, current response, induced magnetic field response and temperature field distribution. Based on the response signal of the target single cell under the action of an alternating magnetic field, the physical structural defect imaging data of the corresponding single cell is obtained by using the structural defect imaging method. Based on the collected response signal of the target single cell under the action of a pulsed magnetic field, the characteristic relaxation time constant of the corresponding single cell is obtained by using the ion dynamics characteristic evaluation method. By combining the state-of-charge data, physical structural defect imaging data, and characteristic relaxation time constants of individual cells, a multi-source information fusion method is used to perform inference and output the state assessment results of the corresponding individual cells.

[0007] Through the above implementation methods, the magnetization response evaluation method under static magnetic field is used to directly obtain the calculated magnetic susceptibility of a single cell and map its state of charge. Then, based on the structural defect imaging method under alternating magnetic field, the eddy current thermal effect is used to transform internal conductivity anomalies into surface temperature distribution anomalies, enabling non-invasive spatial positioning and visualization imaging of the single cell. Next, based on the ion dynamics evaluation method under pulsed magnetic field, the open-circuit voltage relaxation time constant is extracted to evaluate the cell's health status. Finally, a multi-source information fusion method is used to jointly infer the state of charge, defect images, and relaxation constant to output a high-confidence state evaluation result, facilitating a comprehensive and accurate evaluation of the single cell.

[0008] In one optional implementation, the process of obtaining the state-of-charge data of the corresponding single-cell battery based on the collected response signal of the target single-cell battery under the action of a static magnetic field, using a magnetization response evaluation method, includes: Collect the additional induced magnetic field of the target single cell under the action of a static magnetic field; Based on the additional induced magnetic field, the macroscopic average magnetic susceptibility of the target single cell is obtained using the magnetic susceptibility evaluation model. Based on the macroscopic average magnetic susceptibility of the target single cell, the state of charge of the corresponding single cell is obtained by querying a pre-established database of mapping relationships between magnetic susceptibility and state of charge.

[0009] Through the above implementation method, by collecting the additional induced magnetic field generated by a single cell under the action of a static magnetic field, and then using the magnetic susceptibility evaluation model to calculate the macroscopic average magnetic susceptibility, the battery's state of charge data can be directly obtained by querying a pre-established database of magnetic susceptibility and state of charge mapping relationship. Since static magnetic field excitation does not require disconnecting the battery circuit, online state of charge calibration can be achieved without interrupting battery operation, while avoiding any damage to the internal structure of the battery, significantly improving the convenience and real-time performance of battery state evaluation.

[0010] In one optional implementation, the step of obtaining physical structural defect imaging data of the corresponding single cell based on the collected response signal of the target single cell under the action of an alternating magnetic field and using a structural defect imaging method includes: Based on the response signal of the target single cell under the action of an alternating magnetic field, an infrared thermal imager is used to collect temperature data and obtain the temperature distribution data of the target single cell.

[0011] Through the above implementation method, eddy currents are induced in the conductive components of the battery by using an alternating magnetic field. The eddy currents will generate local conductivity anomalies in the defect area, which will cause changes in Joule heat power density, which will manifest as the characteristics of an abnormal area in the temperature field. The temperature distribution data of the battery surface can be directly collected by an infrared thermal imager under the excitation of an alternating magnetic field, so as to realize non-invasive imaging of physical structural defects inside the battery.

[0012] In one optional implementation, the characteristic relaxation time constant of the corresponding single cell is obtained based on the collected response signal of the target single cell under the action of a pulsed magnetic field using an ion dynamics characteristic evaluation method, including: Based on the collected response signal of the target single cell under the action of the pulsed magnetic field, the decay curve of the open circuit voltage of the single cell over time after the pulsed magnetic field is removed is obtained. Based on the decay curve of the open-circuit voltage of the single cell over time, an exponential decay model is used for fitting to obtain the characteristic relaxation time constant. Based on the aforementioned characteristic relaxation time constant, the chemical diffusion coefficient of lithium ions in a single cell is obtained by evaluating the diffusion kinetics method.

