Lithium battery electrode plate containing conductive coating and preparation method thereof

Abstract

The lithium battery electrode plate comprises an electrode plate base body, a current guiding layer is arranged on the electrode plate base body, a self-adaptive buffer layer is arranged on one side of the current guiding layer, an ion enrichment layer is arranged on the side, away from the current guiding layer, of the self-adaptive buffer layer, and a conductive coating is arranged on the electrode plate base body. An interface fusion layer is arranged on one side, far away from the self-adaptive buffer layer, of the ion enrichment layer, and the current guide layer is a contact interface layer of the electrode plate substrate; the carbon nanotube array current guide layer which is distributed in a non-continuous net shape is arranged on the electrode plate base body, and is matched with the fast ion conductor material ion enrichment layer with higher ion conductivity to form a conduction-ion transmission synergistic structure, so that rapid and uniform conduction of charges can be guaranteed, efficient enrichment and migration of ions can be realized, and the service life of the electrode plate is prolonged. And the rate capability and the energy output efficiency of the battery are obviously improved.

Description

Technical Field

[0001] This invention belongs to the field of lithium battery technology, specifically relating to a lithium battery electrode sheet with a conductive coating and its preparation method. Background Technology

[0002] Lithium-ion battery electrode sheets are the core components of energy storage devices. As a key structure for charge transport and interface connection, the performance of conductive coatings directly affects the energy density, cycle stability and safety of the battery. Traditional lithium-ion battery electrode sheet conductive coatings mostly adopt single-component or simple composite structure designs, focusing mainly on basic conductivity performance, and the corresponding material structure and functional design are relatively simplified.

[0003] In the application of existing lithium battery electrode sheets with conductive coatings, the coating structure often lacks targeted layered functional design, making it difficult to simultaneously meet the multiple requirements of rapid charge conduction, efficient ion transport, structural buffering adaptation, and stable interface bonding. Traditional conductive coatings are mostly continuous and dense structures, lacking precise design of non-continuous network distribution, resulting in insufficient uniformity of current conduction; and they are difficult to mitigate the volume expansion and contraction of electrode materials during battery charging and discharging, easily causing coating peeling or cracking; the ionic conductivity of the ion transport region is low, which restricts the rate performance of the battery; moreover, the interlayer is mostly bonded by simple methods, lacking gradient transition design, resulting in insufficient interlayer bonding and increased contact resistance. Summary of the Invention

[0004] The purpose of this invention is to provide a lithium battery electrode sheet with a conductive coating to solve the problems mentioned in the background art.

[0005] In a first aspect, the present invention provides a lithium battery electrode sheet with a conductive coating, comprising: The electrode substrate 1 includes a current guiding layer 2 on the electrode substrate 1, an adaptive buffer layer 3 on one side of the current guiding layer 2, an ion enrichment layer 4 on the side of the adaptive buffer layer 3 away from the current guiding layer 2, and an interface fusion layer 5 on the side of the ion enrichment layer 4 away from the adaptive buffer layer 3. The current guiding layer 2 is the contact interface layer of the electrode substrate 1.

[0006] In one possible implementation of the first aspect, the current guiding layer 2 comprises a discontinuously distributed array of carbon nanotubes with an areal density of 0.1-0.5 mg / cm².

[0007] In one possible implementation of the first aspect, the adaptive buffer layer 3 is a porous polymer skeleton with elasticity.

[0008] In one possible implementation of the first aspect, the ion enrichment layer 4 is made of a fast ion conductor material, the fast ion conductor material having a higher ion conductivity than the adaptive buffer layer 3.

[0009] In one possible implementation of the first aspect, the interface fusion layer 5 is a composite functional layer that has undergone hot pressing and has a surface roughness Ra≤0.5μm.

[0010] In one possible implementation of the first aspect, the current guiding layer 2 and the adaptive buffer layer 3 are composited by a conductive adhesive, and the ion enrichment layer 4 and the interface fusion layer 5 are connected by a gradient transition.

