Battery dendritic crystal monitoring method, system, equipment and product based on ultrasonic guided waves

Abstract

The invention discloses a battery dendritic crystal monitoring method, system, equipment and product based on ultrasonic guided waves, and the method comprises the steps: employing a piezoelectric transducer to excite SH0 ultrasonic guided waves in a normal charging and discharging state of a battery, and enabling the SH0 ultrasonic guided waves to be transmitted along the surface of an electrode or a waveguide structure which is tightly coupled with the electrode, and high-precision acquisition and analysis are carried out on reflection and transmission echo signals. And carrying out guided wave feature extraction on the echo signal to obtain key parameters such as guided wave propagation time, speed drift and energy attenuation, so as to realize real-time and high-sensitivity monitoring of the process from early stage initiation and growth to irreversible accumulation of the crystal dendrites. And in combination with a signal processing algorithm and a threshold criterion, a quantitative characterization and early warning mechanism of crystal dendrite evolution is constructed, so that the safety risks that the crystal dendrite pierces the diaphragm and internal short circuit occurs are reduced. The nondestructive detection monitoring method can provide powerful technical support for battery safety management, life prediction and battery management system linkage control.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and in particular to a method, system, device and product for monitoring battery dendrites based on ultrasonic guided waves. Background Technology

[0002] Due to their crucial role in power peak shaving, renewable energy grid integration, and distributed energy systems, energy storage batteries are continuously evolving towards higher safety, lower cost, and longer lifespan. Among them, energy storage battery systems with metal anodes (such as zinc and lithium metal anode batteries) have shown promising application prospects in large-scale energy storage due to their advantages of high theoretical capacity, abundant raw material reserves, and diverse systems. However, during repeated charge and discharge cycles, the deposition of metal ions on the anode surface is prone to uneven spatial distribution. Local current density concentrations can lead to non-uniform metal deposition and further induce the formation of unstable deposition morphologies such as dendrites. With increasing cycle count, dendrite structures may continue to grow towards the electrolyte and separator, posing a risk of puncturing the separator and causing internal short circuits, resulting in serious safety hazards. Furthermore, some metal deposits cannot be completely recovered during subsequent stripping processes, gradually transforming into irreversible "dead metal," leading to reversible capacity decay, reduced coulombic efficiency, and potential thermal runaway due to localized electrochemical and thermodynamic imbalances. Therefore, under the actual working conditions of energy storage batteries, real-time, online monitoring of metal deposition inhomogeneity, dendrite growth, and irreversible deposition accumulation processes with sufficient sensitivity has become a key technical requirement for improving the safety and service life of metal anode energy storage batteries.

[0003] Existing ultrasonic transmission or reflection monitoring technologies typically assess the internal structural state of batteries at a holistic scale, including macroscopic features such as electrode integrity, electrolyte state, and battery casing deformation. These methods, which transmit bulk waves through the entire battery structure, have limited sensitivity to changes in the microscopic deposition state of the electrode surface, particularly local structural changes during the early stages of metal deposition inhomogeneity and dendrite initiation. Furthermore, traditional ultrasonic detection methods struggle to distinguish the subtle effects of reversible metal deposition / stripping processes on acoustic signals from those of irreversible metal residues. They also lack the ability to directionally monitor and differentiate deposition behavior at specific electrode interfaces, failing to meet the practical needs of safe operation and lifespan management for metal anode energy storage batteries. Summary of the Invention

[0004] This invention provides a method, system, device, and product for monitoring battery dendrites based on ultrasonic guided waves. It monitors dendrites on the target battery electrode based on SHO ultrasonic guided waves, and has a high sensitivity for detecting dendrites in the early stage of dendrite formation. By analyzing the evolution characteristics of ultrasonic guided wave parameters, it distinguishes between reversible and irreversible deposition accumulation states in the metal deposition / stripping process. Irreversible deposition accumulation can manifest as dendrite growth or dead metal residue, and its different effects on battery health are clarified.

[0005] To achieve the above objectives, embodiments of the present invention provide a battery dendrite monitoring method based on ultrasonic guided waves, comprising: SH0 ultrasonic guided waves are excited to the target battery, and the echo signal data of the SH0 ultrasonic guided waves are acquired; The guided wave feature is extracted from the echo signal data to obtain the guided wave parameter features of the echo signal data; The dendritic evolution morphology of the target cell is determined based on the characteristics of the waveguide parameters and the preset correspondence between the characteristics of the waveguide parameters and the deposition state. The dendrite growth stage of the target battery is determined based on the dendrite evolution morphology, the characteristics of the waveguide parameters, the historical monitoring data of the target battery, and the synchronous electrode surface images.

[0006] As an improvement to the above scheme, the step of exciting SHO ultrasonic guided waves to the target battery and acquiring the echo signal data of the SHO ultrasonic guided waves includes: A piezoelectric transducer is used to excite SHO ultrasonic guided waves to the target battery, and the SHO ultrasonic guided waves propagate along the battery electrodes of the target battery and the waveguide structure tightly coupled to the battery electrodes. The echo signal data of the SHO ultrasonic guided wave during its propagation is acquired using a receiving transducer; wherein, the echo signal data includes the reflected wave and transmitted wave signals of the SHO ultrasonic guided wave during its propagation.

