A lithium precipitation online monitoring method and device based on multi-signal coupling

Abstract

The application discloses a lithium battery lithium precipitation online monitoring method and device based on multi-signal coupling, and relates to the field of lithium ion battery safety monitoring. The method comprises the following steps: collecting strain data, impedance spectrum data, capacity data, voltage data and ultrasonic signal intensity diagrams of a lithium battery to be measured; calculating the differential of strain and voltage and the differential of capacity and voltage respectively, generating a differential strain curve and a differential capacity curve; extracting the impedance modulus in the medium frequency region from the impedance spectrum data, drawing an impedance modulus curve in the medium frequency region, calculating the differential of the impedance modulus and voltage, and generating a differential curve of the impedance modulus in the medium frequency region; and identifying the occurrence and evolution stage of lithium precipitation according to the evolution characteristics of the differential strain curve, the differential capacity curve, the impedance modulus curve in the medium frequency region and the differential curve of the impedance modulus in the medium frequency region, and combining the color change of the ultrasonic signal intensity diagram. The application overcomes the limitations of single signal monitoring methods by coupling electrochemical impedance, strain and ultrasonic signals.

Description

Technical Field

[0001] This invention relates to the field of lithium-ion battery safety monitoring, and more specifically, to an online monitoring method and apparatus for lithium plating in lithium batteries based on multi-signal coupling. Background Technology

[0002] With the widespread application of lithium-ion batteries, their safety has become increasingly important. Lithium plating is one of the key factors affecting lithium battery safety. Under conditions such as fast charging, overcharging, and low-temperature charging, lithium ions easily deposit as metallic lithium on the surface of the negative electrode. Lithium plating not only causes irreversible capacity loss, but the resulting lithium dendrites can also pierce the separator, triggering internal short circuits or even thermal runaway. Therefore, accurately understanding the evolution process of lithium plating and developing reliable detection methods are crucial.

[0003] Existing lithium plating detection methods are mainly divided into three categories: surface morphology analysis, chemical analysis, and electrochemical methods. Morphology analysis methods such as scanning electron microscopy, and chemical analysis methods such as nuclear magnetic resonance and X-ray photoelectron spectroscopy, all require disassembly of the battery, which introduces irreversible damage and makes it difficult to track the dynamic evolution of lithium plating in situ.

[0004] Among non-destructive testing methods, electrochemical techniques such as incremental capacity analysis, differential voltage analysis, three-electrode method, and electrochemical impedance spectroscopy are widely used. However, incremental capacity analysis and differential voltage analysis are difficult to effectively identify lithium stripping plateaus caused by small amounts of lithium plating; the reference electrode introduced by the three-electrode method may damage the structure of commercial batteries and has drift problems after long-term use; traditional electrochemical impedance spectroscopy has a long testing time and cannot be monitored in real time during charge and discharge; although dynamic electrochemical impedance spectroscopy can track impedance changes during charge and discharge, the simple impedance characteristics are easily affected by factors such as temperature and charging rate.

[0005] Detection based on mechanical deformation signals offers a novel approach to lithium plating identification. Battery thickness changes can serve as an indicator for lithium plating detection. Using fiber optic sensors with high resolution, high sensitivity, and electromagnetic interference resistance, strain changes related to lithium plating can be monitored in real time. However, current research still lacks sufficient evidence to reliably link mechanical responses to electrochemical processes.

[0006] In addition, ultrasonic testing provides an intuitive, non-destructive testing method. It utilizes the differences in wave velocity and attenuation of sound waves in different media inside the battery to reveal internal structural changes caused by lithium plating or gas production. However, the internal structure of batteries is complex, the spatial resolution of ultrasonic testing is limited, and the signal is susceptible to interference, thus limiting the accurate identification of lithium plating.

[0007] In summary, existing single detection methods such as electrochemical, mechanical, and acoustic detection each have their limitations, making it difficult to achieve accurate online monitoring of lithium plating status in lithium batteries. There is an urgent need to develop an online lithium plating monitoring method and device based on multi-signal coupling. By integrating multiple characteristics from electrochemical, mechanical, and acoustic sources, this approach can overcome the shortcomings of single signals and effectively improve the real-time performance and reliability of lithium plating detection.

[0008] No effective solutions have yet been proposed to address the problems in the relevant technologies. Summary of the Invention

[0009] To address the problems in related technologies, this invention proposes an online monitoring method and device for lithium plating in lithium batteries based on multi-signal coupling, in order to overcome the aforementioned technical problems existing in the prior art.