[0013] Through the above implementation method, by recording the decay curve of the open-circuit voltage of a single cell after the pulsed magnetic field is removed, and fitting it with an exponential decay model, the characteristic relaxation time constant is accurately extracted. Then, the chemical diffusion coefficient of lithium ions is obtained by using the diffusion kinetics evaluation method. This eliminates the need to wait for a long time for low-frequency scanning of electrochemical impedance spectroscopy, which significantly improves the testing efficiency. At the same time, the characteristic relaxation time constant reflects the migration and diffusion kinetics of lithium ions in the electrode material, providing key physical parameters for subsequent quantitative evaluation of battery aging.

[0014] In one optional implementation, the combined state-of-charge data, physical structural defect imaging data, and characteristic relaxation time constant of the integrated single-cell battery are used to perform inference using a multi-source information fusion method, outputting the state assessment result of the corresponding single-cell battery, including: Based on the state of charge data, physical structural defect imaging data, and characteristic relaxation time constant of the single cell, advanced features are obtained using feature extraction methods. The advanced features include state of charge measurement bias, thermal imaging spatial features and evolution features, and relaxation time constant curve morphology features. Based on the aforementioned advanced features, an evaluation is performed using a pre-defined joint reasoning model to obtain the state evaluation results of the corresponding individual battery cells.

[0015] Through the above implementation method, the state of charge data, physical structure defect imaging data and characteristic relaxation time constant are deeply integrated. First, the high-level features such as state of charge measurement deviation, thermal imaging space and evolution characteristics and relaxation time constant curve shape are extracted from them using feature extraction methods. Then, these high-level features are input into a preset joint inference model for evaluation, which breaks through the limitations of single parameter evaluation, effectively decouples the intertwined electrochemical, thermal and mechanical information inside the battery, and realizes consistency verification, defect root cause analysis and health status quantification of single cells.

[0016] In one optional implementation, the joint reasoning model includes: Evaluation models based on physical rules or data-driven machine learning models.

[0017] Through the above implementation methods, by flexibly selecting evaluation models or machine learning models, it is possible to meet the requirements of physical interpretability in laboratory scenarios as well as adapt to the needs of adaptive and highly robust intelligent evaluation in industrial settings.

[0018] Secondly, the present invention provides a single-cell battery state assessment device, the device comprising: The control and analysis module is used to generate excitation waveform commands, receive response signals, and execute the single-cell state evaluation method of the first aspect or any corresponding embodiment described above. The magnetic excitation module is used to receive excitation waveform commands and apply static magnetic field, alternating magnetic field or pulsed magnetic field to the individual cells; The signal acquisition module is used to acquire the response signals of individual cells under the action of static magnetic field, alternating magnetic field or pulsed magnetic field.

[0019] In one optional implementation, the signal acquisition module includes: A high-precision voltmeter used to measure the voltage response of a single cell. A zero-flux galvanometer is used to measure the current response of the circuit containing a single battery cell. A triaxial magnetometer is used to measure the induced magnetic field response in the near-field region of a single battery cell. Infrared thermal imagers are used to collect the temperature field distribution on the surface of individual battery cells. A multi-channel synchronous data acquisition instrument is used to synchronously acquire analog signals and convert them into digital signals.

[0020] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the single-cell battery state assessment method of the first aspect or any corresponding embodiment described above.

[0021] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the single-cell state assessment method of the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0022] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of the first process of a single-cell state assessment method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a second process for evaluating the state of a single cell according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the third process of the single-cell state assessment method according to an embodiment of the present invention; Figure 4 This is a structural block diagram of a single-cell battery state assessment device according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0026] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0027] The single-cell state assessment method disclosed in related technologies is electrochemical impedance spectroscopy (EIS). This method involves applying a small AC signal to the cell and measuring the change in impedance with frequency to obtain internal electrochemical information. However, the low-frequency testing in these methods is too time-consuming and can only provide overall frequency domain response information. It cannot spatially locate and visualize internal physical structural anomalies (such as electrode cracks, current collector fractures, and interface delamination), making it difficult to meet the comprehensive state assessment requirements of current energy storage power stations.