[0007] As an improvement to the above scheme, the step of extracting guided wave features from the echo signal data to obtain the guided wave parameter features of the echo signal data includes: The echo signal data is preprocessed to extract the propagation time and amplitude information of the processed echo signal data; The waveguide parameter characteristics of the echo signal data are calculated based on the propagation time and amplitude information; wherein, the waveguide parameter characteristics include waveguide propagation velocity and attenuation coefficient.

[0008] As an improvement to the above scheme, if the waveguide parameter characteristics include waveguide propagation velocity and attenuation coefficient, The step of determining the dendritic evolution morphology of the target cell based on the waveguide parameter characteristics and the preset correspondence between the waveguide parameter characteristics and the deposition state includes: If the propagation speed of the guided wave exhibits a regular fluctuation synchronized with the battery charge-discharge cycle, and the attenuation coefficient does not show a continuous increasing trend, then based on the preset correspondence between the guided wave parameter characteristics and the deposition state, it is determined that the metal deposition / stripping process in the target battery remains reversible, and no obvious dendrite-induced deposition accumulation occurs on the electrode surface. If the propagation velocity of the guided wave exhibits an irreversible monotonic drift and the attenuation coefficient continues to increase, then based on the preset correspondence between the guided wave parameter characteristics and the deposition state, it is determined that there is irreversible residual metal deposition behavior in the target battery, and the metal deposition morphology is manifested as dendrite growth or dead metal accumulation.

[0009] As an improvement to the above scheme, determining the dendrite growth stage of the target battery based on the dendrite evolution morphology, the waveguide parameter characteristics, the historical monitoring data of the target battery, and concurrent electrode surface images includes: Align the waveguide parameter characteristics and the historical monitoring data of the target battery according to the number of charge-discharge cycles or timestamps, and calculate the change amount and trend of the waveguide parameter characteristics; The dendrite growth stage of the target battery is determined based on the change amount and trend, the dendrite evolution morphology, the synchronous electrode surface image, and the preset dendrite growth stage characteristic state.

[0010] As an improvement to the above scheme, after determining the dendrite growth stage of the target cell, the method further includes: Risk warnings are issued for the target battery based on preset waveguide parameter characteristic thresholds and the dendrite growth stage.

[0011] To achieve the above objectives, embodiments of the present invention provide a battery dendrite monitoring system based on ultrasonic guided waves, comprising: The echo signal acquisition module is used to excite SHO ultrasonic guided waves to the target battery and acquire the echo signal data of the SHO ultrasonic guided waves. The waveguide parameter extraction module is used to extract waveguide features from the echo signal data to obtain the waveguide parameter features of the echo signal data. The dendrite type determination module is used to determine the dendrite evolution morphology of the target cell based on the waveguide parameter characteristics and the preset correspondence between the waveguide parameter characteristics and the deposition state. The growth stage determination module is used to determine the dendrite growth stage of the target battery based on the dendrite evolution morphology, the waveguide parameter characteristics, the historical monitoring data of the target battery, and the synchronous electrode surface image.

[0012] To achieve the above objectives, this invention provides a battery dendrite monitoring device based on ultrasonic guided waves, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the above-described battery dendrite monitoring method based on ultrasonic guided waves.

[0013] To achieve the above objectives, embodiments of the present invention also provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the above-described method for monitoring battery dendrites based on ultrasonic guided waves.

[0014] Compared with existing technologies, the present invention discloses a battery dendrite monitoring method, system, device, and product based on ultrasonic guided waves. This method involves exciting SHO ultrasonic guided waves onto a target battery to obtain echo signal data of the SHO ultrasonic guided waves; extracting guided wave features from the echo signal data to obtain guided wave parameter features; determining the dendrite evolution morphology of the target battery based on the guided wave parameter features and a preset correspondence between the guided wave parameter features and the deposition state; and determining the dendrite growth stage of the target battery based on the dendrite evolution morphology, the guided wave parameter features, historical monitoring data of the target battery, and concurrent electrode surface images. By extracting the parameter characteristics of the SHO ultrasonic guided wave and combining them with a preset correspondence, it is possible to clearly distinguish between the reversible evolution state and the irreversible deposition accumulation state of the metal deposition / exfoliation process. This enables accurate identification of the reversibility of metal deposition behavior and its corresponding dendrite evolution morphology, thereby avoiding the impact of misjudging irreversible deposition residues as normal reversible deposition processes on battery status assessment. Based on the characteristics of the SHO ultrasonic guided wave propagating along the electrode and tightly coupled waveguide structure under normal battery operation, it has high sensitivity to changes in the micro-morphology of the electrode surface and can capture subtle physical changes in the early dendrite initiation stage. This solves the problem of insufficient sensitivity of existing technologies in monitoring the initial formation of dendrites and improves the sensitivity and real-time performance of dendrite growth monitoring. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart of a battery dendrite monitoring method based on ultrasonic guided waves provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the physical structure of a battery dendrite monitoring system provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a battery dendrite monitoring system based on ultrasonic guided waves provided in an embodiment of the present invention; Figure 4 This is a structural block diagram of a battery dendrite monitoring device based on ultrasonic guided waves provided in an embodiment of the present invention. Detailed Implementation

[0016] 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, and 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.