[0010] Therefore, the specific technical solution adopted by the present invention is as follows:

[0011] According to one aspect of the present invention, an online monitoring method for lithium plating in lithium batteries based on multi-signal coupling is provided, the method comprising:

[0012] S1. Collect strain data, impedance spectrum data, capacity data, voltage data, and ultrasonic signal intensity diagram of the lithium battery under test;

[0013] S2. Based on the strain data, capacity data, and voltage data, calculate the differential of strain with respect to voltage and the differential of capacity with respect to voltage, respectively, and generate differential strain curves and differential capacity curves.

[0014] S3. Extract the mid-frequency impedance modulus from the impedance spectrum data, plot the mid-frequency impedance modulus curve, calculate the derivative of the impedance modulus with respect to voltage, and generate the mid-frequency impedance modulus differential curve.

[0015] S4. Based on the evolution characteristics of the differential strain curve, differential capacity curve, mid-frequency impedance modulus curve, and mid-frequency impedance modulus differential curve, combined with the color change of the ultrasonic signal intensity map, the occurrence and evolution stages of lithium plating are identified to achieve online monitoring of lithium plating in lithium batteries.

[0016] According to another aspect of the present invention, an online monitoring device for lithium plating in lithium batteries based on multi-signal coupling is also provided, the device comprising:

[0017] The data acquisition module is used to acquire strain data, impedance spectrum data, capacity data, voltage data, and ultrasonic signal intensity maps of the lithium battery under test.

[0018] The differential curve generation module is used to calculate the differential of strain with respect to voltage and the differential of capacity with respect to voltage based on strain data, capacity data and voltage data, and generate differential strain curves and differential capacity curves.

[0019] The feature extraction and differentiation module is used to extract the mid-frequency impedance modulus from the impedance spectrum data, plot the mid-frequency impedance modulus curve, calculate the derivative of the impedance modulus with respect to voltage, and generate the mid-frequency impedance modulus differentiation curve.

[0020] The multi-stage evolution identification module is used to identify the occurrence and evolution stages of lithium plating based on the evolution characteristics of differential strain curves, differential capacity curves, mid-frequency impedance modulus curves, and mid-frequency impedance modulus differential curves, combined with the color changes of ultrasonic signal intensity maps, so as to realize online monitoring of lithium plating in lithium batteries.

[0021] The beneficial effects of this invention are as follows:

[0022] 1. This invention overcomes the limitations of single-signal monitoring methods by coupling three signals: electrochemical impedance, strain, and ultrasound. Electrochemical impedance reflects the kinetic changes of interfacial reactions, strain reflects the mechanical response of battery volume, and ultrasound reflects changes in internal structure. The three signals corroborate and complement each other, enabling accurate tracking of lithium plating.

[0023] 2. This invention establishes multi-signal feature criteria for each stage of lithium plating evolution, realizing online monitoring and stage identification of lithium plating.

[0024] 3. This invention can accurately identify the starting moment of lithium nucleation by simultaneously judging two independent signals: the second decrease in impedance modulus in the mid-frequency region and the flattening of the differential strain curve, thus avoiding the misjudgment that may occur with a single signal.

[0025] 4. This invention utilizes the attenuation and recovery characteristics of ultrasonic signals during the charging and discharging process to effectively distinguish between reversible lithium plating and irreversible gas generation, providing an additional verification method for the accurate identification of lithium plating.

[0026] 5. This invention eliminates the need to disassemble the battery, enabling non-destructive, in-situ, and real-time monitoring. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is one of the flowcharts of an online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to an embodiment of the present invention;

[0029] Figure 2 This is a schematic block diagram of an online monitoring device for lithium plating in lithium batteries based on multi-signal coupling, according to an embodiment of the present invention.

[0030] Figure 3 This is a second flowchart of an online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to an embodiment of the present invention;

[0031] Figure 4 This is a schematic diagram of the experimental platform setup in an online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to an embodiment of the present invention;

[0032] Figure 5 This is a schematic diagram of the arrangement of fiber Bragg grating strain sensors on the battery surface in an online monitoring method for lithium plating of lithium batteries based on multi-signal coupling according to an embodiment of the present invention.

[0033] Figure 6 This is a graph showing the evolution of ultrasonic signal intensity during the charging and discharging process in an online monitoring method for lithium plating in lithium batteries based on multi-signal coupling, according to an embodiment of the present invention.