[0028] To overcome the aforementioned shortcomings, this embodiment provides a single-cell state assessment method. It directly obtains the calculated magnetic susceptibility of a single cell and maps it to the state of charge using a magnetization response assessment method under a static magnetic field. Then, based on a structural defect imaging method under an alternating magnetic field, it utilizes the eddy current thermal effect to transform internal conductivity anomalies into surface temperature distribution anomalies, enabling non-invasive spatial localization and visualization imaging of the single cell. Next, based on an ion dynamics assessment method under a pulsed magnetic field, it extracts the open-circuit voltage relaxation time constant to assess the cell's health. Finally, it employs a multi-source information fusion method to jointly infer the state of charge, defect images, and relaxation constant, outputting a high-confidence state assessment result, facilitating a comprehensive and accurate evaluation of the single cell.

[0029] According to an embodiment of the present invention, a method for evaluating the state of a single cell is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] This embodiment provides a method for assessing the state of a single battery cell, which can be used in the aforementioned energy storage power station monitoring server. Figure 1 This is a flowchart of a single-cell state assessment method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: S101, based on the collected response signal of the target single cell under the action of a static magnetic field, the state of charge data of the corresponding single cell is obtained by using the magnetization response evaluation method; the response signal includes voltage response, current response, induced magnetic field response and temperature field distribution.

[0031] A static magnetic field is a magnetic field whose magnitude and direction do not change with time. It is generated by using a constant direct current through an excitation coil and is used to excite the stable magnetization of the magnetic materials inside a single cell.

[0032] The response signal is a measurable physical quantity generated by the battery under the excitation of an external magnetic field, including: voltage response, which represents the change in potential difference between the positive and negative electrodes of the battery, such as the open-circuit voltage decay curve; current response, which represents the current signal flowing through the battery circuit or external circuit; induced magnetic field response, which represents the additional magnetic field generated by the magnetization of a single cell or eddy currents, and is measured using a magnetometer; and temperature field distribution, which represents the spatial distribution of temperature values ​​at various points on the battery surface, and is recorded using an infrared thermal imager.

[0033] The magnetization response evaluation method utilizes the magnetization characteristics of battery materials under a static magnetic field (magnetic susceptibility is related to lithium intercalation), and calculates the magnetic susceptibility by measuring the additional induced magnetic field, thereby indirectly determining the battery's state of charge.

[0034] State of charge (SOC) data describes the percentage of a battery's current remaining charge. The range of SOC data is typically 0% to 100%.

[0035] For example, S101 above includes: Collect the additional induced magnetic field of the target single cell under the action of a static magnetic field; Based on the additional induced magnetic field, the macroscopic average magnetic susceptibility of the target single cell is obtained using the magnetic susceptibility evaluation model. Based on the macroscopic average magnetic susceptibility of the target single cell, the state of charge of the corresponding single cell is obtained by querying a pre-established database of mapping relationships between magnetic susceptibility and state of charge.

[0036] Specifically, the above S101 can be implemented as follows: When a uniform static magnetic field of known strength is applied to a battery, the magnetic materials inside the battery are magnetized, generating an additional induced magnetic field. This additional induced magnetic field is measured using a high-precision magnetometer. The macroscopic average magnetic susceptibility χ is calculated using a magnetic susceptibility evaluation model, which satisfies the following:

[0037] In the formula, Indicates the macroscopic average magnetic susceptibility; This indicates the additional induced magnetic field measured in a single cell; This represents the magnetic field strength of the applied uniform static magnetic field; It represents the vacuum permeability.

[0038] Since there is a one-to-one correspondence between average magnetic susceptibility and state of charge, by querying a pre-established mapping database of magnetic susceptibility and state of charge for the corresponding battery material, the state of charge of a single cell can be determined quickly and accurately in a non-invasive manner.

[0039] By collecting the additional induced magnetic field generated by a single cell under the action of a static magnetic field, and then using a magnetic susceptibility evaluation model to calculate the macroscopic average magnetic susceptibility, the battery's state of charge data can be directly obtained by querying a pre-established database of magnetic susceptibility and state of charge mapping relationship. Since static magnetic field excitation does not require disconnecting the battery circuit, online state of charge calibration can be achieved without interrupting battery operation, while avoiding any damage to the internal structure of the battery, significantly improving the convenience and real-time performance of battery state assessment.

[0040] S102, based on the collected response signal of the target single cell under the action of an alternating magnetic field, the physical structural defect imaging data of the corresponding single cell is obtained by using the structural defect imaging method.

