A battery electrolyte experiment research and development system, method and device

Abstract

The application provides a battery electrolyte experiment research and development system, method and equipment. Through the cooperative matching of the modular experimental device, the intelligent transfer robot and the scheduling device, the efficiency, flexibility and automation of the battery electrolyte experiment research and development are realized. The scheduling device determines the function module selection configuration scheme and generates a research and development task sequence by analyzing the research and development requirements and the battery model of the target battery, so that the selection and development process execution of the function module are accurately matched with the actual research and development requirements, and the waste of redundant procedures and equipment resources is avoided. Meanwhile, the standardized research and development task sequence solves the problem of chaotic connection of traditional research and development procedures. The modular experimental device is configured with multiple function modules which can be selected as needed, so as to realize flexible combination and adaptation of different battery models and research and development requirements. The intelligent transfer robot automatically transfers the battery, materials and experimental containers among the function modules according to the research and development task sequence, thereby improving the automation degree and operation efficiency of the research and development process.

Description

Technical Field

[0001] This application belongs to the field of battery manufacturing, and in particular relates to a battery electrolyte experimental research and development system, method and equipment. Background Technology

[0002] Electrolytes, as the core medium for ion transport and interfacial reaction regulation in batteries, directly determine the rate capability, cycle stability, and safety of the battery, making them a crucial element in the development of next-generation battery technologies. However, current electrolyte experimental research relies on decentralized, fixed systems, which cannot flexibly design experiments according to different battery models and research needs. This results in poor system adaptability and low utilization. Furthermore, the transfer of cells and materials between different processes depends on manual labor, leading to low research efficiency, easy introduction of operational errors, poor consistency of experimental results, and potential problems such as chaotic process connections and insufficient research focus, thus increasing the research cycle and costs. Summary of the Invention

[0003] This application provides a battery electrolyte experimental research and development system, method, and equipment, which can solve the problems of existing electrolyte experimental research and development relying on decentralized fixed systems, which have low utilization rates, low research and development efficiency, and are prone to operational errors, resulting in poor consistency of experimental results. At the same time, it is easy to have chaotic process connections and insufficient research and development focus, which increases the research and development cycle and cost.

[0004] In a first aspect, embodiments of this application provide a battery electrolyte experimental research and development system, the system comprising: The scheduling device is used to analyze the R&D requirements and battery models of the target battery, determine the selection and configuration scheme of functional modules, and generate a matching R&D task sequence based on the selection and configuration scheme. Intelligent transfer robots are used to automatically transfer battery cells, materials and experimental containers between various functional modules in the selected configuration scheme according to the R&D task sequence. The modular experimental device includes multiple functional modules that can be selected and configured as needed. The modular experimental device is used to perform corresponding R&D procedures in dry cell preparation, electrolyte preparation and injection, and battery performance testing according to the R&D task sequence.

[0005] In one feasible implementation, the above-mentioned modular experimental device includes at least one of the following: a dry cell preparation module, an electrolyte preparation and post-injection treatment module, and a battery performance testing module. The dry cell preparation module is used to perform the forming, stacking or winding of the positive and negative electrodes, complete the connection and welding of the tabs or current collectors, pre-package the cell structure, and dry or pre-treat the cell to obtain a dry cell. The electrolyte preparation, injection, and post-processing module is used to perform solid and liquid raw material feeding, electrolyte raw material mixing and homogenization to obtain electrolyte, injecting electrolyte into dry cell and performing vacuum or negative pressure wetting treatment, performing battery packaging and post-processing to obtain the battery to be tested. The battery performance testing module is used to perform one or more of the following tests on the battery under test: rate performance test, long cycle life test, internal resistance or impedance test, and high and low temperature test, to obtain the battery performance test results.

[0006] In one feasible implementation, the above-described modular experimental apparatus further includes an electrolyte characterization module; The electrolyte characterization module is used to perform one or more tests on the prepared electrolyte, including conductivity testing, viscosity testing, infrared spectroscopy testing, and Raman spectroscopy testing, to obtain the electrolyte property characterization results.