[0034] Figure 7 This is a graph showing the strain ε and the first derivative of strain with respect to voltage dε / dV as a function of voltage V when the lithium battery is charged to 4.2V, 4.4V, 4.5V, 4.6V and 4.7V, according to an embodiment of the present invention.

[0035] Figure 8 This is a graph showing the first derivative of capacity with respect to voltage dQ / dV as a function of voltage V when the lithium battery is charged to 4.2V, 4.4V, 4.5V, 4.6V and 4.7V according to an embodiment of the present invention.

[0036] Figure 9 This is a comparison diagram of the evolution of dynamic electrochemical impedance spectroscopy Nyquist plots in an online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to an embodiment of the present invention. Figure 9 (a) Comparison of the evolution of Nyquist plots of dynamic electrochemical impedance spectroscopy for lithium batteries under normal charging to 4.2V. Figure 9 (b) Comparison of the evolution of the Nyquist plot of dynamic electrochemical impedance spectroscopy after overcharging to 4.7V;

[0037] Figure 10 This is a graph showing the evolution of the impedance modulus and its differential curve in the mid-frequency region (20Hz) with voltage, and a graph showing the division of lithium plating stages, in an online monitoring method for lithium battery lithium plating based on multi-signal coupling according to an embodiment of the present invention.

[0038] Figure 11This is a coupling analysis diagram of the differential capacity curve, differential strain curve, and mid-frequency impedance modulus curve in an online monitoring method for lithium plating of lithium batteries based on multi-signal coupling according to an embodiment of the present invention.

[0039] Figure 12 These are scanning electron microscope (SEM) images of the graphite anode surface under different overcharge conditions in an online monitoring method for lithium plating in lithium batteries based on multi-signal coupling, according to an embodiment of the present invention. Figure 12 (a) A scanning electron microscope image of the graphite anode surface showing a clean, impurity-free lithium intercalation stage during a 4.2V overcharge. Figure 12 (b) Scanning electron microscope image of lithium nucleation stage corresponding to the appearance of nucleated lithium deposits on the graphite anode surface during 4.5V overcharging. Figure 12 (c) Scanning electron microscope image of the lithium growth stage corresponding to the appearance of more nucleated lithium deposits (dendritic lithium dendrites) on the graphite anode surface during 4.7V overcharging.

[0040] In the picture:

[0041] 1. Data acquisition module; 2. Differential curve generation module; 3. Feature extraction and differential processing module; 4. Multi-stage evolution recognition module. Detailed Implementation

[0042] To further illustrate the various embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention. These drawings are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementation methods and the advantages of the present invention.

[0043] According to an embodiment of the present invention, a method and apparatus for online monitoring of lithium plating in lithium batteries based on multi-signal coupling are provided.

[0044] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments, such as... Figure 1 As shown, according to an embodiment of the present invention, a lithium battery lithium plating online monitoring method based on multi-signal coupling includes:

[0045] S1. Collect strain data, impedance spectrum data, capacity data, voltage data, and ultrasonic signal intensity diagram of the lithium battery under test;

[0046] In this optional embodiment, S1 includes:

[0047] S11. Using a fiber Bragg grating strain sensor deployed in the central region of the surface of the lithium battery under test, the surface deformation of the lithium battery under test during charging and discharging is monitored in real time to obtain strain data.

[0048] S12. During the charging and discharging process of the lithium battery under test, dynamic electrochemical impedance spectroscopy and charge-discharge tests are performed simultaneously to acquire impedance spectrum data in real time and record the corresponding capacity and voltage data.

[0049] In this optional embodiment, during dynamic electrochemical impedance spectroscopy testing, a printed circuit board with flexible printed circuit pins is fixedly connected to the electrodes of the lithium battery under test by welding.

[0050] S13. When the lithium battery under test is charged to different preset state of charge nodes, ultrasonic detection is performed to acquire ultrasonic signals, and the ultrasonic signals are processed to generate an ultrasonic signal intensity map characterizing the intensity of ultrasonic transmission signals at different positions of the lithium battery under test.

[0051] In this optional embodiment, the ultrasonic detection adopts a one-transmitter-one-receiver probe arrangement, with the transmitting probe and the receiving probe placed on both sides of the lithium battery under test, and both the probe and the lithium battery under test are immersed in the coupling medium; based on the attenuation of the ultrasonic signal intensity during charging and the recovery of the ultrasonic signal intensity during discharging, the reversible lithium plating phenomenon and the irreversible gas generation phenomenon are distinguished.

