CN117173100A - Polymer lithium ion battery production control system and method thereof - Google Patents
Polymer lithium ion battery production control system and method thereof Download PDFInfo
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- CN117173100A CN117173100A CN202310950323.6A CN202310950323A CN117173100A CN 117173100 A CN117173100 A CN 117173100A CN 202310950323 A CN202310950323 A CN 202310950323A CN 117173100 A CN117173100 A CN 117173100A
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- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 title claims abstract description 64
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The application discloses a polymer lithium ion battery production control system and a method thereof, wherein a camera is used for collecting a core appearance image of a detected core; performing image feature analysis on the appearance image of the winding core to obtain appearance features of the winding core; and determining whether to generate a core appearance quality early warning prompt based on the core appearance characteristics. Through the mode, the problems of low efficiency and low accuracy caused by manual intervention can be avoided, so that the automatic detection and control of the appearance quality of the winding core are realized, the production efficiency and the product quality are improved, and the safety risk is reduced.
Description
Technical Field
The application relates to the technical field of intelligent production, in particular to a polymer lithium ion battery production control system and a method thereof.
Background
The polymer lithium ion battery is a commonly used battery type, has the advantages of high energy density, long service life, light weight and the like, and is widely applied to the fields of electric automobiles, portable equipment, energy storage systems and the like. Winding is an important step in the production of polymer lithium ion batteries, where the quality of the appearance of the winding core has a significant impact on the battery performance and safety.
When the appearance quality of the winding core is detected, the parallelism of the battery tab after winding, the black core and the exposed sheet are mainly detected. Specifically, the tab parallelism refers to the parallelism of two tabs of a battery, and directly influences the internal resistance and power output of the battery. Black core refers to incomplete filling of the central portion of the battery winding core, which may lead to loss of battery capacity and risk of thermal runaway. The exposed sheet refers to an exposed electrode sheet which appears outside the battery winding core and can cause short circuit and safety accidents.
However, conventional core appearance quality detection schemes typically rely on manual visual inspection, which requires operators to evaluate the quality of core appearance by experience and subjective judgment. This method is susceptible to individual differences and fatigue of the operator, resulting in inconsistent and inaccurate results. In addition, it is difficult for the conventional solution to accurately capture fine defects in the appearance of the winding core, such as a fine black core or a dew sheet. These minor defects may have potential impact on battery performance and safety, but are difficult to accurately detect by conventional methods.
Accordingly, an optimized polymer lithium ion battery production control system is desired that automatically enables intelligent quality detection of the appearance of the winding core and generates early warning cues.
Disclosure of Invention
The embodiment of the application provides a polymer lithium ion battery production control system and a method thereof, wherein a camera is used for collecting a core appearance image of a detected core; performing image feature analysis on the appearance image of the winding core to obtain appearance features of the winding core; and determining whether to generate a core appearance quality early warning prompt based on the core appearance characteristics. Through the mode, the problems of low efficiency and low accuracy caused by manual intervention can be avoided, so that the automatic detection and control of the appearance quality of the winding core are realized, the production efficiency and the product quality are improved, and the safety risk is reduced.
The embodiment of the application also provides a production control method of the polymer lithium ion battery, which comprises the following steps:
collecting a core appearance image of the detected core through a camera;
performing image feature analysis on the appearance image of the winding core to obtain appearance features of the winding core; and
and determining whether to generate a core appearance quality early warning prompt based on the core appearance characteristics.
The embodiment of the application also provides a polymer lithium ion battery production control system, which comprises:
the image acquisition module is used for acquiring a core appearance image of the detected core through the camera;
the image feature analysis module is used for carrying out image feature analysis on the appearance image of the winding core so as to obtain appearance features of the winding core; and
and the early warning prompt generation module is used for determining whether to generate the early warning prompt of the appearance quality of the winding core based on the appearance characteristics of the winding core.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
fig. 1 is a flowchart of a method for controlling production of a polymer lithium ion battery according to an embodiment of the present application.
Fig. 2 is a schematic diagram of a system architecture of a method for controlling production of a polymer lithium ion battery according to an embodiment of the present application.
Fig. 3 is a flowchart illustrating a sub-step of step 120 in a method for controlling the production of a polymer lithium ion battery according to an embodiment of the present application.
Fig. 4 is a flow chart of a process for generating a polymer lithium ion battery according to an embodiment of the application.
Fig. 5 is a block diagram of a polymer lithium ion battery production control system provided in an embodiment of the application.
Fig. 6 is an application scenario diagram of a method for controlling production of a polymer lithium ion battery according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present application and their descriptions herein are for the purpose of explaining the present application, but are not to be construed as limiting the application.
Unless defined otherwise, all technical and scientific terms used in the embodiments of the application have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present application.