[0011] Compared with the prior art, the present invention provides a lithium battery electrode sheet with a conductive coating, which has the following advantages: 1. By setting a non-continuous network-distributed carbon nanotube array current guiding layer on the electrode substrate, and combining it with an ion enrichment layer of fast ion conductor material with higher ion conductivity, a "conductivity-ion transport" synergistic structure is formed, which can not only ensure rapid and uniform charge conduction, but also achieve efficient ion enrichment and migration, significantly improving the rate performance and energy output efficiency of the battery. Second, the adaptive buffer layer of the elastic porous polymer skeleton can effectively alleviate the volume expansion and contraction of the electrode material during battery charging and discharging. Combined with the interface fusion layer with a surface roughness Ra≤0.5μm after hot pressing, as well as the interlayer conductive adhesive composite and gradient transition connection method, the bonding force between the functional layers is greatly enhanced, reducing structural failure problems such as coating peeling and cracking, and significantly improving the cycle stability and long service life of the battery.

[0012] Secondly, the present invention provides a method for preparing a lithium battery electrode sheet containing a conductive coating, comprising: Obtain the electrode substrate to be coated and its automatic coating device, collect the substrate surface data of the electrode substrate, and analyze the surface morphology features and key coating areas of the electrode substrate based on the substrate surface data; The coating performance requirements of the automatic coating device are queried. Based on the surface morphology features and the key coating area, an optimized coating path is planned for the electrode substrate to meet the coating performance requirements. Based on the optimized coating path, the coating control parameters corresponding to the automatic coating device are generated. The automatic coating device is controlled by the coating control parameters to coat the surface of the electrode substrate with a conductive coating, thereby obtaining a coated lithium battery electrode sheet.

[0013] In one possible implementation of the second aspect, the step of analyzing the surface morphology features and key coating areas of the electrode substrate based on the substrate surface data includes: The surface data of the substrate is subjected to noise signal filtering to obtain optimized surface data; The optimized surface data is analyzed for morphological features to obtain microscopic morphological features; The micro-morphological features are subjected to feature parameter quantization to obtain a surface morphology feature vector; Regional clustering analysis is performed on the surface morphology feature vectors to obtain functional zoning identifiers; Based on the functional zoning identifiers, the surface state characterization of the electrode substrate is analyzed. Spatial distribution modeling is performed on the surface morphology feature vector to obtain the key coating area corresponding to the electrode substrate.

[0014] In one possible implementation of the second aspect, the step of combining the surface morphology features and the key coating area to plan the optimized coating path for the coating performance requirements with respect to the electrode substrate includes: The coating performance requirements are analyzed to obtain coating process parameters; Wetting characteristics analysis was performed on the surface morphology features and the key coating areas to obtain regional wetting patterns; By combining the regional wetting pattern and the coating process parameters, an initial coating path corresponding to the electrode substrate is constructed; Obtain the rheological property data of the slurry in the automatic coating device; Based on the rheological data, the initial coating path is corrected for flow field uniformity to obtain a corrected coating path. The modified coating path is then subjected to process adaptability verification to obtain an optimized coating path.

[0015] In one possible implementation of the second aspect, the process analysis of the coating performance requirements to obtain coating process parameters includes: The technical specifications for the coating performance requirements are analyzed to obtain coating quality indicators. The coating quality indicators are mapped to obtain process control parameters; A correlation analysis was performed on the process control parameters to obtain a parameter correlation matrix; The process constraints are obtained by extracting the constraints from the parameter correlation matrix. The feasibility of the aforementioned process constraints is verified to obtain a feasible process window; The parameters of the feasible process window are optimized to obtain the coating process parameters.