[0052] It should be added that the fiber Bragg grating strain sensor is placed in the central region of the battery surface, and adhesive is used to tightly bond the sensor to the battery surface to ensure that the sensor can accurately sense strain changes on the battery surface. The fiber Bragg grating strain sensor, placed in the central region of the battery surface, has a peak reflectivity of not less than 94%, a 3dB bandwidth of 0.2~0.3nm, and a side-mode rejection ratio of not less than 23dB. For example, in the embodiment of this invention, the FBG sensor used has a peak reflectivity of 94.35%, a 3dB bandwidth of 0.239nm, and a side-mode rejection ratio of 23.667dB to ensure that the grating has a high signal-to-noise ratio and excellent wavelength selectivity, guaranteeing demodulation stability. The black dots visible on the fiber represent the main sensing area. The fiber is connected to the demodulator to record the strain signal during the charging and discharging process in real time.

[0053] A printed circuit board (PCB) is used in conjunction with a flexible printed circuit board (FPC) to connect to the battery electrodes. To reduce contact resistance and improve measurement stability, four pins on the FPC are directly soldered to the battery electrodes; the two pins closest to the chip are connected to the positive electrode, and the other two pins are connected to the negative electrode. Dynamic electrochemical impedance spectroscopy (EIS) is performed simultaneously during battery charging and discharging, with a frequency range of 0.1Hz to 7800Hz, to acquire impedance spectrum data in real time and track the dynamic evolution of the interface process during charging and discharging. The PCB is connected to a computer via a data cable, and the impedance data is recorded in real time using the accompanying software.

[0054] A single-transmitter, single-receiver probe setup was adopted, with the transmitting and receiving probes positioned on opposite sides of the battery. Both the probes and the battery were immersed in a silicone oil coupling medium to ensure effective ultrasonic signal transmission. Ultrasonic detection was performed with the battery at 3.0V, 50% SOC, 4.2V, 4.7V, and subsequently discharged to 3.0V, acquiring ultrasonic signal intensity images, such as... Figure 6 As shown.

[0055] S2. Based on the strain data, capacity data, and voltage data, calculate the differential of strain with respect to voltage and the differential of capacity with respect to voltage, respectively, and generate differential strain curves and differential capacity curves.

[0056] It is necessary to supplement this by using strain data acquired by the fiber optic demodulator and capacity and voltage data acquired by the battery cycle meter to plot the curve of strain ε versus voltage V. Simultaneously, the first derivative of strain with respect to voltage, dε / dV, and the first derivative of capacity with respect to voltage, dQ / dV, are calculated using interpolation differentiation methods. Differential strain curves and differential capacity curves are then plotted, and the variation laws of strain, differential strain, and differential capacity are analyzed. Figure 7 As shown, ε represents strain, V represents voltage, Q represents capacity, dε / dV represents the first derivative of strain with respect to voltage, and dQ / dV represents the first derivative of capacity with respect to voltage.

[0057] S3. Extract the mid-frequency impedance modulus from the impedance spectrum data, plot the mid-frequency impedance modulus curve, calculate the derivative of the impedance modulus with respect to voltage, and generate the mid-frequency impedance modulus differential curve.

[0058] It should be added that Nyquist plots of dynamic electrochemical impedance spectroscopy were obtained using the PCB and FPC for normal charging to 4.2V and overcharging to 4.7V. (See attached image.) Figure 9 As shown, Z´ represents the real part of the impedance, and Z´´ represents the imaginary part of the impedance. Subsequently, the mid-frequency impedance modulus |Z| is extracted from the dynamic electrochemical impedance spectroscopy data, where the mid-frequency range is 1Hz-1kHz, represented by 20Hz. The curve of |Z| versus voltage V is plotted. Simultaneously, the first derivative of the impedance modulus with respect to voltage, d|Z| / dV, is calculated using interpolation differentiation, and the d|Z| / dV curve is plotted, as shown below. Figure 10 As shown. Based on the evolution characteristics of |Z| and d|Z| / dV, including the decreasing, increasing, and decreasing slope characteristics of the |Z| curve, and the positive and negative transitions and numerical changes of the d|Z| / dV curve, the impedance evolution during the overcharging process is divided into four stages.

[0059] S4. Based on the evolution characteristics of the differential strain curve, differential capacity curve, mid-frequency impedance modulus curve, and mid-frequency impedance modulus differential curve, combined with the color change of the ultrasonic signal intensity map, the occurrence and evolution stages of lithium plating are identified to achieve online monitoring of lithium plating in lithium batteries.