[0017] It should be noted that the terms "comprising" and "specific" in this invention, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0018] Please see Figure 1 , Figure 1 This is a flowchart illustrating a battery dendrite monitoring method based on ultrasonic guided waves provided in an embodiment of the present invention. The battery dendrite monitoring method based on ultrasonic guided waves includes: S1, excite SH0 ultrasonic guided waves to the target battery and acquire the echo signal data of the SH0 ultrasonic guided waves; S2, perform guided wave feature extraction on the echo signal data to obtain the guided wave parameter features of the echo signal data; S3, determine the dendritic evolution morphology of the target cell based on the waveguide parameter characteristics and the preset correspondence between the waveguide parameter characteristics and the deposition state; S4. Based on the dendrite evolution morphology, the characteristics of the waveguide parameters, the historical monitoring data of the target battery, and the synchronous electrode surface image, determine the dendrite growth stage of the target battery.

[0019] For example, taking the formation of zinc dendrites in a zinc-ion battery as an example, under the normal charging and discharging operation of the target battery, without disassembling the battery, a shear level mode (SHO) ultrasonic guided wave is excited to the electrodes of the target battery and the waveguide structure tightly coupled to the electrodes through a piezoelectric transducer. Simultaneously, the reflected and transmitted wave signals of the SHO ultrasonic guided wave are collected as raw monitoring data. The raw monitoring data undergoes high sampling rate acquisition and digital signal processing. Guided wave parameter features are extracted using correlation matching, envelope extraction, and time-base correction methods. These guided wave parameter features include propagation velocity, attenuation coefficient, time delay, and amplitude variation. The morphology of dendrite evolution is determined based on the preset correspondence between the guided wave parameter features and the metal deposition evolution state: if the propagation velocity... If the velocity fluctuates regularly and the attenuation coefficient does not show a continuous increasing trend, it is determined that the metal deposition / stripping process remains reversible and no obvious dendrite-induced deposition accumulation occurs on the electrode surface. If the propagation velocity shows an irreversible monotonous drift and the attenuation coefficient continuously increases, it is determined that there is irreversible metal deposition residue behavior in the battery, and its deposition morphology is manifested as dendrite growth or dead metal accumulation. Combining the dendrite evolution morphology, the difference between the characteristics of the guided wave parameters and the initial reference parameters, the historical monitoring data of the target battery, and the optical image of the electrode surface of the same period calibrated with the ultrasonic guided wave analysis results, based on the preset velocity drift threshold and attenuation change threshold, the dendrite growth stage (initial initiation, continuous growth, or metal accumulation stage) of the target battery is determined. This invention, by extracting the parameter characteristics of SHO ultrasonic guided waves and combining them with a preset correspondence, can clearly distinguish between reversible metal deposition / stripping processes and irreversible metal deposition residue behavior, achieving accurate differentiation of dendrite evolution morphology and avoiding the defect of battery state impacted by the risk of misjudgment of battery dendrites. Relying on the characteristics of SHO ultrasonic guided waves propagating along the electrodes and tightly coupled waveguide structures under normal battery conditions, it has high sensitivity to changes in the micro-morphology of the electrode surface, and can capture subtle physical changes in the early dendrite initiation stage, solving the problem of insufficient sensitivity of existing technologies in monitoring the initial formation of dendrites, and improving the sensitivity and real-time performance of dendrite growth monitoring.

[0020] Specifically, step S1 includes: S11, a piezoelectric transducer is used to excite SHO ultrasonic guided waves to the target battery, so that the SHO ultrasonic guided waves propagate along the battery electrodes of the target battery and the waveguide structure tightly coupled to the battery electrodes. S12, using a receiving transducer to acquire echo signal data of the SHO ultrasonic guided wave during propagation; wherein, the echo signal data includes reflected wave and transmitted wave signals of the SHO ultrasonic guided wave during propagation.

[0021] For example, a shear level (SHO) ultrasonic guided wave is excited by a piezoelectric transducer and propagates along the battery electrode and the waveguide structure tightly coupled to the electrode, and the reflected wave and transmitted wave signals are simultaneously collected by a receiving transducer arranged at a specific location.