[0041] An alternating magnetic field is a magnetic field whose magnitude and direction change periodically with time. It is generated by alternating current passing through an excitation coil and is used to induce eddy currents in the conductors of a single cell.

[0042] The structural defect imaging method utilizes an alternating magnetic field to generate eddy currents inside the battery, captures the abnormal temperature distribution caused by the defect using a thermal imager, and converts it into a visualized image of the defect location and shape.

[0043] Physical structural defect imaging data are two-dimensional or three-dimensional images and characteristic parameters used to reflect the spatial location, shape, area, and temperature anomaly type (cold spot / hot spot) of physical damage inside the battery (such as electrode cracks, current collector fractures, interface delamination, etc.).

[0044] For example, S102 above includes: Based on the response signal of the target single cell under the action of an alternating magnetic field, an infrared thermal imager is used to collect temperature data and obtain the temperature distribution data of the target single cell.

[0045] Specifically, the above S102 can be implemented as follows: When a high-frequency alternating magnetic field B_ac(ω) is applied to the battery, the time-varying magnetic field induces eddy currents J_eddy in the conductive parts (aluminum / copper current collector, casing) inside the battery. When these eddy currents flow in a resistive conductor, they generate Joule heat, with a corresponding heat power density of P_heat=(J_eddy)² / σ. When defects such as electrode cracks, current collector fractures, or interface delamination exist inside the battery, the local conductivity σ will significantly decrease or the current path will change, leading to abnormal eddy current heating in that region, manifesting as "cold spots" or "hot spots" in the surface temperature field. By capturing this temperature distribution anomaly using an infrared thermal imager, non-invasive spatial imaging and localization of internal physical structural defects can be achieved.

[0046] By inducing eddy currents in the conductive components of a battery using an alternating magnetic field, the eddy currents can generate localized conductivity anomalies in defect areas, which in turn cause changes in Joule heat power density, manifesting as the characteristics of an abnormal region in the temperature field. By using an infrared thermal imager to directly collect temperature distribution data on the battery surface under the excitation of an alternating magnetic field, non-invasive imaging of physical structural defects inside the battery can be achieved.

[0047] S103. Based on the collected response signal of the target single cell under the action of a pulsed magnetic field, the characteristic relaxation time constant of the corresponding single cell is obtained by using the ion dynamics characteristic evaluation method.

[0048] A pulsed magnetic field is a transient magnetic field with an extremely short duration (such as milliseconds) and a high amplitude. It is generated by a pulsed current passing through an excitation coil and is used to create instantaneous disturbances in the ion distribution inside a single cell.

[0049] The ion kinetics evaluation method utilizes a pulsed magnetic field to perturb the lithium-ion distribution in a single cell, and extracts the time constant by recording the exponential decay curve of the open-circuit voltage during relaxation to evaluate the lithium-ion diffusion and migration capabilities.

[0050] The characteristic relaxation time constant is a physical quantity used to describe how quickly a disturbed ion system recovers to equilibrium. It is obtained by exponentially fitting the open-circuit voltage decay curve and is inversely proportional to the lithium-ion chemical diffusion coefficient.

[0051] S104 integrates the state-of-charge data of individual cells, imaging data of physical structural defects, and characteristic relaxation time constants, and uses a multi-source information fusion method to perform inference, outputting the state assessment results of the corresponding individual cells.

[0052] Multi-source information fusion is a process of extracting features, performing correlation analysis, and making comprehensive inferences from heterogeneous data from different assessment modes (charge state data, physical structure defect imaging data, and characteristic relaxation time constants) to output more accurate and comprehensive diagnostic conclusions than those from a single parameter.

[0053] The condition assessment results are the final conclusions output after multi-source fusion, including the verified state of charge, defect type and location, root cause analysis, comprehensive health score, and safety risk level.

[0054] This embodiment provides a method for assessing the state of a single battery cell. It directly obtains the calculated magnetic susceptibility of the cell and maps it to the state of charge using a magnetization response assessment method under a static magnetic field. Then, based on a structural defect imaging method under an alternating magnetic field, it utilizes the eddy current thermal effect to transform internal conductivity anomalies into surface temperature distribution anomalies, enabling non-invasive spatial localization and visualization imaging of the single battery cell. Next, based on an ion dynamics assessment method under a pulsed magnetic field, it extracts the open-circuit voltage relaxation time constant to assess the battery's health. Finally, it uses a multi-source information fusion method to jointly infer the state of charge, defect images, and relaxation constant, outputting a high-confidence state assessment result, facilitating a comprehensive and accurate assessment of the single battery cell.