[0060] In this optional embodiment, the evolution characteristics of the differential strain curve, differential capacity curve, mid-frequency impedance modulus curve, and mid-frequency impedance modulus differential curve include: fluctuation and flattening characteristics of the differential strain curve, peak position change and flattening characteristics of the differential capacity curve, and rising, falling, and slope change characteristics of the mid-frequency impedance modulus.

[0061] In this optional embodiment, the evolution stages of lithium plating include: normal lithium intercalation stage, late lithium intercalation stage, lithium nucleation stage, and lithium growth stage;

[0062] During the normal lithium intercalation stage, the value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage is less than the preset threshold, the impedance modulus in the mid-frequency region shows a decreasing trend, the differential strain curve and differential capacity curve show fluctuation characteristics, and the color of the ultrasonic signal intensity map shifts towards the first preset color direction.

[0063] In the final stage of lithium intercalation, the differential curve of the impedance modulus in the mid-frequency region with respect to voltage becomes positive, the impedance modulus in the mid-frequency region shows an upward trend, the differential strain curve and differential capacity curve reach the last characteristic peak, and the ultrasonic signal intensity map maintains the target signal intensity characteristics.

[0064] During the lithium nucleation stage, the value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage is once again less than the preset threshold, the impedance modulus in the mid-frequency region shows a downward trend again, the differential strain curve and differential capacity curve change from fluctuating and peak characteristics to flat characteristics, and the ultrasonic signal intensity map begins to show local signal attenuation.

[0065] During the lithium growth stage, the differential strain curve and differential capacity curve maintain a flat characteristic. The absolute value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage is less than the absolute value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage during the lithium nucleation stage, and is less than the preset threshold. The slope of the decrease of the impedance modulus in the mid-frequency region becomes slower, and the second preset color appears in the ultrasonic signal intensity graph.

[0066] It should be added that the appearance of the second preset color area indicates that the local ultrasonic signal intensity of the battery has dropped to a low intensity, that is, the corresponding area has formed a relatively obvious lithium plating or irreversible gas production, resulting in a decrease in ultrasonic signal intensity; the target signal intensity feature is a high signal intensity feature, mainly manifested in the first preset color area accounting for a large proportion; the local signal attenuation is manifested in some of the first preset color areas starting to migrate to the second preset color area, but a large area of ​​low intensity has not yet been formed.

[0067] In this optional embodiment, the starting time of the lithium nucleation stage is determined by identifying the turning point where the impedance modulus in the mid-frequency region changes from an upward trend to a downward trend again, and the turning point where the differential strain curve and differential capacity curve change from fluctuating characteristics to flat characteristics.

[0068] In this optional embodiment, the criterion for determining whether lithium plating has transitioned from the lithium nucleation stage to the lithium growth stage is: during the period when the differential strain curve and differential capacity curve maintain flat characteristics, the inflection point of the range of decreasing slope of the impedance modulus in the mid-frequency region is identified.

[0069] It should be added that the range of change is from about -2.5με / V to about -0.5με / V as the differential of the impedance modulus with respect to voltage increases.

[0070] In this optional embodiment, if the ultrasonic signal intensity map shows a second preset color during charging and then recovers to a third preset color during subsequent discharging, it is determined that the ultrasonic signal attenuation is caused by reversible lithium plating; if the ultrasonic signal attenuation fails to recover to the third preset color during subsequent discharging, it is determined that there is an irreversible gas generation phenomenon.

[0071] It should be added that the embodiment uses a color mapping method to characterize the intensity of ultrasonic transmission signals, where red corresponds to the high ultrasonic signal intensity region, blue corresponds to the low ultrasonic signal intensity region, and yellow and green correspond to the intermediate intensity region. The first preset color is red, used to characterize the high-intensity signal region when the battery's internal structure is intact and dense under full charge conditions, and ultrasonic propagation loss is low; the second preset color is blue, used to characterize the low-intensity signal region after lithium plating or changes in the internal structure leading to ultrasonic propagation attenuation; the third preset color is yellow or green, used to characterize the intermediate intensity region when the battery's internal structure has no obvious defects under normal conditions. The preset threshold is 0 mΩ / V, and the evolution process of lithium plating is divided into the following four stages:

[0072] Phase 1: Normal lithium intercalation phase, d|Z| / dV is less than 0mΩ / V, impedance modulus |Z| decreases, differential capacitance curve and differential strain curve show fluctuation characteristics, with alternating peak and valley values, and the area of ​​the color region representing high signal intensity in the ultrasonic signal intensity graph gradually increases, and the color migrates to the high signal intensity region corresponding to the first preset color.