[0022] In specific implementation, such as Figure 2 As shown, Figure 2 This is a schematic diagram of the physical structure of a battery dendrite monitoring system provided in an embodiment of the present invention. Figure 2 The system includes a battery cycle charging and discharging device, core battery components (working electrode, control electrode, reference electrode, zinc sheet), an ultrasonic system, a piezoelectric transducer, an optical mirror, a temperature sensor, a temperature receiver, and a display screen. A shear wave piezoelectric transducer with acoustic impedance matched to the target battery electrode / waveguide structure is selected. The center operating frequency must match the excitation requirements of the SHO guided wave (typically selected in the range of 100kHz-5MHz, optimized based on electrode thickness and waveguide structure dimensions to avoid coupling with other guided wave modes). The transducer size must be adapted to the battery electrode surface area to ensure energy transfer efficiency when tightly fitted to the electrode / waveguide structure. If directly exciting guided waves on the electrode surface is insufficient, a waveguide structure tightly coupled to the electrode (such as a thin metal sheet or ceramic waveguide) can be designed. The waveguide material must meet the requirements of low acoustic loss and strong adhesion to the electrode to ensure that the SHO guided wave propagates directionally along the electrode-waveguide composite structure and reduces energy scattering. A high-power signal generator (to drive the transducer to excite the guided wave), a high-sampling-rate data acquisition card (sampling rate not less than 10 times the center frequency of the guided wave to ensure distortion-free signal acquisition), and a temperature sensor (to monitor the environment and battery temperature in real time for subsequent signal temperature compensation) should be provided. The transmitting and receiving transducers are fixed at preset positions on the battery electrode or waveguide structure to form a directional guided wave propagation path (such as a straight path from the transmitter to the electrode surface to the receiver). The transducer and the electrode / waveguide surface are tightly bonded using an ultrasonic coupling agent (such as silicone grease or a special ultrasonic coupling adhesive) to eliminate air gaps and reduce acoustic wave reflection loss. The receiving transducer must be directly facing the direction of guided wave propagation to ensure effective capture of reflected and transmitted wave signals.

[0023] In the initial state before battery cycling (no zinc dendrite formation), the system is started for calibration: a preset excitation signal is output through the signal generator to drive the transmitting transducer to excite the SHO guided wave. The receiving transducer collects the initial echo signal (reflected wave and transmitted wave), and the signal amplitude, propagation time, waveform morphology, and other data are recorded as the reference signal for subsequent comparative analysis. A narrow pulse signal (such as a 5-10 period sinusoidal pulse train) is used as the excitation signal. The pulse width must match the propagation characteristics of the SHO guided wave to avoid mode confusion caused by signal broadening. The signal amplitude is set through the signal generator (adjusted according to the transducer power and battery structure to ensure sufficient guided wave energy without damaging the battery). The optimal excitation frequency of the SHO guided wave is determined through frequency sweep testing: the excitation signal frequency is gradually adjusted within a preset frequency range (100kHz-5MHz), and echo signals at different frequencies are collected. The frequency with the largest waveform amplitude and the highest mode purity (no interference from other guided wave modes) is selected as the fixed excitation frequency to ensure stable excitation of the SHO guided wave. Utilizing the propagation characteristics of SH0 guided waves (shear vibration along the structural plane with no thickness displacement), the polarization direction of the excitation signal is controlled (making the transducer vibration direction parallel to the electrode surface) to ensure that the excited guided wave is dominated by the SH0 mode, avoiding interference from other modes such as Lamb waves. Spectral analysis and dispersion curve matching are performed on the echo signals acquired during the initial calibration phase. By comparing with the theoretical dispersion curve of the SH0 guided wave, the proportion of the SH0 mode in the acquired guided wave signal is verified. If interference from other modes exists, optimization can be achieved by adjusting the excitation frequency, transducer arrangement angle, etc.

[0024] The receiving transducer synchronously acquires reflected waves (signals reflected from dendrites, defects, or structural boundaries on the electrode surface) and transmitted waves (signals penetrating the electrode / waveguide structure to reach the receiving end) from the SHO guided wave. The data acquisition card converts the analog signals into digital signals and transmits them to the data storage module in real time. Simultaneously with the acquisition of echo signals, auxiliary data such as the current number of charge / discharge cycles, real-time charge / discharge current / voltage, ambient temperature (acquired by a temperature sensor), and acquisition timestamp are recorded to ensure a one-to-one correspondence between the echo signal data and the battery's operating status and environmental conditions. During battery charge / discharge cycles, signal acquisition is performed at preset monitoring intervals (e.g., acquiring one set of data after each cycle, or continuous real-time acquisition) to ensure the continuity of echo signal data, providing a complete data chain for tracking the dynamic process of dendrite growth and dead metal accumulation.

[0025] Specifically, step S2 includes: S21, preprocess the echo signal data and extract the propagation time and amplitude information of the processed echo signal data; S22, calculate the guided wave parameter characteristics of the echo signal data based on the propagation time and amplitude information; wherein, the guided wave parameter characteristics include guided wave propagation velocity and attenuation coefficient.