In describing embodiments of the present application, unless otherwise indicated and limited thereto, the term "connected" should be construed broadly, for example, it may be an electrical connection, or may be a communication between two elements, or may be a direct connection, or may be an indirect connection via an intermediate medium, and it will be understood by those skilled in the art that the specific meaning of the term may be interpreted according to circumstances.
It should be noted that, the term "first\second\third" related to the embodiment of the present application is merely to distinguish similar objects, and does not represent a specific order for the objects, it is to be understood that "first\second\third" may interchange a specific order or sequence where allowed. It is to be understood that the "first\second\third" distinguishing objects may be interchanged where appropriate such that embodiments of the application described herein may be practiced in sequences other than those illustrated or described herein.
It should be understood that a polymer lithium ion battery is a lithium ion battery using a polymer electrolyte. Compared with the traditional liquid electrolyte lithium ion battery, the polymer lithium ion battery has higher safety, higher energy density and better flexibility.
The main components of the polymer lithium ion battery comprise a positive electrode, a negative electrode, a polymer electrolyte and a separator. The positive electrode is usually formed by mixing lithium salt (such as LiCoO2, liFePO4, etc.) with a conductive agent, and the negative electrode is usually formed by graphite, silicon, etc. The polymer electrolyte is a core part of a polymer lithium ion battery, and has high ion conductivity, low conductivity and excellent mechanical flexibility. The separator is used for isolating the positive electrode and the negative electrode and preventing short circuit.
The working principle of the polymer lithium ion battery is realized by the migration of lithium ions between the positive electrode and the negative electrode in the charge and discharge process. During charging, lithium ions are released from the positive electrode, migrate through the electrolyte to the negative electrode and intercalate into the negative electrode material. During discharge, lithium ions are released from the negative electrode, migrate through the electrolyte to the positive electrode and intercalate into the positive electrode material. This migration process of lithium ions is accompanied by the flow of electrons, which generate a current for use in an external circuit.
Compared with the traditional liquid lithium ion battery, the polymer lithium ion battery has the following characteristics:
1. polymer electrolyte: polymer lithium ion batteries use polymers as the electrolyte rather than conventional liquid electrolytes. The polymer electrolyte has high ion conductivity, good mechanical strength and chemical stability, and can provide higher safety and durability.
2. High energy density: polymer lithium ion batteries have a higher energy density and are capable of storing more energy in a relatively smaller volume and weight. This makes polymer lithium ion batteries an ideal choice in the fields of portable devices and electric vehicles, etc., capable of providing longer use times and mileage.
3. Rapid charge and discharge performance: the polymer lithium ion battery has good charge and discharge performance and can be charged and discharged rapidly. This means that the user can charge the device or the electric vehicle faster and obtain a higher power output.
4. Low self-discharge rate: polymer lithium ion batteries have a lower self-discharge rate, i.e., the battery has less charge loss when not in use. This results in a polymer lithium ion battery having a longer shelf life and a longer service life.
5. Safety: due to the adoption of the polymer electrolyte, the polymer lithium ion battery has higher safety compared with the traditional liquid lithium ion battery. The polymer electrolyte is not easy to burn at high temperature, and can effectively prevent overheating and thermal runaway of the battery.
In the production process of the polymer lithium ion battery, winding is an important step, the quality of the appearance of the winding core has an important influence on the performance and the safety of the battery, wherein the quality of the appearance of the winding core directly influences the internal resistance of the battery, and if the appearance of the winding core has bad conditions, such as unqualified tab parallelism, black core or exposed sheet, and the like, poor contact or local resistance increase in the battery can be caused, so that the internal resistance of the battery is increased. The increase of the internal resistance affects the charge and discharge efficiency of the battery, and reduces the power output capability of the battery.
Poor appearance quality of the winding core may cause a loss of battery capacity, for example, a black core phenomenon indicates that the central portion of the winding core is not completely filled, resulting in a reduction of battery capacity. If there is a black core problem with the appearance of the winding core, the available capacity of the battery will decrease, reducing the energy storage capacity of the battery.
Poor appearance quality of the winding core may increase the risk of thermal runaway of the battery, for example, the phenomenon of exposed electrode sheets exists outside the winding core of the battery, and if the exposed electrode sheets are contacted with other metal substances, short circuits may be caused, so that the battery is overheated, thermal runaway and even fire explosion occur.
Poor appearance quality of the winding core can affect the cycle life of the battery, and poor appearance of the winding core can cause problems of concentrated internal stress, uneven electrolyte distribution and the like of the battery, so that the attenuation and aging of the battery are accelerated. This shortens the service life of the battery and reduces the cycle life of the battery.
Therefore, ensuring the qualification of the appearance quality of the winding core is critical to the performance and safety of the battery. Through intelligent detection and control of appearance quality of the winding core, adverse conditions can be found and treated early, and quality and reliability of the battery are improved.