[0055] This embodiment provides a method for assessing the state of a single battery cell, which can be used in the aforementioned energy storage power station monitoring server. Figure 2 This is a flowchart of a single-cell state assessment method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: S201, based on the collected response signal of the target single cell under the action of a static magnetic field, uses the magnetization response evaluation method to obtain the state of charge data of the corresponding single cell; the response signal includes voltage response, current response, induced magnetic field response, and temperature field distribution. For details, please refer to [link to relevant documentation]. Figure 1 S101 of the illustrated embodiment will not be described again here.

[0056] S202, based on the collected response signal of the target single cell under the action of an alternating magnetic field, uses a structural defect imaging method to obtain the physical structural defect imaging data of the corresponding single cell. For details, please refer to [link to relevant documentation]. Figure 1 S102 of the illustrated embodiment will not be described again here.

[0057] S203, based on the collected response signal of the target single cell under the action of a pulsed magnetic field, the characteristic relaxation time constant of the corresponding single cell is obtained by using the ion dynamics characteristic evaluation method.

[0058] Specifically, S203 above includes: S2031, Based on the collected response signal of the target single cell under the action of the pulsed magnetic field, obtain the decay curve of the open circuit voltage of the single cell over time after the pulsed magnetic field is removed. S2032, based on the decay curve of the open-circuit voltage of a single cell over time, uses an exponential decay model for fitting to obtain the characteristic relaxation time constant; S2033, based on the characteristic relaxation time constant, is evaluated using the diffusion kinetics assessment method to obtain the chemical diffusion coefficient of lithium ions in a single cell.

[0059] For example, S203 above includes: A short (millisecond-level) strong magnetic pulse B_pulse is applied to a battery in electrochemical equilibrium. The pulsed magnetic field instantaneously disturbs the migration of lithium ions in the electrolyte of a single cell through the Lorentz force F_L=q(v×B). After the pulsed magnetic field is removed, the disturbed ion distribution in the single cell relaxes back to equilibrium through diffusion and other means. This process is manifested as an exponential decay of the battery open-circuit voltage U_ocv(t) over time. By recording the decay curve of the battery open-circuit voltage U_ocv(t) and fitting it with the formula U_ocv(t)=U_∞+ΔU·exp(-t / τ), the characteristic relaxation time constant τ is extracted. According to diffusion kinetics theory, the characteristic relaxation time constant is approximately inversely proportional to the lithium-ion chemical diffusion coefficient D_Li. Therefore, the characteristic relaxation time constant is output as a key kinetic parameter for evaluating the battery's health status.

[0060] By recording the decay curve of the open-circuit voltage of a single cell after the pulsed magnetic field is removed and fitting it with an exponential decay model, the characteristic relaxation time constant is accurately extracted. Then, the chemical diffusion coefficient of lithium ions is obtained by using the diffusion kinetics evaluation method. This eliminates the need to wait for a long time for low-frequency scanning of electrochemical impedance spectroscopy, which significantly improves the testing efficiency. At the same time, the characteristic relaxation time constant reflects the migration and diffusion kinetics of lithium ions in the electrode material, providing key physical parameters for subsequent quantitative assessment of battery aging.

[0061] S204 integrates the state-of-charge data of individual cells, imaging data of physical structural defects, and characteristic relaxation time constants. It then uses a multi-source information fusion method to perform inference and output the state assessment result for the corresponding individual cell. For details, please refer to [link to relevant documentation]. Figure 1 S104 of the illustrated embodiment will not be described again here.

[0062] This embodiment provides a method for assessing the state of a single battery cell. It directly obtains the calculated magnetic susceptibility of the cell and maps it to the state of charge using a magnetization response assessment method under a static magnetic field. Then, based on a structural defect imaging method under an alternating magnetic field, it utilizes the eddy current thermal effect to transform internal conductivity anomalies into surface temperature distribution anomalies, enabling non-invasive spatial localization and visualization imaging of the single battery cell. Next, based on an ion dynamics assessment method under a pulsed magnetic field, it extracts the open-circuit voltage relaxation time constant to assess the battery's health. Finally, it uses a multi-source information fusion method to jointly infer the state of charge, defect images, and relaxation constant, outputting a high-confidence state assessment result, facilitating a comprehensive and accurate assessment of the single battery cell.