[0026] For example, by performing high-precision timing and amplitude measurements on echo signal data, characteristics such as time delay, waveform distortion, and energy attenuation during guided wave propagation can be obtained. For instance, methods such as correlation matching, envelope extraction, and time-base correction can be used to accurately extract the propagation time and amplitude information of the guided wave, and the guided wave propagation velocity and attenuation coefficient can be calculated. Specifically, the echo signal data (reflected and transmitted wave signals) undergoes preprocessing (noise suppression, envelope extraction, time-base correction, and dispersion compensation, etc.) to eliminate interference factors and ensure signal stability and accuracy. For example, correlation matching algorithms are used to filter the echo signal data, filtering out irrelevant noise such as environmental vibration and electromagnetic interference, while retaining the effective signal components of guided wave propagation; signal envelopes are extracted using methods such as Hilbert transform to simplify the complex waveform structure and highlight the core characteristics of signal amplitude changes; time errors caused by equipment response delays and minor deviations in the propagation path are eliminated to ensure the accuracy of guided wave propagation time measurement; and for the waveform broadening phenomenon that may occur during the propagation of SHO guided waves, a preset dispersion curve is used for correction to restore the original waveform characteristics of the guided wave and avoid the influence of dispersion on parameter extraction. Based on preprocessed echo signal data, guided wave parameter features are extracted through quantitative calculation, directly correlated with the evolution state of dendrites and dead metal, and high-precision timing algorithms (such as cross-correlation algorithms) are used to extract the arrival times of reflected and transmitted waves, calculating the arrival time difference of the same signal in different monitoring periods. Combined with the known path length of guided wave propagation (the coupling propagation distance between the electrode and the waveguide structure), the guided wave propagation velocity is calculated, and the velocity change in different periods is derived. The peak amplitude of the signal envelope is extracted, and the amplitude attenuation in different periods under the same propagation path is calculated. The signal waveform is integrated to calculate the signal energy value, and the energy change rate characterizes the degree of guided wave energy attenuation, converting it into a quantitative attenuation coefficient. This embodiment of the invention uses a high-precision timing algorithm to extract the time difference between reflected and transmitted signals, and combines waveform amplitude and energy analysis to improve the measurement accuracy of guided wave propagation velocity and attenuation changes derived from time difference and amplitude changes, while suppressing noise and dispersion effects.

[0027] Specifically, if the waveguide parameter characteristics include waveguide propagation velocity and attenuation coefficient, then step S3 includes: S31, if the propagation speed of the guided wave exhibits a regular fluctuation synchronized with the battery charge-discharge cycle, and the attenuation coefficient does not show a continuous increasing trend, then based on the preset correspondence between the guided wave parameter characteristics and the deposition state, it is determined that the metal deposition / stripping process in the target battery remains reversible, and no obvious dendrite-induced deposition accumulation occurs on the electrode surface. S32, if the waveguide propagation velocity exhibits irreversible monotonic drift and the attenuation coefficient continues to increase, then based on the preset correspondence between waveguide parameter characteristics and deposition state, it is determined that there is irreversible metal deposition residue behavior in the target battery, and the metal deposition morphology is manifested as dendrite growth or dead metal accumulation.

[0028] For example, this invention improves the characterization accuracy of propagation velocity and attenuation changes on electrode surface dendrite growth through calibration and multi-parameter fitting, thereby more accurately and in real-time reflecting the dendrite initiation, growth, and accumulation process. Specifically, the formation of zinc dendrites causes measurable changes in guided wave propagation velocity, while irreversible accumulation of dead zinc dendrites leads to a continuous increase in guided wave attenuation. For instance, using the dendrite growth state (such as dendrite size and distribution density) and dead zinc accumulation on the electrode surface observed by optical microscopy as calibration benchmarks, a mapping relationship between guided wave parameter changes and dendrite / dead zinc states is established. Fitting analysis is performed on multiple parameters such as propagation velocity changes and attenuation coefficients to eliminate abnormal parameter values ​​caused by random errors, improving the characterization accuracy of characteristic parameters for early dendrite initiation and gradual dead zinc accumulation. This embodiment of the invention analyzes the changes in guided wave propagation velocity and attenuation characteristics with the number of cycles or time, judges the growth state of zinc dendrites and the degree of dead zinc accumulation based on their changing trends, and combines the observation results of the electrode surface by optical microscopy to achieve qualitative and quantitative monitoring of initial dendrite formation, providing a basis for battery safety assessment and lifespan prediction.

[0029] Specifically, step S4 includes: S41, Align the waveguide parameter characteristics and the historical monitoring data of the target battery according to the number of charge-discharge cycles or timestamps, and calculate the change amount and trend of the waveguide parameter characteristics; S42, the dendrite growth stage of the target battery is determined based on the change amount and trend, the dendrite evolution morphology, the synchronous electrode surface image, and the preset dendrite growth stage characteristic state.

[0030] For example, the ultrasonic guided wave analysis results are correlated and calibrated with the electrode surface images obtained by optical microscopy to perform image-based and quantitative monitoring of the initial dendrite formation process. For instance, the guided wave parameters (propagation velocity, attenuation coefficient) of the current monitoring cycle are extracted and aligned with historical monitoring data (e.g., historical propagation velocity, historical attenuation coefficient) according to the number of cycles or time dimension. The change amount of guided wave parameters (current value - initial reference value) and the rate of change (parameter change per unit cycle / time) are calculated. Simultaneously, optical microscopic images of the electrode surface from the same period are retrieved, and the size, density, and morphological characteristics of the protrusions in the images are labeled. Based on the change amount and trend, the dendrite evolution morphology, the concurrent electrode surface images, and the preset dendrite growth stage characteristics, the dendrite growth stage of the target battery is determined.