In one embodiment of the present application, fig. 1 is a flowchart of a method for controlling production of a polymer lithium ion battery according to an embodiment of the present application. Fig. 2 is a schematic diagram of a system architecture of a method for controlling production of a polymer lithium ion battery according to an embodiment of the present application. As shown in fig. 1 and 2, a method 100 for controlling production of a polymer lithium ion battery according to an embodiment of the present application includes: 110, collecting a core appearance image of the detected core through a camera; 120, performing image feature analysis on the appearance image of the winding core to obtain appearance features of the winding core; and 130, determining whether to generate a core appearance quality early warning prompt based on the core appearance characteristics.
In the step 110, the position and angle of the camera are ensured to accurately capture the appearance details of the winding core, so as to facilitate subsequent image analysis and feature extraction. The camera is used for collecting the appearance image of the winding core, so that non-contact detection can be realized, physical contact of the winding core is avoided, potential damage risk is reduced, and production efficiency is improved.
In the step 120, a suitable image processing algorithm and technique is selected to analyze and process the core appearance image to extract representative core appearance features. Through image feature analysis, key feature information of the appearance of the winding core, such as tab parallelism, black cores, exposed sheets and the like, can be obtained. These features can be used to evaluate the quality of the appearance of the winding core, providing a basis for subsequent quality determinations.
In the step 130, the extracted appearance characteristics of the winding core are determined according to the preset appearance quality standard and threshold value of the winding core, and whether the appearance quality early warning prompt of the winding core is generated is determined. The situation of poor appearance quality of the winding core can be timely found through the judgment based on the appearance characteristics of the winding core, and an early warning prompt is provided. This helps to find potential quality problems early, and corresponding measures are taken to adjust and correct, thereby improving the production quality and stability of the battery.
By the production control method, intelligent detection and control of appearance quality of the polymer lithium ion battery winding core can be realized by combining camera acquisition, image feature analysis and quality early warning prompt. This helps to improve production efficiency, reduce defective product rate, and ensure that the performance and safety of the battery meet the requirements.
Specifically, in the step 110, a core appearance image of the detected core is acquired by a camera. Aiming at the technical problems, the technical conception of the application is that in the winding process, the appearance image of the winding core is acquired through a camera, and an image processing and analyzing algorithm is introduced at the rear end to carry out quality detection on the appearance of the winding core (pole lug parallelism, black core, exposed sheet and the like) so as to judge whether the appearance of the winding core meets the preset standard or not, and an early warning prompt is generated.
Specifically, in the technical scheme of the application, firstly, a core appearance image of a detected core acquired by a camera is acquired. The following useful information can be extracted from the core appearance image of the detected core:
appearance defects, core appearance images may show defects on the core surface such as cracks, bubbles, contamination, etc. Through image processing and analysis, the characteristics of the appearance defects, such as size, shape, distribution and the like, can be extracted, and further the severity of the defects and the influence on the battery performance are judged.
Size and shape the core appearance image may provide size and shape information for the core. By measuring and analyzing dimensional parameters in the image, such as length, width, thickness, etc., it is possible to evaluate whether the geometric characteristics of the winding core meet specifications.
The distribution of the electrodes can be displayed by the appearance image of the winding core, and the distribution of the electrodes comprises the positions, symmetry and the like of the anode and the cathode. The centering and offset conditions of the electrodes can be judged by analyzing the distribution conditions of the electrodes, so that the consistency and the performance stability of the battery are evaluated.
Black core and exposed sheet, the appearance image of the winding core can display the condition of the black core and the exposed sheet. The black core refers to the opaque region in the central region of the core and the exposed sheet refers to the electrode exposure in the edge region of the core. By analyzing the black core and the open sheet condition in the image, the uniformity of the winding core and the electrode coverage condition can be evaluated.
Other features, such as color distribution, texture features, etc., may also be extracted from the core appearance image, as desired. These features can be used for further quality decisions and early warning cues.
By carrying out feature extraction and analysis on the appearance image of the winding core acquired by the camera, key appearance information can be acquired and used for judging whether the appearance quality of the winding core meets the requirement or not and generating corresponding early warning prompt. The method is favorable for early finding potential quality problems, and measures are taken to adjust and correct, so that the production quality and the safety of the battery are ensured.
Further, in said step 110, the core appearance image acquired by the camera provides visual information on the core appearance, which enables the operator to directly observe and analyze the appearance characteristics of the core, including shape, color, texture, etc. Through visual information, some obvious appearance defects and anomalies such as cracks, deformation, pollution and the like can be captured.
The camera is non-contact in the process of collecting the appearance image of the winding core, and the winding core is not required to be in direct contact, so that potential physical damage and pollution risks are avoided. The non-contact detection not only improves the production efficiency, but also protects the integrity and quality of the winding core.
The image collected by the camera can be processed and analyzed to extract key characteristics of the appearance of the winding core, the characteristics can be used for subsequent image characteristic analysis, and whether the quality of the appearance of the winding core meets the preset standard is automatically judged by the algorithm and the operation of the model. The automatic analysis greatly reduces subjectivity and inconsistency of manual judgment and improves accuracy and reliability of judgment.