[0016] As can be seen, by analyzing the surface morphology features and key coating areas of the electrode substrate based on the substrate surface data, this invention can identify the surface state and optimal coating position of the electrode substrate, thereby facilitating the subsequent automated coating process of the electrode substrate. By combining the surface morphology features and the key coating areas, this invention plans an optimized coating path corresponding to the coating performance requirements of the electrode substrate, enabling intelligent path planning and precise parameter configuration of the automatic coating device. This provides an execution basis for the subsequent high-quality coating process of the electrode substrate. By utilizing the coating control parameters to control the automatic coating device, this invention achieves precise coating of the conductive coating on the surface of the electrode substrate, ensuring that the coating thickness uniformity and areal density consistency meet the design requirements. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of a three-dimensional structure of a lithium battery electrode sheet with a conductive coating according to an embodiment of the present invention; Figure 2 A flowchart illustrating a method for preparing a lithium battery electrode sheet with a conductive coating, as proposed in one embodiment of the invention. In the figure: 1. Electrode substrate; 2. Current guiding layer; 3. Adaptive buffer layer; 4. Ion enrichment layer; 5. Interface fusion layer. Detailed Implementation

[0018] 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.

[0019] Please see Figure 1 This is a schematic diagram of the three-dimensional structure of the lithium battery electrode sheet with conductive coating proposed in this invention. It includes an electrode sheet substrate 1, a current guiding layer 2 on the electrode sheet substrate 1, an adaptive buffer layer 3 on one side of the current guiding layer 2, an ion enrichment layer 4 on the side of the adaptive buffer layer 3 away from the current guiding layer 2, and an interface fusion layer 5 on the side of the ion enrichment layer 4 away from the adaptive buffer layer 3. The current guiding layer 2 is the contact interface layer of the electrode sheet substrate 1, ensuring efficient electron transport from the current collector to the active material layer.

[0020] The current guiding layer 2 comprises a discontinuous network of carbon nanotube arrays with an areal density of 0.1-0.5 mg / cm². The carbon nanotubes, with their unique one-dimensional tubular structure and excellent conductivity, construct a three-dimensional conductive network on the current collector surface. This not only provides efficient electron transport channels for the electrode sheet but also effectively suppresses the growth of lithium dendrites. The discontinuous network distribution ensures sufficient electron conduction paths while reserving space for ion transport, thus achieving synergistic optimization of electron-ion conduction.

[0021] The adaptive buffer layer 3 is an elastic porous polymer skeleton. This porous structure has good compression resilience and can effectively absorb the volume change stress of the active material during battery charging and discharging. It prevents the electrode sheet from cracking or separating from the current collector due to repeated expansion and contraction. At the same time, its porous characteristics provide a continuous channel for electrolyte wetting and ion transport, ensuring the uniformity of electrode reaction.

[0022] The ion enrichment layer 4 is made of a fast ion conductor material, which has a higher ion conductivity than the adaptive buffer layer 3. This layer significantly reduces the migration barrier of lithium ions at the electrode-electrolyte interface by constructing a fast ion transport channel on the surface of the electrode sheet, effectively improving the high-rate charge and discharge performance of the electrode. It is particularly suitable for fast charging applications. At the same time, its stable crystal structure helps to form a uniform solid electrolyte interface film.

[0023] The interface fusion layer 5 is a composite functional layer that has undergone hot pressing treatment. Its surface roughness Ra≤0.5μm. Through a precisely controlled hot pressing process, a dense and flat interface layer is formed on the surface of the electrode sheet. The lower surface roughness is conducive to the formation of a stable and uniform solid electrolyte interface film, reducing the occurrence of side reactions, while enhancing the contact consistency with the separator, and improving the safety performance and cycle life of the battery.

[0024] The current guiding layer 2 and the adaptive buffer layer 3 are bonded together by a conductive adhesive. The conductive adhesive ensures a strong bond between the two layers while maintaining the continuity of electron conduction between the layers. The ion enrichment layer 4 and the interface fusion layer 5 are connected by a gradient transition. This gradient interface design avoids stress concentration caused by abrupt performance changes and ensures the smooth transport of lithium ions between layers, thereby enabling the synergistic work between the functional layers.