[0031] It is worth noting that, taking the zinc dendrite growth stage as an example, it includes the dendrite-free stage, the initial initiation stage, the rapid growth stage, and the dead zinc accumulation stage. The dendrite-free stage is characterized by the following features: the dendrite formation is completely reversible during the zinc plating / stripping process; after charge-discharge cycles, no deposited protrusions remain on the electrode surface, and all zinc deposits disappear during the stripping process; the propagation speed of the guided wave parameters is close to the initial reference value, the attenuation coefficient shows no significant change, and the guided wave parameters exhibit regular reversible fluctuations with charge-discharge cycles (synchronized with zinc deposition / stripping); historical monitoring data shows a high degree of overlap in the guided wave parameter curves over multiple cycles, with no obvious drift trend, and the cumulative change in parameters approaches 0; the electrode surface in the concurrent electrode surface image is flat, without any protrusions or irregular deposits observable by the naked eye or optical microscope, only exhibiting a uniform morphology of normal zinc deposition / stripping.

[0032] The initial dendrite growth stage is characterized by the following features: irreversible zinc deposition in the dendrites, with a small number of tiny protrusions remaining after charge-discharge cycles, not completely stripped away; slight irreversible drift in propagation velocity (e.g., drift amount 0.5%-3%), slow increase in attenuation coefficient (e.g., increase rate ≤0.2% / cycle), and slightly increased parameter fluctuation amplitude compared to the non-dendritic stage, but still mainly stable; historical monitoring data show that the waveguide parameters have shown a continuous small deviation from the initial reference value, with the change accumulating slowly with the number of cycles, without an accelerating growth trend; in the same period, sporadic tiny protrusions (e.g., size <1μm, density <5 / 100μm2) appear on the electrode surface in the electrode surface image, with irregular protrusion morphology but not connected to each other, posing no obvious risk of puncturing the diaphragm.

[0033] The characteristics of the dendrite growth stage during the rapid growth phase are as follows: zinc deposition in the dendrites is completely irreversible, the dendritic structure continues to exist and grow, cannot be eliminated by charge-discharge cycles, and gradually forms a tree-like extension structure; in the characteristics of the guided wave parameters, the propagation velocity drifts significantly and irreversibly, the attenuation coefficient increases rapidly, the absolute value of the slope of the parameter change curve increases significantly, and the degree of waveform distortion intensifies; in the historical monitoring data, the cumulative change of the guided wave parameters increases rapidly, and compared with the previous stage (initial germination), the rate of change increases by ≥50%, and the parameter stability across cycles deteriorates (the fluctuation amplitude increases); in the electrode surface image at the same time, the number and size of the protrusions on the electrode surface increase significantly, forming an obvious dendritic structure, some dendrites connect with each other, and begin to extend towards the electrolyte, close to the diaphragm.

[0034] The dendrite growth stage of the dead zinc accumulation stage is characterized by: mature dendrite structure and partial fracture, forming a large amount of dead zinc (residual deposits that cannot participate in the charge and discharge reaction), with irreversible characteristics dominating; in the characteristics of guided wave parameters, the propagation velocity drift tends to be gradual (the rate of increase slows down after the drift amount is ≥10%), the attenuation coefficient continues to increase at a high level (the rate of increase is ≥1% / cycle), and even signal attenuation saturation occurs (the amplitude is difficult to capture accurately); in the historical monitoring data, the cumulative change of guided wave parameters tends to stabilize after reaching a peak, or there may be a sudden change in parameters due to dendrites piercing the diaphragm (such as a sudden drop in propagation velocity and a sudden increase in attenuation coefficient); in the same period, the electrode surface image shows densely distributed dendrites with large size (>10μm), some dendrites piercing the diaphragm (if they do not pierce, they are in the state of touching the diaphragm), and a large number of fractured dendrite residues (dead zinc) on the electrode surface, with disordered deposition morphology.

[0035] Furthermore, after determining the dendrite growth stage of the target cell, the method further includes: S5, a risk warning is given to the target battery based on the preset waveguide parameter characteristic threshold and the dendrite growth stage.

[0036] For example, the results of ultrasonic guided wave analysis are correlated and calibrated with electrode surface images obtained by optical microscopy to perform image-based and quantitative monitoring of the initial dendrite formation process. Simultaneously, a warning criterion is constructed based on preset guided wave parameter characteristic thresholds (characteristic thresholds for propagation velocity drift and attenuation changes). When the detection results (dendrite growth stage) exceed the safe range, a warning message is output to reduce safety risks such as zinc dendrites piercing the separator and causing short circuits. For instance, the guided wave characteristic parameters are converted into battery safety status and fault risk levels; when the monitoring results exceed the set thresholds, the signal is fed back to the BMS to execute corresponding charging / discharging strategy adjustments or protection actions.