The real-time monitoring and early warning can be realized through the images acquired by the cameras, and the image processing and analysis can be completed in a short time, so that the quality condition of the appearance of the winding core can be rapidly judged. Once the quality problem of the appearance of the winding core is found, the system can immediately generate an early warning prompt to inform related personnel to take corresponding measures, and the corresponding measures are processed and adjusted in time so as to avoid further production and outflow of defective products.
Visual information can be provided by collecting the appearance image of the winding core through the camera, non-contact detection is realized, automatic analysis is supported, and real-time monitoring and early warning are realized. The effects are helpful for improving the detection efficiency and accuracy of the appearance quality of the winding core, and ensuring the quality control and the timely treatment of the problems in the production process.
Specifically, in the step 120, fig. 3 is a flowchart illustrating the substeps of the step 120 in the method for controlling the production of a polymer lithium ion battery according to the embodiment of the present application, as shown in fig. 3, the image feature analysis is performed on the appearance image of the winding core to obtain appearance features of the winding core, including: 121, passing the core appearance image through a backbone network-based core appearance feature extractor to obtain a core appearance feature map; 122, performing multi-scale pooling treatment on the winding core appearance feature images to obtain a plurality of winding core appearance pooled feature images; and, 123, performing context aggregation on the plurality of core appearance pooling feature maps to obtain a context aggregated core appearance feature map as the core appearance feature.
Wherein the backbone network is a convolutional neural network model.
Through the steps, firstly, key features in the appearance image of the winding core can be effectively extracted by using a backbone network-based appearance feature extractor, and the features can capture details and structural information of the appearance of the winding core, including textures, shapes, edges and the like. The image can be converted into the appearance characteristic diagram of the winding core through the characteristic extractor, so that the characteristic diagram is more abstract and representative.
Then, the multi-scale pooling processing is carried out on the appearance characteristic diagram of the winding core, so that characteristic information under different scales can be extracted, global and local characteristics of the appearance of the winding core can be captured, and the appearance condition of the winding core can be described more comprehensively. Multiscale pooling can enhance the robustness and discrimination capability of features.
Then, context aggregation is carried out on the pooled feature graphs of the appearance of the plurality of winding cores, and information of different scales and positions can be comprehensively utilized. The context aggregation can fuse local features and global features in a convolution mode, an attention mechanism mode and the like, and a winding core appearance feature map with more representativeness and rich semantic information is obtained. Such a profile may better represent the overall quality and appearance characteristics of the winding core.
Through the steps 121, 122 and 123, the appearance characteristics of the winding core with higher hierarchy and more abundance can be obtained, and the characteristics have better expression capability and discrimination capability, thereby being beneficial to more accurately judging whether the appearance quality of the winding core meets the requirement. The feature extraction and analysis method can improve the accuracy and efficiency of the appearance quality detection of the winding core, and help to realize intelligent production control and quality management.
Next, considering that the appearance quality of the winding core mainly refers to the characteristics of the coiled battery tab parallelism, the black core, the exposed piece and the like, wherein the tab parallelism refers to the parallelism of two tabs of the battery, and the internal resistance and the power output of the battery are directly affected; black core refers to incomplete filling of the central portion of the battery winding core, which may lead to loss of battery capacity and risk of thermal runaway; the exposed sheet refers to an exposed electrode sheet which appears outside the battery winding core and can cause short circuit and safety accidents. Therefore, in order to effectively detect the appearance quality of the winding core, it is necessary to extract the feature information such as the parallelism of the tab of the winding core after winding, the black core, and the exposed sheet. Specifically, feature mining of the image is performed using a convolutional neural network model having excellent performance in terms of implicit feature extraction of the image, that is, the core appearance image is feature mined by a core appearance feature extractor based on a backbone network, in particular, the backbone network is a convolutional neural network model, so as to extract implicit feature distribution information of the core appearance quality, thereby obtaining a core appearance feature map.
The step 122 of performing multi-scale pooling processing on the core appearance feature map to obtain a plurality of core appearance pooled feature maps includes: and carrying out multi-scale space pooling on the core appearance characteristic images by using pooling cores with different scales to obtain a plurality of core appearance pooled characteristic images.
Then, it is also considered that in the actual winding process, the appearance defect with respect to the winding core may be minute, such as minute black core or exposed sheet. These minor imperfections can potentially impact battery performance and safety, but are difficult to effectively capture and quality detect by conventional feature extraction means. That is, in the core appearance image, feature information of different scales may play a different role in judging the core appearance quality, some features may be more obvious on a smaller scale, and other features may be more obvious on a larger scale.