[0073] Phase 2: The final stage of lithium intercalation, d|Z| / dV becomes positive, the impedance modulus |Z| increases, and the differential capacity curve and differential strain curve reach their last characteristic peak.

[0074] Stage 3: Lithium nucleation stage. d|Z| / dV again falls below 0 mΩ / V, the impedance modulus |Z| decreases again, and the differential capacitance and differential strain curves exhibit flattening characteristics. The amplitude of curve changes decreases, and the alternating peak and trough phenomenon no longer occurs. At this point, the rate of change of dQ / dV is less than 5.2 Ah / V. 2 The rate of change of dε / dV is less than 600 με / V 2 It no longer exhibits the fluctuation and peak characteristics of Phase 1 and Phase 2.

[0075] Phase 4: Lithium growth phase. The differential capacity curve and differential strain curve maintain the flat characteristics of Phase 3. d|Z| / dV is closer to 0mΩ / V than in Phase 3. The slope of the impedance modulus |Z| decreases more gently. The ultrasonic signal intensity map shows a blue area where the signal intensity approaches 0%.

[0076] The dQ / dV curve, dε / dV curve, and |Z| curve are analyzed together, such as... Figure 11 As shown, dQ / dV represents the first derivative of capacity with respect to voltage. When the |Z| curve changes from rising to falling again, and the dQ / dV and dε / dV curves change from fluctuating to flat, the lithium nucleation stage is determined to have begun. When the dQ / dV and dε / dV curves remain flat, and the downward slope of the |Z| curve becomes gentler, lithium deposition is determined to have transitioned from the lithium nucleation stage to the lithium growth stage. Furthermore, the attenuation of the ultrasonic signal during charging and its recovery during discharging are used to distinguish between reversible lithium deposition and irreversible gas generation.

[0077] Example:

[0078] Taking a certain type of 5Ah NCM811 / graphite soft-pack battery cell as an example. First, according to... Figure 4 The experimental setup was arranged. A battery testing system was used to charge and discharge the battery. During the charging and discharging process, dynamic electrochemical impedance spectroscopy, fiber optic strain signals, and ultrasonic signals were simultaneously acquired. The strain signals were then interpolated and differentiated to obtain the dε / dV curve. The mid-frequency impedance modulus |Z| was extracted from the impedance spectrum, and the d|Z| / dV curve was calculated. Combining dQ / dV and ultrasonic images, the occurrence and evolution stages of lithium plating were identified, enabling online monitoring of lithium plating in the battery. Figure 3 As shown, it specifically includes:

[0079] S01. Arrange fiber Bragg grating strain sensors on the battery surface: Place the fiber Bragg grating strain sensors in the central region of the battery surface, such as... Figure 5 As shown, an adhesive is used to tightly bond the sensor to the battery surface, and the sensor is connected to a demodulator to record the strain signal during the charging and discharging process in real time.

[0080] S02. Simultaneous dynamic electrochemical impedance spectroscopy testing: A printed circuit board is used in conjunction with a flexible printed circuit to connect to the battery electrodes. The four pins on the FPC are directly soldered to the battery electrodes to ensure measurement stability. Dynamic electrochemical impedance spectroscopy testing is performed simultaneously during battery charging and discharging, with a frequency range of 0.1Hz~7800Hz, and impedance spectrum data is acquired in real time.

[0081] S03. Ultrasonic testing of batteries at different states of charge: A single-transmitter, single-receiver ultrasonic probe was used, with both the probe and the battery immersed in a silicone oil coupling medium. Ultrasonic testing was performed when the battery was at 3.0V, 50% SOC, 4.2V, 4.7V, and subsequently discharged to 3.0V. Ultrasonic signal intensity images were acquired, such as... Figure 6 As shown.

[0082] S04. Calculate the differentials of strain and capacitance with respect to voltage, respectively, to obtain differential strain curves and differential capacitance curves: Based on the strain data acquired by the fiber optic grating sensor, perform interpolation and differentiation to obtain the dε / dV curve, and plot the strain and differential strain images, as shown below. Figure 7 As shown. Based on the capacity data collected by the battery cycle meter, interpolation and differentiation are performed to obtain the dQ / dV curve, and a dQ / dV image is plotted, as shown. Figure 8 As shown.