[0007] In one feasible implementation, the scheduling device includes: The comparison module is used to receive the electrolyte property characterization results and compare the electrolyte property characterization results with the preset electrolyte property thresholds; The first execution module is used to trigger the battery performance testing module to perform performance testing on the battery under test when the electrolyte property characterization results meet the preset electrolyte property threshold. The second execution module is used to mark the corresponding electrolyte formula as to be reconstituted or eliminated and terminate the process if the electrolyte property characterization results do not meet the preset electrolyte property threshold.

[0008] In one feasible implementation, the electrolyte preparation, injection, and post-processing module includes: The wetting state determination unit is used to monitor and record one or more monitoring data such as pressure change, processing time, and cell quality change in real time during vacuum or negative pressure wetting process, so as to determine the wetting state of electrolyte in dry cell based on the monitoring data. The re-wetting unit is used to perform vacuum or negative pressure wetting treatment again if the wetting state does not meet the preset standard state.

[0009] In one feasible implementation, the electrolyte preparation, injection, and post-processing module includes: The weighing unit is used to obtain the actual feed amount of solid and liquid raw materials; The feed rate comparison unit is used to compare the actual feed rate with the preset feed rate. The correction unit is used to correct the feeding action based on the preset deviation value when the actual deviation value between the actual feed amount and the preset feed amount reaches the preset deviation value, so that the actual deviation value is less than the preset deviation value.

[0010] In one feasible implementation, the scheduling device includes: The task orchestration module is used to break down the R&D requirements of the target battery into cell preparation indicators, electrolyte performance indicators, and testing dimension indicators. It selects and combines suitable functional modules according to the battery model, and decomposes the R&D process into multiple process tasks according to the process sequence, as the R&D task sequence. The resource allocation module is used to allocate corresponding functional module resources, intelligent transfer robot resources, and workstation resources to the R&D task sequence based on the operating status of each functional module and the operational capabilities of the intelligent transfer robot. The priority management module is used to set the execution priority of each R&D task in the R&D task sequence based on R&D needs or R&D timeliness requirements.

[0011] In one feasible implementation, the scheduling device further includes an exception handling module; The exception handling module is used to monitor the operating status of each functional module, the operation status of the intelligent transfer robot, and the execution progress of the R&D process in real time. When a functional module failure, an abnormal operation of the intelligent transfer robot, or a deviation in the execution of the process is detected, the corresponding resources are reallocated to the R&D task sequence and the R&D task sequence is adjusted.

[0012] In one feasible implementation, the aforementioned intelligent transfer robot includes: The positioning and navigation module is used to complete path planning and perform obstacle avoidance in real time as the intelligent transfer robot moves; The mobile chassis drive module is used to drive the intelligent transfer robot to move between various functional modules based on path planning; The gripping and handling execution module is used to grip, transfer, and place battery cells, materials, and experimental containers.

[0013] In one feasible implementation, the system further includes a data management device; The data management device is used to collect and store process data, system status data, and battery performance test results generated during system operation.

[0014] In one feasible implementation, the above-mentioned data management device includes: The data acquisition module is used to collect in real time the operating parameters of each functional module, process execution data, equipment fault and abnormal information, and battery performance test results. The data alignment and traceability module is used to associate electrolyte formula information, process conditions of each R&D process, system status data, and battery performance test results data one by one, and establish an association mapping relationship identified by formula name and cell name. The data storage module is used to classify and store the association mapping relationships in a structured form, and to perform data deduplication and consistency verification.

[0015] Secondly, this application provides a method for experimental research and development of battery electrolytes. This method is applied to a battery electrolyte research and development system, which includes a modular experimental device, an intelligent transfer robot, and a scheduling device. The modular experimental setup includes multiple functional modules that can be selected and configured as needed; The above methods include: The scheduling device analyzes the R&D requirements and battery model of the target battery, determines the selection and configuration scheme of functional modules, and generates a matching R&D task sequence based on the selection and configuration scheme. Intelligent transfer robots automatically transfer battery cells, materials, and experimental containers between various functional modules in the selected configuration scheme according to the R&D task sequence. The modular experimental device executes the corresponding R&D procedures in dry cell preparation, electrolyte preparation and injection, and battery performance testing according to the R&D task sequence.

[0016] Thirdly, this application provides a battery electrolyte experimental research and development device, the device including: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the battery electrolyte experimental research and development method as described above.

[0017] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the battery electrolyte experimental development method described above.