Based on the above, in the technical scheme of the application, the pooling check with different scales is further used for carrying out multi-scale space pooling on the appearance characteristic diagrams of the winding cores so as to obtain a plurality of pooled appearance characteristic diagrams of the winding cores. It should be appreciated that downsampling of the image is required because deep learning models often have memory and computational resource limitations in processing high resolution images. However, conventional pooling operations can only be performed over a fixed size window, and typically employ fixed step sizes for sampling, which is prone to information loss and excessive smoothing problems. The pooling cores with different scales can provide a plurality of pooling windows with different sizes, so that the network can better explore the characteristic information with different scales related to the appearance quality of the winding core, and further capture the details and the integral characteristics with different scales related to the appearance quality of the winding core, and the final characteristic representation is more comprehensive and rich. Meanwhile, the problem of excessive smoothness of the sampled characteristics can be avoided, the robustness and accuracy of the model are further improved, and the appearance quality of the winding core can be better detected, so that whether the appearance of the winding core meets the preset standard or not can be judged.
For the step 123, performing context aggregation on the plurality of core appearance pooling feature maps to obtain a context aggregated core appearance feature map as the core appearance feature, including: and performing context aggregation based on characteristic content on the plurality of core appearance pooled characteristic diagrams by using a context content encoder to obtain the context aggregated core appearance characteristic diagrams.
Further, since the separately extracted core appearance pooling feature map only contains feature information about local or local combinations of core appearance quality in core appearance quality detection, the global view angle and context relationship is lacking. However, the quality of the appearance of the winding core is often affected by the overall structure and adjacent areas. Therefore, in the technical scheme of the application, a context content encoder is further used for carrying out context aggregation on the feature content-based feature images of the plurality of core appearance pooling feature images to obtain a context aggregation core appearance feature image, so that a more representative and global feature representation is obtained. Thus, accuracy and robustness of appearance quality detection of the winding core are improved, and the system can better understand and judge the appearance quality of the winding core.
It should be appreciated that the context encoder is intended to mine for hidden patterns between contexts in a word sequence, optionally the encoder comprises: CNN (Convolutional Neural Network ), recurrent NN (RecursiveNeural Network, recurrent neural network), language Model (Language Model), and the like. The CNN-based method has a better extraction effect on local features, but has a poor effect on Long-Term Dependency (Long-Term Dependency) problems in sentences, so Bi-LSTM (Long Short-Term Memory) based encoders are widely used. The repetitive NN processes sentences as a tree structure rather than a sequence, has stronger representation capability in theory, but has the weaknesses of high sample marking difficulty, deep gradient disappearance, difficulty in parallel calculation and the like, so that the repetitive NN is less in practical application. The transducer has a network structure with wide application, has the characteristics of CNN and RNN, has a better extraction effect on global characteristics, and has a certain advantage in parallel calculation compared with RNN (RecurrentNeural Network ).
Specifically, in the step 130, determining whether to generate the core appearance quality warning cue based on the core appearance feature includes: performing feature distribution optimization on the context aggregation roll core appearance feature map to obtain an optimized context aggregation roll core appearance feature map; the appearance characteristic diagram of the optimized context aggregation winding core is passed through a classifier to obtain a classification result, wherein the classification result is used for indicating whether the appearance of the winding core meets a preset standard or not; and generating a production control instruction based on the classification result, wherein the production control instruction is used for indicating whether the appearance quality early warning prompt of the winding core is generated or not.
In particular, in the technical solution of the present application, when the pooling feature images with different scales are used to perform multi-scale spatial pooling to obtain the plurality of core appearance pooled feature images, and the context content encoder is used to perform context polymerization based on feature content on the plurality of core appearance pooled feature images, it is desirable that the context polymerized core appearance feature images express context-associated image semantic features of the plurality of core appearance pooled feature images with different scales, and meanwhile, local spatial-associated image semantic features of the core appearance images expressed by the core appearance pooled feature images with different scales still have good expression under a classification rule, so that correction of the context polymerized core appearance feature images is required based on the local spatial-associated image semantic feature representation of the core appearance feature images.
Based on this, the applicant of the present application has a characteristic view of the appearance of the winding core, for example noted asAnd the contextual polymeric core appearance feature map, e.g., noted +.>Performing smooth response parameterization decoupling fusion to obtain an optimized context aggregation roll core appearance characteristic diagram, for example, marked as +.>The method specifically comprises the following steps: performing smooth response parameterization decoupling fusion on the core appearance characteristic diagram and the context aggregation core appearance characteristic diagram by using the following optimization formula to obtain the optimized context aggregation core appearance characteristic diagram; wherein, the optimization formula is: />Wherein->And->The core appearance characteristic diagram and the context aggregation core appearance characteristic diagram are respectively,representing the cosine distance between the core appearance feature map and the contextual polymeric core appearance feature map, and +.>As a logarithmic function with base 2 +.>An exponential operation representing a feature map representing a natural exponential function value raised to a power by feature values at respective positions in the feature map,/>Representing subtraction by position +.>Representing addition by position +.>Representing multiplication by location +.>Is the appearance characteristic diagram of the optimized context aggregation roll core.