[0037] This invention discloses a method for monitoring battery dendrites based on ultrasonic guided waves. The method involves exciting an SHO ultrasonic guided wave onto a target battery to obtain echo signal data of the SHO ultrasonic guided wave; extracting guided wave features from the echo signal data to obtain guided wave parameter features; determining the dendrite evolution morphology of the target battery based on the guided wave parameter features and a preset correspondence between the guided wave parameter features and the deposition state; and determining the dendrite growth stage of the target battery based on the dendrite evolution morphology, the guided wave parameter features, historical monitoring data of the target battery, and concurrent electrode surface images. This invention, by extracting the parameter characteristics of SHO ultrasonic guided waves and combining them with a preset correspondence, can clearly distinguish between reversible metal deposition / stripping processes and irreversible metal deposition residue behavior, achieving accurate differentiation of dendrite evolution morphology and avoiding the defect of battery state impacted by the risk of misjudgment of battery dendrites. Relying on the characteristics of SHO ultrasonic guided waves propagating along the electrodes and tightly coupled waveguide structures under normal battery conditions, it has high sensitivity to changes in the micro-morphology of the electrode surface, and can capture subtle physical changes in the early dendrite initiation stage, solving the problem of insufficient sensitivity of existing technologies in monitoring the initial formation of dendrites, and improving the sensitivity and real-time performance of dendrite growth monitoring.

[0038] See Figure 3 , Figure 3 This is a schematic diagram of a battery dendrite monitoring system 10 based on ultrasonic guided waves provided in an embodiment of the present invention. The battery dendrite monitoring system 10 based on ultrasonic guided waves includes: The echo signal acquisition module 11 is used to excite SH0 ultrasonic guided waves to the target battery and acquire the echo signal data of the SH0 ultrasonic guided waves. The waveguide parameter extraction module 12 is used to extract waveguide features from the echo signal data to obtain the waveguide parameter features of the echo signal data. Dendrite type determination module 13 is used to determine the dendrite evolution morphology of the target cell based on the waveguide parameter characteristics and the preset correspondence between the waveguide parameter characteristics and the deposition state. The growth stage determination module 14 is used to determine the dendrite growth stage of the target battery based on the dendrite evolution morphology, the waveguide parameter characteristics, the historical monitoring data of the target battery and the synchronous electrode surface image.

[0039] Furthermore, the battery dendrite monitoring system 10 based on ultrasonic guided waves also includes: The battery risk warning module is used to provide risk warnings to the target battery based on preset waveguide parameter characteristic thresholds and the dendrite growth stage.

[0040] The battery dendrite monitoring system 10 based on ultrasonic guided waves provided in this embodiment of the invention can realize all the processes of the battery dendrite monitoring method based on ultrasonic guided waves in the above embodiment. The functions and technical effects of each module in the system are the same as those of the battery dendrite monitoring method based on ultrasonic guided waves in the above embodiment, and will not be repeated here.

[0041] See Figure 4 , Figure 4 This is a schematic diagram of the structure of a battery dendrite monitoring device 20 based on ultrasonic guided waves provided in an embodiment of the present invention. The battery dendrite monitoring device 20 based on ultrasonic guided waves in this embodiment includes: a processor 21, a memory 22, and a computer program stored in the memory 22 and executable on the processor 21. When the processor 21 executes the computer program, it implements the steps in the above-described embodiment of the battery dendrite monitoring method based on ultrasonic guided waves. Alternatively, when the processor 21 executes the computer program, it implements the functions of each module in the above-described embodiment of the battery dendrite monitoring system based on ultrasonic guided waves.

[0042] For example, the computer program may be divided into one or more modules, which are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the ultrasonic guided wave-based battery dendrite monitoring device 20.

[0043] The ultrasonic guided wave-based battery dendrite monitoring device 20 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The ultrasonic guided wave-based battery dendrite monitoring device 20 may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will understand that the schematic diagram is merely an example of the ultrasonic guided wave-based battery dendrite monitoring device 20 and does not constitute a limitation on the ultrasonic guided wave-based battery dendrite monitoring device 20. It may include more or fewer components than shown, or combine certain components, or use different components. For example, the ultrasonic guided wave-based battery dendrite monitoring device 20 may also include input / output devices, network access devices, buses, etc.

[0044] The processor 21 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 21 is the control center of the ultrasonic guided wave-based battery dendrite monitoring device 20, connecting all parts of the device using various interfaces and lines.

[0045] The memory 22 can be used to store the computer program and / or modules. The processor 21 implements various functions of the ultrasonic guided wave-based battery dendrite monitoring device 20 by running or executing the computer program and / or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0046] The module integrated into the ultrasonic guided wave-based battery dendrite monitoring device 20, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by the processor 21, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately added to or subtracted from the content as required by the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0047] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0048] Furthermore, embodiments of the present invention also provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the battery dendrite monitoring method based on ultrasonic guided waves described above.