[0083] S05. Extract the impedance modulus in the mid-frequency region and calculate the derivative of the impedance modulus with respect to voltage: Use the PCB and FPC to obtain the Nyquist plots of the dynamic electrochemical impedance spectroscopy of the battery at normal charging to 4.2V and overcharging to 4.7V, as shown below. Figure 9 As shown. Based on dynamic electrochemical impedance spectroscopy data, the impedance modulus |Z| in the mid-frequency region of 20 Hz was extracted, the d|Z| / dV curve was calculated, and the images of |Z| and d|Z| / dV were plotted, as shown. Figure 10 As shown in the figure, the analysis reveals that the evolution of |Z| with voltage can be divided into four stages: in stage I, |Z| continuously decreases; in stage II, |Z| begins to rise; in stage III, |Z| decreases again and d|Z| / dV shows a flat trend; in stage IV, d|Z| / dV remains flat but the slope is gentler. Stages I and II correspond to the normal lithium intercalation process, while stages III and IV correspond to the lithium plating process.

[0084] S06. Identifying the occurrence and evolution stages of lithium plating: Jointly analyze the dQ / dV curves, dε / dV curves, and |Z| curves, and combine this with ultrasonic images, such as... Figure 11 As shown in the diagram, when the |Z| curve changes from rising to falling again and the dQ / dV and dε / dV curves change from fluctuating to flat, the lithium nucleation stage is considered to have begun; when the dQ / dV and dε / dV curves remain flat while the slope of the |Z| curve decreases, the lithium deposition stage is considered to have entered. Simultaneously, this is verified using SEM morphology characterization, as shown in the diagram. Figure 12 As shown.

[0085] like Figure 2 As shown, according to another embodiment of the present invention, an online monitoring device for lithium plating in lithium batteries based on multi-signal coupling is also provided, the device comprising:

[0086] Data acquisition module 1 is used to acquire strain data, impedance spectrum data, capacity data, voltage data and ultrasonic signal intensity map of the lithium battery under test;

[0087] The differential curve generation module 2 is used to calculate the differential of strain with respect to voltage and the differential of capacity with respect to voltage based on strain data, capacity data and voltage data, respectively, and generate differential strain curve and differential capacity curve.

[0088] The feature extraction and differentiation processing module 3 is used to extract the mid-frequency impedance modulus from the impedance spectrum data, plot the mid-frequency impedance modulus curve, calculate the differential of the impedance modulus with respect to voltage, and generate the mid-frequency impedance modulus differentiation curve.

[0089] The multi-stage evolution identification module 4 is used to identify the occurrence and evolution stages of lithium plating based on the evolution characteristics of the differential strain curve, differential capacity curve, mid-frequency impedance modulus curve and mid-frequency impedance modulus differential curve, combined with the color change of the ultrasonic signal intensity map, so as to realize online monitoring of lithium plating in lithium batteries.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for online monitoring of lithium plating in lithium batteries based on multi-signal coupling, characterized in that, The method includes: S1. Collect strain data, impedance spectrum data, capacity data, voltage data, and ultrasonic signal intensity diagram of the lithium battery under test; S2. Based on the strain data, capacity data, and voltage data, calculate the differential of strain with respect to voltage and the differential of capacity with respect to voltage, respectively, and generate differential strain curves and differential capacity curves. S3. Extract the mid-frequency impedance modulus from the impedance spectrum data, plot the mid-frequency impedance modulus curve, calculate the derivative of the impedance modulus with respect to voltage, and generate the mid-frequency impedance modulus differential curve. S4. Based on the evolution characteristics of the differential strain curve, differential capacity curve, mid-frequency impedance modulus curve, and mid-frequency impedance modulus differential curve, combined with the color change of the ultrasonic signal intensity map, the occurrence and evolution stages of lithium plating are identified to achieve online monitoring of lithium plating in lithium batteries.

2. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 1, characterized in that, S1 includes: S11. Using a fiber Bragg grating strain sensor deployed in the central region of the surface of the lithium battery under test, the surface deformation of the lithium battery under test during charging and discharging is monitored in real time to obtain strain data. S12. During the charging and discharging process of the lithium battery under test, dynamic electrochemical impedance spectroscopy and charge-discharge tests are performed simultaneously to acquire impedance spectrum data in real time and record the corresponding capacity and voltage data. S13. When the lithium battery under test is charged to different preset state of charge nodes, ultrasonic detection is performed to acquire ultrasonic signals, and the ultrasonic signals are processed to generate an ultrasonic signal intensity map characterizing the intensity of ultrasonic transmission signals at different positions of the lithium battery under test.

3. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 2, characterized in that, In the dynamic electrochemical impedance spectroscopy test, a printed circuit board with flexible printed circuit pins is fixedly connected to the electrode of the lithium battery under test by welding.

4. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 1, characterized in that, The evolution characteristics of the differential strain curve, differential capacity curve, mid-frequency impedance modulus curve, and mid-frequency impedance modulus differential curve include: fluctuation and flattening characteristics of the differential strain curve, peak position change and flattening characteristics of the differential capacity curve, and rising, falling, and slope change characteristics of the mid-frequency impedance modulus.

5. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 1, characterized in that, The evolutionary stages of lithium plating include: normal lithium intercalation stage, late lithium intercalation stage, lithium nucleation stage, and lithium growth stage. During the normal lithium intercalation stage, the value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage is less than the preset threshold, the impedance modulus in the mid-frequency region shows a decreasing trend, the differential strain curve and differential capacity curve show fluctuation characteristics, and the color of the ultrasonic signal intensity map shifts towards the first preset color direction. In the final stage of lithium intercalation, the differential curve of the impedance modulus in the mid-frequency region with respect to voltage becomes positive, the impedance modulus in the mid-frequency region shows an upward trend, the differential strain curve and differential capacity curve reach the last characteristic peak, and the ultrasonic signal intensity map maintains the target signal intensity characteristics. During the lithium nucleation stage, the value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage is once again less than the preset threshold, the impedance modulus in the mid-frequency region shows a downward trend again, the differential strain curve and differential capacity curve change from fluctuating and peak characteristics to flat characteristics, and the ultrasonic signal intensity map begins to show local signal attenuation. During the lithium growth stage, the differential strain curve and differential capacity curve maintain a flat characteristic. The absolute value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage is less than the absolute value of the differential curve of the impedance modulus in the mid-frequency region with respect to voltage during the lithium nucleation stage, and is less than the preset threshold. The slope of the decrease of the impedance modulus in the mid-frequency region becomes slower, and the second preset color appears in the ultrasonic signal intensity graph.

6. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 5, characterized in that, The starting point of the lithium nucleation stage is determined by identifying the turning point where the impedance modulus in the mid-frequency region changes from an upward trend to a downward trend again, and the turning point where the differential strain curve and differential capacity curve change from fluctuating characteristics to flat characteristics.

7. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 5, characterized in that, The criteria for determining whether lithium deposition has transitioned from the lithium nucleation stage to the lithium growth stage are: during the period when the differential strain curve and differential capacity curve maintain flat characteristics, the inflection point of the range of decreasing slope of the impedance modulus in the mid-frequency region is identified.

8. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 2, characterized in that, The ultrasonic detection employs a one-transmitter-one-receiver probe arrangement, with the transmitting and receiving probes placed on opposite sides of the lithium battery under test, and both the probes and the lithium battery under test immersed in the coupling medium. Based on the attenuation of the ultrasonic signal intensity during charging and the recovery of the ultrasonic signal intensity during discharging, reversible lithium plating and irreversible gas generation phenomena are distinguished.

9. The online monitoring method for lithium plating in lithium batteries based on multi-signal coupling according to claim 8, characterized in that, If the ultrasonic signal intensity graph shows a second preset color during charging, but recovers to a third preset color during subsequent discharging, it is determined that the ultrasonic signal attenuation is caused by reversible lithium plating; if the ultrasonic signal attenuation fails to recover to the third preset color during subsequent discharging, it is determined that there is an irreversible gas generation phenomenon.

10. A lithium battery lithium plating online monitoring device based on multi-signal coupling, used to implement the lithium battery lithium plating online monitoring method based on multi-signal coupling as described in any one of claims 1-9, characterized in that, The device includes: The data acquisition module is used to acquire strain data, impedance spectrum data, capacity data, voltage data, and ultrasonic signal intensity maps of the lithium battery under test. The differential curve generation module is used to calculate the differential of strain with respect to voltage and the differential of capacity with respect to voltage based on strain data, capacity data and voltage data, and generate differential strain curves and differential capacity curves. The feature extraction and differentiation module is used to extract the mid-frequency impedance modulus from the impedance spectrum data, plot the mid-frequency impedance modulus curve, calculate the derivative of the impedance modulus with respect to voltage, and generate the mid-frequency impedance modulus differentiation curve. The multi-stage evolution identification module is used to identify the occurrence and evolution stages of lithium plating based on the evolution characteristics of differential strain curves, differential capacity curves, mid-frequency impedance modulus curves, and mid-frequency impedance modulus differential curves, combined with the color changes of ultrasonic signal intensity maps, so as to realize online monitoring of lithium plating in lithium batteries.

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