Here, the smoothing response parameterized decoupling fusion is based on the core appearance feature map by using a decoupling principle of a smoothing parameterization functionAnd the contextual polymeric core appearance feature map +.>Non-negative symmetry of cosine distance between said winding cores appearance characteristic map +.>And the contextual polymeric core appearance feature map +.>Point-by-point embedding between features of (a) to infer the core appearance profile with a spatial transformation between features (transformation)>And the contextual polymeric core appearance feature map +.>Information distribution transfer (information distribution shift) between the expression features so as to express information structured fusion of smooth response between the features under class rules, thereby improving the optimized context aggregation roll core appearance feature map->And for the expression effect of the local space associated image semantic features of the roll core appearance feature map based on the classification rule, improving the accuracy of the classification result obtained by the classifier of the optimized context aggregation roll core appearance feature map. In this way, the appearance quality of the winding core can be effectively detected in the production process of the polymer lithium ion battery, and the quality of the winding core can be effectively detectedThe defective winding core generates early warning prompt, so that the production efficiency and the product quality are improved, and the safety risk is reduced.
In one embodiment of the present application, the optimizing the context-aggregation core appearance feature map is passed through a classifier to obtain a classification result, where the classification result is used to indicate whether the core appearance meets a predetermined criterion, and the method includes: expanding the appearance feature map of the optimized context aggregation roll core into classification feature vectors according to row vectors or column vectors; performing full-connection coding on the classification feature vectors by using a plurality of full-connection layers of the classifier to obtain coded classification feature vectors; and passing the coding classification feature vector through a Softmax classification function of the classifier to obtain the classification result.
And then, the context aggregation roll core appearance characteristic diagram is passed through a classifier to obtain a classification result, wherein the classification result is used for indicating whether the roll core appearance meets a preset standard. That is, the classification processing is performed with the global multi-scale context-related feature information of the appearance quality of the winding core, so as to evaluate and judge whether the appearance quality (tab parallelism, black core, exposed sheet, etc.) of the winding core meets the predetermined standard. And generating a production control instruction based on the classification result, wherein the production control instruction is used for indicating whether the appearance quality early warning prompt of the winding core is generated. Through the mode, the problems of low efficiency and low accuracy caused by manual intervention can be avoided, so that real-time automatic detection and control of appearance quality of the winding core are realized, production efficiency and product quality are improved, and safety risk is reduced.
In summary, the method 100 for controlling production of a polymer lithium ion battery according to the embodiment of the application is illustrated, in the winding process, an appearance image of a winding core is collected by a camera, and an image processing and analyzing algorithm is introduced at the rear end to perform quality detection on the appearance of the winding core (such as parallelism of tabs, black core, exposed sheet, etc.) so as to determine whether the appearance of the winding core meets a predetermined standard, and generate an early warning prompt.
In a specific example of the present application, as shown in fig. 4, a process flow for generating a polymer lithium ion battery is provided, which includes the steps of:
s1, proportioning: and (3) according to the formula requirement of the battery, the required raw materials are proportioned according to a certain proportion. These raw materials include positive electrode materials, negative electrode materials, electrolytes, and other additives.
S2, coating: in the coating step, the positive electrode material and the negative electrode material in the formulation are coated on the conductive current collector, respectively. The positive and negative electrodes may be coated by different methods, such as thickness measurement coating or knife coating.
S3, roll pressing: the roll pressing is to compact the coated positive and negative electrode materials and the current collector to ensure good contact between the positive and negative electrode materials and the current collector. This step helps to improve the energy density and cycle performance of the battery.
S4, slitting: in the slitting step, the composite sheet of the anode and cathode materials and the current collector which are pressed by the rod is cut into proper widths so as to facilitate the subsequent sheet making process.
S5, tabletting: the sheet making is to cut the composite sheet of the positive and negative electrode materials and the current collector obtained by the slitting into proper lengths through a certain technological method to form a single sheet assembly of the battery.
S6, winding: in the winding step, the flaked anode and cathode materials and the current collector flaky assembly are wound together in a certain mode to form a laminated structure of the battery. Care must be taken in winding to avoid shorting by insulating between the positive and negative electrodes.
S7, appearance total inspection of the winding core: in the appearance full inspection of the winding core, the appearance inspection is performed on the wound battery core, so that no obvious defects or damages such as pits, cracks and the like are ensured.
S8, shell punching: the punching shell is to put the coiled battery core into a metal shell and seal the battery core so as to protect the internal structure of the battery from the external environment.
S9, formation: in the formation step, the battery cells that have been punched out are connected to a specific battery test device, and a primary charge-discharge cycle is performed to activate the battery and evaluate the performance thereof.