[0025] The working principle and usage process of a lithium battery electrode sheet with a conductive coating according to the present invention are as follows: During the charging and discharging process of the battery, each functional layer works in concert: During the discharge stage, lithium ions are extracted from the counter electrode, pass through the electrolyte and the interface fusion layer 5 to reach the ion enrichment layer 4. The fast ion conductor material in this layer provides a fast transport channel for lithium ions with its ionic conductivity, which is two orders of magnitude higher than that of the adaptive buffer layer 3, significantly reducing the interface impedance and improving the rate performance; The ions then pass through the porous polymer skeleton of the adaptive buffer layer 3. The elastic properties of this skeleton effectively absorb the volume change stress generated by the active material during the lithium ion insertion / extraction process, preventing the electrode structure from being damaged; Finally, electrons are efficiently collected to the current collector through the discontinuous network carbon nanotube array (area density 0.1-0.5 mg / cm²) of the current guiding layer 2, completing the energy output.

[0026] During charging, the above process is reversed, and each layer continues to perform its corresponding function. The current guiding layer 2 and the adaptive buffer layer 3 are bonded together with a conductive adhesive to ensure the continuity of electron transport between layers; while the gradient transition connection between the ion enrichment layer 4 and the interface fusion layer 5 ensures the smooth migration of lithium ions between layers and avoids concentration polarization at the interface.

[0027] After multiple charge-discharge cycles, the synergistic effect of each functional layer is fully demonstrated: the adaptive buffer layer 3 maintains the structural integrity of the electrode, the ion enrichment layer 4 ensures rapid charge-discharge capability, the interface fusion layer 5 stabilizes the electrode-electrolyte interface, and the current guiding layer 2 continuously provides an efficient electron conduction path, ultimately enabling the battery to have high energy density, excellent rate performance and long cycle life.

[0028] See Figure 2 The figure shows a method for preparing a lithium battery electrode sheet with a conductive coating according to an embodiment of the present invention, comprising: S1. Obtain the electrode substrate to be coated and its automatic coating device, collect the substrate surface data of the electrode substrate, and analyze the surface morphology features and key coating areas of the electrode substrate based on the substrate surface data.

[0029] This invention analyzes the surface morphology and key coating areas of the electrode substrate based on surface data, identifying the surface state and optimal coating location. This facilitates subsequent automated coating processes on the electrode substrate. The electrode substrate refers to the base layer of the active material to be coated in battery manufacturing or electronic component production. The automated coating device refers to a complete set of automated equipment used in battery and electronic component production to precisely coat the active material slurry onto the surface of the electrode substrate. It includes a substrate unwinding mechanism, a precision coating head, a substrate tension stabilization system, an online thickness detection module, and a hot air drying unit. The component and finished product winding mechanism, wherein the substrate surface data is obtained by high-resolution morphological scanning of the electrode substrate surface using a white light interferometer or laser confocal microscope, and simultaneously fusing the three-dimensional morphological data obtained from surface roughness sensor data, wherein the surface morphological features refer to the microscopic and macroscopic features of the electrode substrate surface such as roughness, waviness, scratches or contamination points, and the key coating area refers to the key areas on the electrode substrate that need to be uniformly coated with active material, such as the central area of ​​the electrode sheet, the edge transition area, etc. Furthermore, the substrate surface data of the electrode substrate can be acquired by using a white light interferometer combined with a multi-region stitching algorithm.

[0030] As an embodiment of the present invention, the step of analyzing the surface morphology features and key coating areas of the electrode substrate based on the substrate surface data includes: The surface data of the substrate is subjected to noise signal filtering to obtain optimized surface data; The optimized surface data is analyzed for morphological features to obtain microscopic morphological features; The micro-morphological features are subjected to feature parameter quantization to obtain a surface morphology feature vector; Regional clustering analysis is performed on the surface morphology feature vectors to obtain functional zoning identifiers; Based on the functional zoning identifiers, the surface state characterization of the electrode substrate is analyzed. Spatial distribution modeling is performed on the surface morphology feature vector to obtain the key coating area corresponding to the electrode substrate.