[0018] Fifthly, embodiments of this application provide a computer program product, including a computer program, which, when executed, implements any of the battery electrolyte experimental development methods described in the above embodiments.

[0019] The battery electrolyte experimental research and development system, method, and equipment of this application, through the coordinated operation of modular experimental devices, intelligent transfer robots, and scheduling devices, achieve high efficiency, flexibility, and automation in battery electrolyte experimental research and development. Specifically, the scheduling device determines the selection and configuration scheme of functional modules and generates a research and development task sequence by analyzing the research and development needs and battery model of the target battery. This ensures that the selection of functional modules and the execution of the research and development process accurately match the actual research and development needs, avoiding redundant procedures and wasting equipment resources, improving the research and development focus and equipment utilization rate. At the same time, the standardized research and development task sequence makes the research and development process more standardized, solving the problem of chaotic connections in traditional research and development processes; modular experimental... The device is equipped with multiple selectable functional modules, which can be flexibly combined and matched according to different battery models and R&D needs. This breaks the limitation of fixed equipment on the R&D of multiple battery models, significantly improves the flexibility of the R&D system, and reduces process switching and system investment costs. The intelligent transfer robot automatically transfers battery cells, materials and experimental containers between functional modules according to the R&D task sequence, replacing the traditional manual transfer method. This not only eliminates the errors introduced by manual operation and improves the consistency and reproducibility of experimental results, but also improves the automation and efficiency of the R&D process, reduces the safety risks caused by human intervention, realizes the connection of R&D procedures, effectively shortens the electrolyte R&D cycle, and improves the overall R&D efficiency. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the structure of a battery electrolyte experimental research and development system provided in an embodiment of this application; Figure 2 This is a structural example diagram of a battery electrolyte experimental research and development system provided in an embodiment of this application; Figure 3 This is a flowchart illustrating an experimental development method for battery electrolyte provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a battery electrolyte experimental research and development device provided in an embodiment of this application; The annotations in the attached figures are explained as follows: 101-Dispatch device, 102-Intelligent transfer robot, 103-Modular experimental device, 204-Data management device. Detailed Implementation

[0022] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0023] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0024] The existing electrolyte R&D system suffers from pain points throughout the entire R&D process due to rigid equipment architecture, inefficient process connections, and fragmented data management. Current R&D employs a decentralized, fixed equipment system lacking standardized, reconfigurable modular design. Different experimental equipment and processes must be built for different battery models such as button cells, cylindrical cells, and pouch cells, making it impossible to flexibly combine functional units according to R&D needs. This results in poor equipment adaptability to multiple battery models, low overall utilization, and significantly increased time and economic costs for process switchovers, making it difficult to meet the diverse R&D needs of next-generation battery technologies. Furthermore, the dispersed R&D processes and the complete reliance on manual operation for cell and material transfer between processes not only disrupt the continuous, high-throughput R&D process and reduce efficiency, but also easily introduce human error, leading to poor consistency and reproducibility of experimental results. Moreover, the lack of a global process coordination mechanism under the manual connection model easily results in chaotic process connections and mismatched cycle times, further reducing R&D focus, lengthening the R&D cycle, and increasing prototyping costs.

[0025] Furthermore, the existing R&D model suffers from a critical technical problem: the lack of a data management system. There is no unified mechanism for collecting and managing the process parameters, equipment status, and test results generated in each step, such as cell preparation, electrolyte formulation, electrolyte injection and packaging, and characterization testing. Data from different stages are isolated from each other, making it impossible to establish an effective mapping between electrolyte formulation, preparation process, and final battery performance test results. This makes it difficult to trace and locate R&D problems and optimize process solutions through data, and also fails to provide systematic data support for the iterative upgrade of electrolyte R&D. Consequently, it is difficult to form effective knowledge accumulation during the R&D process, which further restricts the improvement of R&D efficiency and the engineering implementation of R&D results.

[0026] To address the problems in the prior art, this application provides a battery electrolyte experimental research and development system, method, and equipment.

[0027] The battery electrolyte experimental research and development system provided in the embodiments of this application will be introduced first below.