[0063] This embodiment provides a method for assessing the state of a single battery cell, which can be used in the aforementioned energy storage power station monitoring server. Figure 3This is a flowchart of a single-cell state assessment method according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: S301, based on the collected response signal of the target single-cell battery under the action of a static magnetic field, uses a magnetization response evaluation method to obtain the state of charge data of the corresponding single-cell battery; the response signal includes voltage response, current response, induced magnetic field response, and temperature field distribution. For details, please refer to [link to relevant documentation]. Figure 1 S101 of the illustrated embodiment will not be described again here.

[0064] S302, based on the collected response signal of the target single cell under the action of an alternating magnetic field, uses a structural defect imaging method to obtain the physical structural defect imaging data of the corresponding single cell. For details, please refer to [link to relevant documentation]. Figure 1 S302 of the illustrated embodiment will not be described again here.

[0065] S303, based on the collected response signal of the target single cell under the action of a pulsed magnetic field, uses the ion dynamics characteristic evaluation method to obtain the characteristic relaxation time constant of the corresponding single cell. For details, please refer to [link to relevant documentation]. Figure 1 S103 of the illustrated embodiment will not be described again here.

[0066] S304 integrates the state-of-charge data of individual cells, imaging data of physical structural defects, and characteristic relaxation time constants, and uses a multi-source information fusion method to perform inference and output the state assessment results of the corresponding individual cells.

[0067] For example, S304 above includes: S3041, based on the state of charge data of a single cell, imaging data of physical structural defects, and characteristic relaxation time constant, uses feature extraction methods to obtain advanced features; the advanced features include state of charge measurement bias, thermal imaging spatial features and evolution features, and relaxation time constant curve morphology features. S3042, based on advanced features, uses a preset joint reasoning model to perform evaluation and obtain the state evaluation results of the corresponding single cell.

[0068] Advanced features are quadratic parameters with stronger characterization capabilities and physical significance obtained from state-of-charge data, thermal imaging maps, and relaxation time constant sequences through feature extraction algorithms. These parameters are used to input the joint inference model to reveal the deep-seated patterns of the battery's internal state.

[0069] The state of charge measurement deviation (ΔSOC) is the absolute difference between the state of charge value obtained based on the magnetization response evaluation method and the theoretical state of charge value set through charge-discharge cycles. The magnitude of this deviation can be used to assess the consistency of battery capacity calibration and the presence of abnormal electrochemical side reactions.

[0070] Thermal imaging spatial features and evolutionary features are two types of features extracted from temperature distribution maps acquired by infrared thermal imagers. They include: Spatial features: including the centroid coordinates, pixel area, and maximum temperature difference of temperature anomaly regions ("cold spots" or "hot spots" whose temperature difference from the average temperature exceeds a threshold), used to locate defects and assess their severity; Evolutionary features: analyzing the patterns of the above spatial features as the state of charge changes. For example, a "cold spot" in a fixed position may correspond to a physical crack, while a "hot spot" that appears and moves with increasing state of charge may correspond to a region of uneven lithium ion insertion / extraction.

[0071] The morphological characteristics of the relaxation time constant curve are morphological parameters extracted from the curve of the relaxation time constant changing with the state of charge. These parameters include the average slope and curvature of the curve in a specific range, reflecting the dependence of the diffusion coefficient on the state of charge (related to the phase transition behavior of the electrode material).

[0072] Joint reasoning models are pre-defined models used to comprehensively judge extracted high-level features. They include: physical rule-based evaluation models and data-driven machine learning models. Physical rule-based evaluation models utilize prior knowledge of electromagnetism, electrochemistry, etc., to construct explicit judgment logic. For example, a large deviation in state of charge measurement, the presence of moving hot spots, and an abnormally low relaxation time constant infers a local micro-short circuit in the corresponding single-cell battery. Data-driven machine learning models, on the other hand, are trained on a large number of samples (such as random forests or neural networks) to automatically learn the complex nonlinear mapping between multi-source features and battery state, adapting to fuzzy or complex fault modes.