[0031] Wherein, the optimized surface data is a dataset of the substrate surface data after noise signal filtering to eliminate measurement errors; the micromorphological features are the surface microstructure features obtained from the optimized surface data through feature analysis; the surface morphological feature vector is a multidimensional feature representation vector generated by parameter quantization of the micromorphological features; and the functional zoning identifier is a regional functional classification identifier obtained by regional clustering analysis of the surface morphological feature vector, such as high wetting area, low adhesion area, and conductivity priority area.

[0032] Furthermore, noise signal filtering can be performed on the substrate surface data using wavelet transform filters to obtain optimized surface data; morphological features can be analyzed using fractal dimension analysis to obtain microscopic morphological features; feature parameter quantification can be performed on the microscopic morphological features by calculating the surface power spectral density and combining skewness and kurtosis statistics to obtain surface morphological feature vectors; regional clustering analysis can be performed on the surface morphological feature vectors using the DBSCAN clustering algorithm to obtain functional zoning identifiers; based on the functional zoning identifiers, the surface state characterization corresponding to the electrode substrate can be characterized by comparison with a standard surface morphology database and local wettability analysis. For example, by comparing the differences between the ideal surface and the measured morphology data in the standard database, unqualified areas such as oxide spots, pore defects, or mechanical scratches on the substrate surface can be identified, and their location, size, and impact on coating quality can be quantified; spatial distribution modeling of the surface morphology feature vectors can be performed by establishing a transformation matrix between the material coordinate system and the coating equipment coordinate system and combining it with the Voronoi diagram segmentation algorithm to obtain the key coating areas corresponding to the electrode substrate.

[0033] S2. Query the coating performance requirements of the automatic coating device, combine the surface morphology features and the key coating area, plan the optimized coating path corresponding to the electrode substrate for the coating performance requirements, and generate the coating control parameters corresponding to the automatic coating device based on the optimized coating path.

[0034] This invention, by combining the surface morphology features and the key coating areas, plans an optimized coating path for the electrode substrate to meet the coating performance requirements. This enables intelligent path planning and precise parameter configuration of the automatic coating device, providing a foundation for subsequent high-quality coating processing of the electrode substrate.

[0035] The coating performance requirements refer to the coating quality indicators set by the user, such as surface density uniformity, thickness tolerance, and interfacial bonding strength. The optimized coating path is the motion trajectory of the coating device planned according to the coating performance requirements and the surface characteristics of the substrate. Furthermore, the coating performance requirements of the automatic coating device can be queried through the process parameter database, which is a database pre-constructed by collecting a large number of process parameters.

[0036] As an embodiment of the present invention, the step of combining the surface morphology features and the key coating area to plan the optimized coating path for the electrode substrate in relation to the coating performance requirements includes: The coating performance requirements are analyzed to obtain coating process parameters; Wetting characteristics analysis was performed on the surface morphology features and the key coating areas to obtain regional wetting patterns; By combining the regional wetting pattern and the coating process parameters, an initial coating path corresponding to the electrode substrate is constructed; Obtain the rheological property data of the slurry in the automatic coating device; Based on the rheological data, the initial coating path is corrected for flow field uniformity to obtain a corrected coating path. The modified coating path is then subjected to process adaptability verification to obtain an optimized coating path.