[0028] Figure 1 A schematic diagram of the structure of a battery electrolyte experimental research and development system provided in one embodiment of this application is shown. Figure 1 As shown, the system may include the following structure: The scheduling device 101 is used to analyze the R&D requirements and battery model of the target battery, determine the selection and configuration scheme of the functional modules, and generate a matching R&D task sequence based on the selection and configuration scheme. The intelligent transfer robot 102 is used to automatically transfer battery cells, materials and experimental containers between various functional modules in the selected configuration scheme according to the R&D task sequence. The modular experimental device 103 includes multiple functional modules that can be selected and configured as needed. The modular experimental device is used to perform corresponding R&D procedures in dry cell preparation, electrolyte preparation and injection, and battery performance testing according to the R&D task sequence.

[0029] In this embodiment, the scheduling device 101, the intelligent transfer robot 102, and the modular experimental device 103 work together to achieve intelligent, modular, and flexible operation of the entire battery electrolyte experimental R&D process. It can adapt to the electrolyte R&D of various battery types, including button batteries, cylindrical batteries, and pouch batteries. Furthermore, it can flexibly configure the experimental process according to different R&D goals and battery types, improving the efficiency of electrolyte R&D and the traceability of experimental results. The scheduling device 101 can accurately analyze the R&D needs of the target battery, including different R&D directions such as electrolyte formulation development, battery performance verification, and process parameter optimization. It also identifies the process characteristics of target battery types such as button, cylindrical, and pouch batteries. Based on the functional module types of the modular experimental device 103, it determines a matching functional module selection and configuration scheme, avoiding resource waste caused by redundant module configurations. After completing the selection and configuration, the scheduling device 101 breaks down the overall R&D process into standardized and executable process nodes, generating an orderly R&D task sequence. It clarifies the execution timing and operational parameters of each functional module, as well as the transfer nodes and action instructions of the intelligent transfer robot 102, achieving refined arrangement of R&D tasks and ensuring smooth connection between each stage. In this embodiment, the intelligent transfer robot 102 can specifically be an embodied intelligent robot.

[0030] The intelligent transfer robot 102 possesses autonomous movement, precise positioning, and flexible grasping capabilities. Based on the R&D task sequence issued by the scheduling device 101, it can automatically transfer battery cells, experimental materials, and various experimental containers between the functional modules of the modular experimental device 103, effectively avoiding human error and safety risks, and achieving continuous sequencing of the R&D process. This intelligent transfer robot 102 can autonomously plan its transfer path according to the workstation layout of the functional modules, has obstacle avoidance capabilities, and can accurately complete the grasping, placement, and loading / unloading operations of materials, ensuring that the transfer actions match the working rhythm of each functional module, thereby improving the overall operational efficiency of the R&D process.

[0031] The modular experimental device 103 is the main experimental execution unit of this R&D system. It is a functional module system that can be selected and configured as needed. Each functional module can operate independently and can be flexibly combined according to the selection and configuration scheme determined by the scheduling device 101 to adapt to the process requirements of different battery models and R&D needs. This eliminates the need to build an independent experimental system for a single battery model, improving equipment utilization and reducing process switching costs. Based on the instructions of the R&D task sequence, the device drives the selected functional modules to collaboratively execute the corresponding R&D procedures, systematically completing core experimental steps such as dry cell preparation, electrolyte preparation and injection, and battery performance testing. Each functional module strictly follows preset process parameters during execution, ensuring the standardization and consistency of experimental operations and providing an experimental execution foundation for electrolyte R&D.

[0032] This application embodiment achieves integrated intelligent operation of the battery electrolyte R&D process through the overall planning of the scheduling device 101, the automated connection of the intelligent transfer robot 102, and the flexible execution of the modular experimental device 103. It solves the problems of poor adaptability, excessive manual intervention, and chaotic process connection in the traditional R&D system, and can significantly shorten the R&D cycle, reduce R&D costs, and improve the consistency and reproducibility of experimental results.

[0033] Furthermore, this application embodiment can include a raw material storage and pretreatment unit, comprising an automated warehouse / material workstation with environmental control. Water, oxygen, temperature, and humidity are managed through glove boxes / locally controlled spaces to ensure raw material stability. A barcode scanning module is also included to bind material batch numbers, container IDs (identifiers), and R&D task IDs, enabling traceable verification of materials. The corresponding intelligent transfer robot can be equipped with a visual recognition and identity verification module. This module uses a wrist camera to achieve precise workstation docking and material / cell posture correction, while a visual barcode reader verifies the identity of the transfer object. In addition, the scheduling device can support collaborative management of multiple robots, unifying path planning and scheduling operations to avoid conflicts and congestion.