[0049] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for monitoring battery dendrites based on ultrasonic guided waves, characterized in that, include: SH0 ultrasonic guided waves are excited to the target battery, and the echo signal data of the SH0 ultrasonic guided waves are acquired; The guided wave feature is extracted from the echo signal data to obtain the guided wave parameter features of the echo signal data; The dendritic evolution morphology of the target cell is determined based on the characteristics of the waveguide parameters and the preset correspondence between the characteristics of the waveguide parameters and the deposition state. The dendrite growth stage of the target battery is determined based on the dendrite evolution morphology, the characteristics of the waveguide parameters, the historical monitoring data of the target battery, and the synchronous electrode surface images.

2. The battery dendrite monitoring method based on ultrasonic guided waves as described in claim 1, characterized in that, The step of exciting an SHO ultrasonic guided wave onto the target battery and acquiring the echo signal data of the SHO ultrasonic guided wave includes: A piezoelectric transducer is used to excite SHO ultrasonic guided waves to the target battery, and the SHO ultrasonic guided waves propagate along the battery electrodes of the target battery and the waveguide structure tightly coupled to the battery electrodes. The echo signal data of the SHO ultrasonic guided wave during its propagation is acquired using a receiving transducer; wherein, the echo signal data includes the reflected wave and transmitted wave signals of the SHO ultrasonic guided wave during its propagation.

3. The battery dendrite monitoring method based on ultrasonic guided waves as described in claim 1, characterized in that, The step of extracting guided wave features from the echo signal data to obtain the guided wave parameter features of the echo signal data includes: The echo signal data is preprocessed to extract the propagation time and amplitude information of the processed echo signal data; The waveguide parameter characteristics of the echo signal data are calculated based on the propagation time and amplitude information; wherein, the waveguide parameter characteristics include waveguide propagation velocity and attenuation coefficient.

4. The battery dendrite monitoring method based on ultrasonic guided waves as described in claim 1, characterized in that, If the waveguide parameters include waveguide propagation velocity and attenuation coefficient... The step of determining the dendritic evolution morphology of the target cell based on the waveguide parameter characteristics and the preset correspondence between the waveguide parameter characteristics and the deposition state includes: If the propagation speed of the guided wave exhibits a regular fluctuation synchronized with the battery charge-discharge cycle, and the attenuation coefficient does not show a continuous increasing trend, then based on the preset correspondence between the guided wave parameter characteristics and the deposition state, it is determined that the metal deposition / stripping process in the target battery remains reversible, and no obvious dendrite-induced deposition accumulation occurs on the electrode surface. If the propagation velocity of the guided wave exhibits an irreversible monotonic drift and the attenuation coefficient continues to increase, then based on the preset correspondence between the guided wave parameter characteristics and the deposition state, it is determined that there is irreversible residual metal deposition behavior in the target battery, and the metal deposition morphology is manifested as dendrite growth or dead metal accumulation.

5. The battery dendrite monitoring method based on ultrasonic guided waves as described in claim 1, characterized in that, The step of determining the dendrite growth stage of the target battery based on the dendrite evolution morphology, the waveguide parameter characteristics, the historical monitoring data of the target battery, and concurrent electrode surface images includes: Align the waveguide parameter characteristics and the historical monitoring data of the target battery according to the number of charge-discharge cycles or timestamps, and calculate the change amount and trend of the waveguide parameter characteristics; The dendrite growth stage of the target battery is determined based on the change amount and trend, the dendrite evolution morphology, the synchronous electrode surface image, and the preset dendrite growth stage characteristic state.

6. The battery dendrite monitoring method based on ultrasonic guided waves as described in claim 1, characterized in that, After determining the dendrite growth stage of the target cell, the method further includes: Risk warnings are issued for the target battery based on preset waveguide parameter characteristic thresholds and the dendrite growth stage.

7. A battery dendrite monitoring system based on ultrasonic guided waves, characterized in that, include: The echo signal acquisition module is used to excite SHO ultrasonic guided waves to the target battery and acquire the echo signal data of the SHO ultrasonic guided waves. The waveguide parameter extraction module is used to extract waveguide features from the echo signal data to obtain the waveguide parameter features of the echo signal data. The dendrite type determination module is used to determine the dendrite evolution morphology of the target cell based on the waveguide parameter characteristics and the preset correspondence between the waveguide parameter characteristics and the deposition state. The growth stage determination module is used to determine the dendrite growth stage of the target battery based on the dendrite evolution morphology, the waveguide parameter characteristics, the historical monitoring data of the target battery, and the synchronous electrode surface image.

8. A battery dendrite monitoring device based on ultrasonic guided waves, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the battery dendrite monitoring method based on any one of claims 1-6.

9. A computer program product, characterized in that, The computer program product is stored in a storage medium and is executed by at least one processor to implement the steps of the battery dendrite monitoring method based on ultrasonic guided waves as described in any one of claims 1-6.

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