[0037] The coating process parameters are executable quantitative parameters obtained through process analysis of the coating performance requirements, such as coating speed, pressure, and gap. The regional wetting map is a topological map with a wetting gradient distribution obtained by analyzing the surface morphology features and the key coating areas. The initial coating path is a coating trajectory obtained by path planning of the electrode substrate, the regional wetting map, and the coating process parameters. The slurry rheological property data is a collection of rheological parameters such as viscosity, thixotropy, and shear thinning characteristics of the slurry in the automatic coating device. The corrected coating path is the path with optimal slurry flow stability obtained by correcting the flow field uniformity of the initial coating path based on the rheological property data.

[0038] Furthermore, surface morphology features and key coating areas can be analyzed for wetting characteristics using surface energy distribution analysis and contact angle measurement techniques to obtain regional wetting patterns. Combining these patterns with coating process parameters, an initial coating path corresponding to the electrode substrate can be constructed using an adaptive path planning algorithm. The rheological properties of the slurry in the automatic coating device can be monitored in real time using a rheometer. Based on this rheological data, the initial coating path can be corrected for flow field uniformity using computational fluid dynamics simulation to obtain a corrected coating path. Finally, the corrected coating path can be validated for process adaptability using coating window theory and process limit analysis to obtain an optimized coating path.

[0039] Furthermore, as an optional embodiment of the present invention, the process analysis of the coating performance requirements to obtain coating process parameters includes: The technical specifications for the coating performance requirements are analyzed to obtain coating quality indicators. The coating quality indicators are mapped to obtain process control parameters; A correlation analysis was performed on the process control parameters to obtain a parameter correlation matrix; The process constraints are obtained by extracting the constraints from the parameter correlation matrix. The feasibility of the aforementioned process constraints is verified to obtain a feasible process window; The parameters of the feasible process window are optimized to obtain the coating process parameters.

[0040] The coating quality index is a technical indicator description corresponding to the coating performance requirements, such as converting the areal density uniformity of ±2% into a quantitative index that includes thickness tolerance and areal density accuracy; the process control parameters are the process parameters corresponding to the coating quality index, such as mapping areal density uniformity to control variables such as coating speed, die gap, and slurry flow rate; the parameter correlation matrix is ​​an expression of the interaction relationship between the process control parameters, such as constructing a coupling relationship matrix between coating speed and slurry flow rate; the process constraints are the boundary conditions defined by the parameter correlation matrix, such as setting the equipment limit threshold range for the coating speed; the feasible process window is the effective parameter space after the process constraints have been verified for feasibility; and the coating process parameters are the optimal combination of process parameters after parameter optimization processing of the feasible process window.

[0041] Furthermore, the coating performance requirements can be analyzed using a natural language processing-based technical specification parsing engine to obtain coating quality indicators; the coating quality indicators can be mapped using a knowledge graph-based process parameter mapping system to obtain process control parameters; the parameter association matrix can be extracted using a multivariate analysis-based constraint extraction algorithm to obtain process constraints; the process constraints can be verified for feasibility using an experimental design-based process window verification platform to obtain feasible process windows; and the feasible process windows can be optimized using a multi-objective optimization-based parameter optimization algorithm to obtain coating process parameters.

[0042] Furthermore, as an optional embodiment of the present invention, the step of performing correlation analysis on the process control parameters to obtain a parameter correlation matrix includes: Extract the parameter feature attributes corresponding to the process control parameters, and filter the parameter feature attributes to obtain the characteristic parameter attributes; Calculate the correlation coefficient between the characterization parameter attributes, and when the correlation coefficient is greater than a preset threshold, group the process control parameters to obtain the correlated control parameters; The associated control parameters are processed to generate a matrix, resulting in a parameter association matrix.

[0043] The parameter feature attributes are multiple dimensions of information extracted from the process control parameters that reflect the basic characteristics of the parameters, such as parameter type, numerical range, statistical characteristics (mean, variance, etc.), and engineering significance. The characterizing parameter attributes are a subset of attributes representing the key characteristics and degree of influence of the parameters after the parameter feature attributes have been filtered. The correlation coefficient is a quantitative value of the correlation strength between the characterizing parameter attributes, used to measure the linear or nonlinear relationship between the parameters. The associated control parameters are a set of process control parameters with strong interdependencies formed by grouping based on the correlation coefficients. The parameter correlation matrix is ​​a matrix representation of the correlation relationship between the associated control parameters, with matrix elements being the correlation coefficients between the parameters, used to visualize the correlation structure between the parameters.