[0034] In one feasible embodiment, in order to improve the adaptability of the R&D system to the R&D needs of different battery electrolytes and the standardization of process execution, the above-mentioned modular experimental device 103 may include at least one of the following: a dry cell preparation module, an electrolyte preparation and injection post-treatment module, and a battery performance testing module. The dry cell preparation module is used to perform the forming, stacking or winding of the positive and negative electrodes, complete the connection and welding of the tabs or current collectors, pre-package the cell structure, and dry or pre-treat the cell to obtain a dry cell. The electrolyte preparation, injection, and post-processing module is used to perform solid and liquid raw material feeding, electrolyte raw material mixing and homogenization to obtain electrolyte, injecting electrolyte into dry cell and performing vacuum or negative pressure wetting treatment, performing battery packaging and post-processing to obtain the battery to be tested. The battery performance testing module is used to perform one or more of the following tests on the battery under test: rate performance test, long cycle life test, internal resistance or impedance test, and high and low temperature test, to obtain the battery performance test results.

[0035] The functional modules configured in the modular experimental device 103 in this embodiment can be flexibly selected according to the R&D needs and battery model of the target battery, and include at least one of the following: dry cell preparation module, electrolyte preparation, injection and post-processing module, and battery performance testing module. Each module can independently complete the corresponding R&D process, or they can cooperate with each other to form a complete electrolyte R&D and battery trial production process, so as to achieve precise matching of R&D processes and efficient utilization of equipment resources.

[0036] The dry cell preparation module, serving as a core pre-production module for battery prototyping, standardizes the entire cell preparation process according to the structural characteristics of different battery models, yielding dry cells that meet the requirements of subsequent electrolyte injection and wetting processes. This provides structurally complete and performance-compliant dry cell substrates for subsequent electrolyte injection and battery packaging. The electrolyte preparation, injection, and post-processing module integrates the entire process from raw material formulation to cell injection and packaging post-processing, completing cell sealing and performance determination to obtain structurally complete test batteries ready for performance testing. The battery performance testing module can conduct multi-dimensional electrochemical performance tests on the packaged test batteries. The test items can provide direct experimental data support for electrolyte formulation optimization and preparation process adjustment based on R&D needs.

[0037] Furthermore, in this embodiment, a temperature-controlled heating unit can be added to the electrolyte preparation, injection, and post-processing module to achieve on-demand temperature adjustment to improve the dissolution and mixing effect of raw materials. Simultaneously, a corresponding parameter acquisition unit is configured to record the stirring speed, duration, and temperature curve in real time, and synchronize these data to the data management device after being bound to the electrolyte batch identifier. The electrolyte preparation, injection, and post-processing module can be equipped with a refined post-processing unit, which can perform operations such as needle puncture and gas bag cutting after vacuum sealing. The hot-pressing formation component supports independent setting and closed-loop control of multiple temperature and pressure segments. During the formation process, the current, voltage, temperature and pressure curves are collected and stored by binding them to the cell ID.

[0038] The battery performance testing module can be equipped with a constant temperature testing unit with a temperature range of 15-60℃, which can accurately adjust the test environment temperature. It also has a built-in safety protection unit that monitors voltage, current and temperature in real time. When overvoltage / overcurrent / overtemperature thresholds are triggered, it automatically performs pause / power-off protection and records the relevant events with the cell ID.

[0039] In one feasible embodiment, in order to improve the targeting of the R&D system for electrolyte R&D and enhance the reference value of experimental results, the modular experimental device 103 may further include an electrolyte characterization module. The electrolyte characterization module is used to perform one or more tests on the prepared electrolyte, including conductivity testing, viscosity testing, infrared spectroscopy testing, and Raman spectroscopy testing, to obtain the electrolyte property characterization results.

[0040] This system adds an electrolyte characterization module to the modular experimental device 103. As a key detection link between electrolyte preparation and cell injection, it can accurately test and analyze the physicochemical properties of the electrolyte after preparation and before injection into the dry cell. This effectively reduces the waste of resources caused by ineffective injection and subsequent testing, and improves the pertinence and efficiency of battery electrolyte experimental research and development.