[0073] The state assessment results are the final diagnostic conclusions output by the joint inference model, which include: the final state of charge value with confidence labels after multi-parameter verification; defect map and root cause analysis (defect type, location, severity level and possible physical / chemical causes); comprehensive health status score and health sub-scores for each dimension (capacity, dynamics, structure).

[0074] By deeply fusing state-of-charge data, physical structural defect imaging data, and characteristic relaxation time constants, high-level features such as state-of-charge measurement deviation, thermal imaging spatial and evolution characteristics, and relaxation time constant curve morphology are first extracted using feature extraction methods. These high-level features are then input into a pre-defined joint inference model for evaluation, overcoming the limitations of single-parameter evaluation and effectively decoupling the intertwined electrochemical, thermal, and mechanical information within the battery. This enables consistency verification, defect root cause analysis, and health status quantification of individual cells.

[0075] This embodiment provides a method for assessing the state of a single battery cell. It directly obtains the calculated magnetic susceptibility of the cell and maps it to the state of charge using a magnetization response assessment method under a static magnetic field. Then, based on a structural defect imaging method under an alternating magnetic field, it utilizes the eddy current thermal effect to transform internal conductivity anomalies into surface temperature distribution anomalies, enabling non-invasive spatial localization and visualization imaging of the single battery cell. Next, based on an ion dynamics assessment method under a pulsed magnetic field, it extracts the open-circuit voltage relaxation time constant to assess the battery's health. Finally, it uses a multi-source information fusion method to jointly infer the state of charge, defect images, and relaxation constant, outputting a high-confidence state assessment result, facilitating a comprehensive and accurate assessment of the single battery cell.

[0076] This embodiment also provides a single-cell battery state assessment device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0077] This embodiment provides a single-cell state assessment device, such as... Figure 4 As shown, it includes: The control and analysis module 410 is used to generate excitation waveform commands, receive response signals, and execute the single-cell state evaluation method of this invention. The magnetic excitation module 420 is used to receive excitation waveform commands and apply a static magnetic field, alternating magnetic field, or pulsed magnetic field to a single cell. The signal acquisition module 430 is used to acquire the response signal of a single cell under the action of a static magnetic field, an alternating magnetic field, or a pulsed magnetic field.

[0078] In some alternative implementations, the magnetic excitation module 420 includes: The signal generator is used to receive the excitation waveform commands generated by the control and analysis module and generate the corresponding control current; The power amplifier is used to receive and amplify the control current from the signal generator and input it to the excitation mechanism. The excitation mechanism is used to receive the control current amplified by the power amplifier and generate an excitation magnetic field with uniform spatial distribution and precise controllable intensity and time characteristics.

[0079] For example, the excitation mechanism can be implemented as a pair of Helmholtz coils.

[0080] In some alternative implementations, the signal acquisition module 430 includes: A high-precision voltmeter used to measure the voltage response of a single cell. A zero-flux galvanometer is used to measure the current response of the circuit containing a single battery cell. A triaxial magnetometer is used to measure the induced magnetic field response in the near-field region of a single battery cell. Infrared thermal imagers are used to collect the temperature field distribution on the surface of individual battery cells. A multi-channel synchronous data acquisition instrument is used to synchronously acquire analog signals and convert them into digital signals.

[0081] The single-cell state assessment device provided in this embodiment of the invention can execute the single-cell state assessment method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0082] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0083] The following is a detailed reference. Figure 5 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, a graphics processing unit, etc.)*01, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from memory 508 into random access memory (RAM) 503. RAM 503 also stores various programs and data required for the operation of the electronic device. The processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0084] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0085] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a memory 508, or installed from a ROM 502. When the computer program is executed by the processor 501, it performs the functions defined in the single-cell battery state assessment method of the embodiments of the present invention.

[0086] Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0087] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the single-cell battery state assessment method shown in the above embodiments is implemented.