S10, intelligent activation liquid injection/pre-sealing: in the intelligent activation liquid injection/pre-sealing step, electrolyte is injected into the formed battery core, and pre-sealing treatment is carried out to ensure the tightness and stability of the inside of the battery.
S11, vacuum laying: in the vacuum placing stage, the injected and pre-sealed battery core is placed in a vacuum environment, so that the sealing performance and stability of the inside of the battery are further improved.
S12, capacity division: the capacity division is to test and classify the capacity of the battery cells which are already subjected to vacuum placement, and classify the battery cells according to the capacity.
S13, vacuum baking: in the vacuum baking step, the separated battery core is placed into baking equipment and baked under certain temperature and humidity conditions, so that the stability and reliability of the inside of the battery are further improved.
S14, aging: aging is a long-time charge-discharge cycle test of the vacuum baked battery cell to evaluate the performance, cycle life and safety of the battery.
S15, shipment: in the shipment step, the battery cells that pass the burn-in test will be packaged and ready for shipment.
S16, basket-loading flaring: basket flaring is the step of placing the shipped battery cells into designated baskets or containers and performing a flaring process for subsequent testing and packaging processes.
S17, voltage/internal resistance test: in the voltage/internal resistance testing step, the battery core after basket-charging flaring is subjected to voltage and internal resistance testing so as to ensure that the battery core meets the specified standard and requirement.
S18, packaging and warehousing: the battery cells passing the voltage/internal resistance test are packed and put in storage to wait for subsequent PACK processing.
S19, four-in-one top side seal: in the four-in-one top side sealing step, the packaged and warehoused battery cells and other components (such as a protection plate, a connecting wire and the like) are assembled, and top side packaging is carried out to form the final battery PACK.
S20, appearance total inspection: in the appearance total inspection step, appearance inspection is carried out on the battery PACK with the four-in-one top side sealed, so that no obvious defect or damage is ensured.
S21, winding core short circuit test: the winding core short circuit test is to carry out short circuit test on the battery PACK with four-in-one top side sealed so as to ensure the safety and reliability of the battery PACK.
S22, warehouse entry: the battery PACK which is qualified through appearance full inspection and core short circuit test is put in storage and waits for subsequent delivery and sales.
S23, PACK processing: PACK processing refers to assembling a warehouse-in battery PACK with other components (e.g., a housing, a connector, etc.), and final packaging and identification.
Fig. 5 is a block diagram of a polymer lithium ion battery production control system provided in an embodiment of the application. As shown in fig. 5, the polymer lithium ion battery production control system includes: the image acquisition module 210 is used for acquiring a core appearance image of the detected core through a camera; the image feature analysis module 220 is configured to perform image feature analysis on the core appearance image to obtain core appearance features; and an early warning prompt generation module 230, configured to determine whether to generate an early warning prompt for appearance quality of the winding core based on the appearance characteristics of the winding core.
Specifically, in the polymer lithium ion battery production control system, the image feature analysis module includes: the appearance characteristic extraction unit is used for enabling the winding core appearance image to pass through a winding core appearance characteristic extractor based on a backbone network so as to obtain a winding core appearance characteristic image; the multi-scale pooling processing unit is used for carrying out multi-scale pooling processing on the appearance characteristic diagrams of the winding cores to obtain a plurality of appearance pooled characteristic diagrams of the winding cores; and a context aggregation unit, configured to perform context aggregation on the plurality of core appearance pooling feature maps to obtain a context aggregated core appearance feature map as the core appearance feature.
It will be appreciated by those skilled in the art that the specific operations of the respective steps in the above-described polymer lithium ion battery production control system have been described in detail in the above description of the polymer lithium ion battery production control method with reference to fig. 1 to 4, and thus, repetitive descriptions thereof will be omitted.
As described above, the polymer lithium ion battery production control system 100 according to the embodiment of the present application may be implemented in various terminal devices, such as a server for polymer lithium ion battery production control, and the like. In one example, the polymer lithium ion battery production control system 100 according to embodiments of the present application may be integrated into the terminal device as a software module and/or hardware module. For example, the polymer lithium ion battery production control system 100 may be a software module in the operating system of the terminal device, or may be an application developed for the terminal device; of course, the polymer lithium ion battery production control system 100 can also be one of the numerous hardware modules of the terminal device.
Alternatively, in another example, the polymer lithium ion battery production control system 100 and the terminal device may be separate devices, and the polymer lithium ion battery production control system 100 may be connected to the terminal device through a wired and/or wireless network and transmit the interactive information in a agreed data format.