[0041] The test items in the electrolyte characterization module can be flexibly selected according to R&D needs. Among them, the conductivity test is used to detect the ion conduction capacity of the electrolyte, which directly reflects the ion transport efficiency of the electrolyte inside the battery; the viscosity test is used to determine the viscosity of the electrolyte, and its value is closely related to the wetting ability and mass transfer rate of the electrolyte; the infrared spectroscopy test can accurately identify the types and distribution of functional groups in the electrolyte; the Raman spectroscopy test can obtain microscopic information such as the solvation structure and coordination structure of the electrolyte.

[0042] In the embodiments of this application, the electrolyte property characterization results can be correlated with electrolyte formulation, preparation process parameters, and subsequent battery performance test results, forming a complete data link from electrolyte performance to battery performance. This provides comprehensive experimental data support for subsequent formulation optimization, process improvement, and performance attribution analysis, and improves the completeness and traceability of R&D data.

[0043] In one feasible embodiment, to prevent invalid formulations from entering subsequent battery testing processes, reduce R&D material and time costs, and improve R&D efficiency, the aforementioned scheduling device 101 may include: The comparison module is used to receive the electrolyte property characterization results and compare the electrolyte property characterization results with the preset electrolyte property thresholds; The first execution module is used to trigger the battery performance testing module to perform performance testing on the battery under test when the electrolyte property characterization results meet the preset electrolyte property threshold. The second execution module is used to mark the corresponding electrolyte formula as to be reconstituted or eliminated and terminate the process if the electrolyte property characterization results do not meet the preset electrolyte property threshold.

[0044] In this embodiment, the scheduling device 101 adds a comparison module, a first execution module, and a second execution module, realizing intelligent judgment and dynamic scheduling of R&D processes based on electrolyte property characterization results. It links electrolyte performance test results with subsequent R&D process execution for control, enabling high-throughput pre-screening of electrolyte formulations before electrolyte is injected into the cell and battery preparation is completed. This effectively eliminates unqualified electrolyte formulations, reduces ineffective injection, packaging, and performance testing processes, reduces waste of R&D resources, and improves the efficiency and relevance of battery electrolyte experimental R&D.

[0045] The comparison module can receive the electrolyte property characterization results detected by the electrolyte characterization module in real time. The results include one or more test data such as conductivity, viscosity, infrared spectrum, and Raman spectrum. The comparison module has a built-in preset electrolyte property threshold that matches the R&D requirements and target battery model. The threshold can be flexibly adjusted according to different electrolyte R&D directions and battery performance requirements. The comparison module accurately compares the received electrolyte property characterization data with the corresponding preset electrolyte property threshold one by one, outputs the comparison results and synchronizes them to the first execution module and the second execution module, providing a basis for the execution and termination of subsequent processes.

[0046] In this embodiment, the scheduling device 101 has the ability to intelligently screen and dynamically control the electrolyte R&D process, realizing closed-loop screening and process control of electrolyte R&D. At the same time, it can synchronously store relevant comparison data, judgment results, and process execution / termination instructions to the system data management unit, and associate them with electrolyte formula, preparation process parameters, and characterization test results to form a complete R&D data traceability link, providing comprehensive data support for subsequent iterative optimization of electrolyte formula.

[0047] In one feasible embodiment, to ensure sufficient and consistent wetting of the electrolyte within the battery cell and improve the quality of battery cell fabrication, the aforementioned electrolyte preparation, injection, and post-processing module may include: The wetting state determination unit is used to monitor and record one or more monitoring data such as pressure change, processing time, and cell quality change in real time during vacuum or negative pressure wetting process, so as to determine the wetting state of electrolyte in dry cell based on the monitoring data. The re-wetting unit is used to perform vacuum or negative pressure wetting treatment again if the wetting state does not meet the preset standard state.

[0048] This application embodiment adds a wetting state determination unit and a re-wetting unit to realize real-time monitoring, state determination and closed-loop control of the electrolyte wetting process in the dry cell. This effectively ensures the sufficiency and uniformity of electrolyte wetting between the cell electrodes and separator, avoids problems such as subsequent electrochemical performance degradation and poor cycle stability caused by insufficient wetting, and improves the performance consistency of the prototype battery and the reliability of the test results.