[0088] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0089] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for evaluating the state of a single cell, characterized in that, The method includes: Based on the collected response signals of the target single cell under the action of a static magnetic field, the state of charge data of the corresponding single cell is obtained by using the magnetization response evaluation method; the response signals include voltage response, current response, induced magnetic field response and temperature field distribution. Based on the response signal of the target single cell under the action of an alternating magnetic field, the physical structural defect imaging data of the corresponding single cell is obtained by using the structural defect imaging method. Based on the collected response signal of the target single cell under the action of a pulsed magnetic field, the characteristic relaxation time constant of the corresponding single cell is obtained by using the ion dynamics characteristic evaluation method. By combining the state-of-charge data, physical structural defect imaging data, and characteristic relaxation time constants of individual cells, a multi-source information fusion method is used to perform inference and output the state assessment results of the corresponding individual cells.

2. The method according to claim 1, characterized in that, The state-of-charge (SOC) data of the corresponding single cell is obtained by using a magnetization response evaluation method based on the collected response signal of the target single cell under a static magnetic field, including: Collect the additional induced magnetic field of the target single cell under the action of a static magnetic field; Based on the additional induced magnetic field, the macroscopic average magnetic susceptibility of the target single cell is obtained using the magnetic susceptibility evaluation model. Based on the macroscopic average magnetic susceptibility of the target single cell, the state of charge of the corresponding single cell is obtained by querying a pre-established database of mapping relationships between magnetic susceptibility and state of charge.

3. The method according to claim 1, characterized in that, The method involves using the acquired response signal of the target single cell under an alternating magnetic field to obtain physical structural defect imaging data of the corresponding single cell using a structural defect imaging method, including: Based on the response signal of the target single cell under the action of an alternating magnetic field, an infrared thermal imager is used to collect temperature data and obtain the temperature distribution data of the target single cell.

4. The method according to claim 1, characterized in that, The characteristic relaxation time constant of the corresponding single cell is obtained by using the ion dynamics evaluation method based on the collected response signal of the target single cell under the action of a pulsed magnetic field, including: Based on the collected response signal of the target single cell under the action of the pulsed magnetic field, the decay curve of the open circuit voltage of the single cell over time after the pulsed magnetic field is removed is obtained. Based on the decay curve of the open-circuit voltage of the single cell over time, an exponential decay model is used for fitting to obtain the characteristic relaxation time constant. Based on the aforementioned characteristic relaxation time constant, the chemical diffusion coefficient of lithium ions in a single cell is obtained by evaluating the diffusion kinetics method.

5. The method according to claim 1, characterized in that, The integrated single-cell state-of-charge data, physical structural defect imaging data, and characteristic relaxation time constants are used to perform inference using a multi-source information fusion method, outputting the corresponding single-cell state assessment results, including: Based on the state of charge data, physical structural defect imaging data, and characteristic relaxation time constant of the single cell, advanced features are obtained using feature extraction methods. The advanced features include state of charge measurement bias, thermal imaging spatial features and evolution features, and relaxation time constant curve morphology features. Based on the aforementioned advanced features, an evaluation is performed using a pre-defined joint reasoning model to obtain the state evaluation results of the corresponding individual battery cells.

6. The method according to claim 5, characterized in that, The joint reasoning model includes: Evaluation models based on physical rules or data-driven machine learning models.

7. A single-cell battery state assessment device, characterized in that, The device includes: The control and analysis module is used to generate excitation waveform commands, receive response signals, and execute the single-cell state evaluation method according to any one of claims 1 to 6. The magnetic excitation module is used to receive excitation waveform commands and apply static magnetic field, alternating magnetic field or pulsed magnetic field to the individual cells; The signal acquisition module is used to acquire the response signals of individual cells under the action of static magnetic field, alternating magnetic field or pulsed magnetic field.

8. The apparatus according to claim 7, characterized in that, The signal acquisition module includes: A high-precision voltmeter used to measure the voltage response of a single cell. A zero-flux galvanometer is used to measure the current response of the circuit containing a single battery cell. A triaxial magnetometer is used to measure the induced magnetic field response in the near-field region of a single battery cell. Infrared thermal imagers are used to collect the temperature field distribution on the surface of individual battery cells. A multi-channel synchronous data acquisition instrument is used to synchronously acquire analog signals and convert them into digital signals.

9. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the single-cell state assessment method according to any one of claims 1 to 6 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the single-cell state assessment method according to any one of claims 1 to 6.

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