[0044] Furthermore, principal component analysis can be used to extract the parameter feature attributes corresponding to the process control parameters to capture the main change patterns of the parameters; the parameter feature attributes can be filtered using a variance threshold screening method, retaining attributes with variance greater than a preset threshold, thereby obtaining the characteristic parameter attributes; the correlation coefficients between the characteristic parameter attributes can be calculated using Pearson correlation coefficient or Spearman rank correlation coefficient, and a preset threshold can be set to identify strong correlations. When the correlation coefficient is greater than the threshold, a hierarchical clustering algorithm is used to group the process control parameters to obtain the associated control parameters; the associated control parameters can be generated by constructing a symmetric matrix, where the rows and columns of the matrix correspond to the parameters, and the element values ​​are the correlation coefficients, thereby obtaining a parameter correlation matrix. This matrix can be used for subsequent process optimization and fault diagnosis. For example, in the parameter correlation matrix, if a group of parameters has a high correlation coefficient, it indicates that these parameters change synergistically during the process and need to be adjusted simultaneously to maintain system stability.

[0045] This invention generates coating control parameters for the automatic coating device based on the optimized coating path, thereby facilitating subsequent precise control of the automatic coating device. The coating control parameters are a set of specific control parameters for the automatic coating device used to drive the device to perform coating actions according to the optimized coating path, including control variables such as speed, pressure, and temperature. Further, the generation of coating control parameters for the automatic coating device based on the optimized coating path involves: performing forward kinematics calculation on the optimized coating path to convert the path coordinates in the substrate coordinate system into a sequence of position and speed parameters for each execution unit of the coating device; standardizing and encoding the parameter sequence according to the control protocol of the coating device, such as OPC UA or Modbus TCP; adding a real-time compensation algorithm to handle changes in slurry characteristics; and combining the uniformity and thickness requirements of the coating performance to generate a set of coating control parameters including speed control, pressure regulation, and temperature management.

[0046] S3. Using the coating control parameters, control the automatic coating device to coat the electrode substrate with a conductive coating to obtain a coated lithium battery electrode sheet.

[0047] This invention utilizes coating control parameters to control the automatic coating device, achieving precise coating of the conductive coating on the electrode substrate surface. This ensures that the coating thickness uniformity and areal density consistency meet design requirements. The coating control parameters include key process indicators such as die gap accuracy, coating speed stability, and slurry supply pressure range. By establishing a mapping relationship between coating parameters and coating quality, a closed-loop control system comprising a tension control subsystem, a thickness monitoring subsystem, and a temperature management subsystem is constructed to achieve precise control of the coating process.

[0048] Based on the coating control parameters, the automatic coating device performs the coating operation according to the preset process procedure: first, the tension adjustment mechanism ensures that the electrode substrate is transported flat, then the precision coating die uniformly coats the functional slurry on the surface of the substrate to form a wet coating of a predetermined thickness; at the same time, the online thickness gauge monitors the coating thickness distribution in real time and feeds the detection data back to the control system to dynamically adjust the coating parameters to eliminate thickness deviation; finally, the coating is cured by the pre-drying unit to obtain the coated lithium battery electrode sheet.

[0049] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A lithium battery electrode sheet with a conductive coating, comprising an electrode sheet substrate (1), characterized in that: The electrode substrate (1) is provided with a current guiding layer (2), an adaptive buffer layer (3) is provided on one side of the current guiding layer (2), an ion enrichment layer (4) is provided on the side of the adaptive buffer layer (3) away from the current guiding layer (2), and an interface fusion layer (5) is provided on the side of the ion enrichment layer (4) away from the adaptive buffer layer (3). The current guiding layer (2) is the contact interface layer of the electrode substrate (1).