Fig. 6 is an application scenario diagram of a method for controlling production of a polymer lithium ion battery according to an embodiment of the present application. As shown in fig. 6, in this application scenario, first, a core appearance image of a detected core is acquired by a camera (e.g., C as illustrated in fig. 6); the obtained core appearance image is then input into a server (e.g., S as illustrated in fig. 6) deployed with a polymer lithium ion battery production control algorithm, wherein the server is capable of processing the core appearance image based on the polymer lithium ion battery production control algorithm to determine whether to generate a core appearance quality pre-warning cue.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the application, and is not meant to limit the scope of the application, but to limit the application to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (10)
1. A method for controlling the production of a polymer lithium ion battery, comprising the steps of:
collecting a core appearance image of the detected core through a camera;
performing image feature analysis on the appearance image of the winding core to obtain appearance features of the winding core; and
and determining whether to generate a core appearance quality early warning prompt based on the core appearance characteristics.
2. The method according to claim 1, wherein performing image feature analysis on the core appearance image to obtain core appearance features comprises:
the appearance image of the winding core passes through a winding core appearance characteristic extractor based on a backbone network to obtain an appearance characteristic image of the winding core;
carrying out multi-scale pooling treatment on the appearance characteristic diagrams of the winding cores to obtain a plurality of pooled appearance characteristic diagrams of the winding cores; and
and performing context aggregation on the plurality of core appearance pooling feature images to obtain a context aggregation core appearance feature image serving as the core appearance feature.
3. The method of claim 2, wherein the backbone network is a convolutional neural network model.
4. The method of claim 3, wherein the multi-scale pooling of the core appearance feature map to obtain a plurality of core appearance pooled feature maps comprises: and carrying out multi-scale space pooling on the core appearance characteristic images by using pooling cores with different scales to obtain a plurality of core appearance pooled characteristic images.
5. The method of claim 4, wherein context polymerizing the plurality of core appearance pooling feature maps to obtain a context polymerized core appearance feature map as the core appearance feature, comprises: and performing context aggregation based on characteristic content on the plurality of core appearance pooled characteristic diagrams by using a context content encoder to obtain the context aggregated core appearance characteristic diagrams.
6. The method of claim 5, wherein determining whether to generate a core appearance quality warning cue based on the core appearance characteristics comprises:
performing feature distribution optimization on the context aggregation roll core appearance feature map to obtain an optimized context aggregation roll core appearance feature map;
the appearance characteristic diagram of the optimized context aggregation winding core is passed through a classifier to obtain a classification result, wherein the classification result is used for indicating whether the appearance of the winding core meets a preset standard or not; and
and generating a production control instruction based on the classification result, wherein the production control instruction is used for indicating whether the appearance quality early warning prompt of the winding core is generated or not.
7. The method of claim 6, wherein optimizing the profile distribution of the contextual polymeric core appearance profile to obtain an optimized contextual polymeric core appearance profile comprises:
performing smooth response parameterization decoupling fusion on the core appearance characteristic diagram and the context aggregation core appearance characteristic diagram by using the following optimization formula to obtain the optimized context aggregation core appearance characteristic diagram;
wherein, the optimization formula is:wherein->Andthe core appearance characteristic diagram and the context aggregation core appearance characteristic diagram are respectively +.>Representing the cosine distance between the core appearance feature map and the contextual polymeric core appearance feature map, and +.>As a logarithmic function with base 2 +.>An exponential operation representing a feature map representing a natural exponential function value raised to a power by feature values at respective positions in the feature map,/>Representing subtraction by position +.>Representing addition by position +.>Representing multiplication by location +.>Is the appearance characteristic diagram of the optimized context aggregation roll core.
8. The method of claim 7, wherein the step of passing the optimized contextual polymeric core appearance profile through a classifier to obtain a classification result, the classification result being used to indicate whether the core appearance meets a predetermined criterion, comprises:
expanding the appearance feature map of the optimized context aggregation roll core into classification feature vectors according to row vectors or column vectors;
performing full-connection coding on the classification feature vectors by using a plurality of full-connection layers of the classifier to obtain coded classification feature vectors; and
and the coding classification feature vector is passed through a Softmax classification function of the classifier to obtain the classification result.
9. A polymer lithium ion battery production control system, comprising:
the image acquisition module is used for acquiring a core appearance image of the detected core through the camera;
the image feature analysis module is used for carrying out image feature analysis on the appearance image of the winding core so as to obtain appearance features of the winding core; and
and the early warning prompt generation module is used for determining whether to generate the early warning prompt of the appearance quality of the winding core based on the appearance characteristics of the winding core.
10. The polymer lithium ion battery production control system of claim 9, wherein the image feature analysis module comprises:
the appearance characteristic extraction unit is used for enabling the winding core appearance image to pass through a winding core appearance characteristic extractor based on a backbone network so as to obtain a winding core appearance characteristic image;
the multi-scale pooling processing unit is used for carrying out multi-scale pooling processing on the appearance characteristic diagrams of the winding cores to obtain a plurality of appearance pooled characteristic diagrams of the winding cores; and
and the context aggregation unit is used for conducting context aggregation on the plurality of core appearance pooling feature images to obtain a context aggregation core appearance feature image serving as the core appearance feature.
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