2. The lithium battery electrode sheet with a conductive coating as described in claim 1, characterized in that, The current guiding layer (2) comprises a discontinuously distributed array of carbon nanotubes with an areal density of 0.1-0.5 mg / cm².

3. The lithium battery electrode sheet with a conductive coating as described in claim 1, characterized in that, The adaptive buffer layer (3) is an elastic porous polymer skeleton.

4. The lithium battery electrode sheet with a conductive coating as described in claim 1, characterized in that, The ion enrichment layer (4) is made of a fast ion conductor material, which has a higher ion conductivity than the adaptive buffer layer (3).

5. A lithium battery electrode sheet with a conductive coating as described in claim 1, characterized in that, The interface fusion layer (5) is a composite functional layer that has undergone hot pressing treatment, and its surface roughness Ra≤0.5μm.

6. A lithium battery electrode sheet with a conductive coating as described in claim 1, characterized in that, The current guiding layer (2) and the adaptive buffer layer (3) are bonded together by a conductive adhesive, and the ion enrichment layer (4) and the interface fusion layer (5) are connected by a gradient transition.

7. A method for preparing a lithium battery electrode sheet with a conductive coating according to any one of claims 1 to 6, characterized in that, The method includes: Obtain the electrode substrate to be coated and its automatic coating device, collect the substrate surface data of the electrode substrate, and analyze the surface morphology features and key coating areas of the electrode substrate based on the substrate surface data; The coating performance requirements of the automatic coating device are queried. Based on the surface morphology features and the key coating area, an optimized coating path is planned for the electrode substrate to meet the coating performance requirements. Based on the optimized coating path, the coating control parameters corresponding to the automatic coating device are generated. The automatic coating device is controlled by the coating control parameters to coat the surface of the electrode substrate with a conductive coating, thereby obtaining a coated lithium battery electrode sheet.

8. The method according to claim 7, characterized in that, The step of analyzing the surface morphology features and key coating areas of the electrode substrate based on the substrate surface data includes: The surface data of the substrate is subjected to noise signal filtering to obtain optimized surface data; The optimized surface data is analyzed for morphological features to obtain microscopic morphological features; The micro-morphological features are subjected to feature parameter quantization to obtain a surface morphology feature vector; Regional clustering analysis is performed on the surface morphology feature vectors to obtain functional zoning identifiers; Based on the functional zoning identifiers, the surface state characterization of the electrode substrate is analyzed. Spatial distribution modeling is performed on the surface morphology feature vector to obtain the key coating area corresponding to the electrode substrate.

9. The method according to claim 7, characterized in that, The step of combining the surface morphology features and the key coating areas to plan the optimized coating path for the electrode substrate in relation to the coating performance requirements includes: The coating performance requirements are analyzed to obtain coating process parameters; Wetting characteristics analysis was performed on the surface morphology features and the key coating areas to obtain regional wetting patterns; By combining the regional wetting pattern and the coating process parameters, an initial coating path corresponding to the electrode substrate is constructed; Obtain the rheological property data of the slurry in the automatic coating device; Based on the rheological data, the initial coating path is corrected for flow field uniformity to obtain a corrected coating path. The modified coating path is then subjected to process adaptability verification to obtain an optimized coating path.

10. The method according to claim 9, characterized in that, The process analysis of the coating performance requirements yields coating process parameters, including: The technical specifications of the coating performance requirements are analyzed to obtain coating quality indicators; The coating quality indicators are mapped to obtain process control parameters; A correlation analysis was performed on the process control parameters to obtain a parameter correlation matrix; The process constraints are obtained by extracting the constraints from the parameter correlation matrix. The feasibility of the aforementioned process constraints is verified to obtain a feasible process window; The parameters of the feasible process window are optimized to obtain the coating process parameters.

Images