[0049] In this embodiment, pressure change data reflects the stability of the vacuum environment during the impregnation process, processing time data controls the execution duration of the impregnation process, and cell quality change data directly reflects the degree of electrolyte adsorption and penetration inside the cell. Based on the deviations in the previously monitored impregnation data, this embodiment can adaptively adjust process parameters such as the vacuum level and processing time of the secondary impregnation, specifically addressing insufficient impregnation issues, until the impregnation state determination unit determines that the cell's impregnation state has reached the preset standard state. Then, the impregnation process is terminated and the process proceeds to the subsequent packaging stage. Furthermore, if the cell's impregnation state still fails to reach the preset standard state after multiple re-impregnations, the system can mark the cell and issue an anomaly warning, facilitating timely troubleshooting by R&D personnel regarding issues such as electrolyte injection volume, cell structure, and impregnation process parameters, preventing unqualified cells from entering subsequent processes and causing resource waste.

[0050] In this embodiment, the electrolyte wetting process replaces the traditional fixed-time operation with a dynamic adjustment operation based on the actual wetting state. This effectively overcomes the shortcomings of traditional processes that rely solely on fixed parameters and cannot adapt to the wetting requirements of different cell models and electrolyte formulations. It improves the adaptability and accuracy of the wetting process, ensuring consistency in wetting effects across different batches and cell models, and providing stable test batteries for subsequent battery performance testing. Furthermore, in this embodiment, all monitoring data, state determination results, and re-wetting operation records for the wetting process can be completely collected and stored, forming a complete data record of the wetting process. This provides detailed experimental data support for subsequent optimization of wetting process parameters and improvement of electrolyte formulations.

[0051] In one feasible embodiment, in order to achieve precise control of electrolyte raw material feeding and improve the accuracy and stability of electrolyte preparation, the above-mentioned electrolyte preparation injection and post-processing module may include: The weighing unit is used to obtain the actual feed amount of solid and liquid raw materials; The feed rate comparison unit is used to compare the actual feed rate with the preset feed rate. The correction unit is used to correct the feeding action based on the preset deviation value when the actual deviation value between the actual feed amount and the preset feed amount reaches the preset deviation value, so that the actual deviation value is less than the preset deviation value.

[0052] This application embodiment adds a weighing unit, a feed quantity comparison unit, and a correction unit to achieve accurate weighing, real-time comparison, and closed-loop correction during the electrolyte raw material feeding process. It strictly controls the ratio accuracy of the electrolyte formula from the raw material feeding stage, avoids electrolyte performance not meeting research and development requirements due to raw material feeding deviations, and improves the reliability and reproducibility of electrolyte research and development experimental results.

[0053] The weighing unit can accurately weigh the solid and liquid raw materials required for electrolyte preparation, precisely obtaining the actual feed amount of each type of raw material. The feed amount comparison unit works in conjunction with the weighing unit and has built-in preset feed amounts and preset deviation values ​​for each raw material that match the electrolyte R&D formula. These preset deviation values ​​can be flexibly adjusted according to the R&D accuracy requirements. After receiving the actual feed amount transmitted from the weighing unit, the feed amount comparison unit compares the actual feed amount of each raw material with the corresponding preset feed amount one by one, calculates the actual deviation value, and performs a threshold judgment between the actual deviation value and the preset deviation value. It then quickly outputs the comparison result. If the actual deviation value does not reach the preset deviation value, the feed amount is determined to meet the formula requirements, and the subsequent mixing and homogenization process continues. If the actual deviation value reaches or exceeds the preset deviation value, the deviation signal is immediately synchronized to the correction unit, providing accurate judgment and data support for correcting the feed action.

[0054] Based on the deviation signal and actual deviation value data transmitted by the feed quantity comparison unit, the correction unit automatically triggers the raw material feeding correction command. For different feeding methods of solid raw materials and liquid raw materials, the feeding action is precisely corrected. By adjusting parameters such as the feeding time, feeding rate, and feeding quantity compensation value of the feeding mechanism, the amount of raw material with deviation is supplemented or reduced until the actual deviation value between the actual feeding quantity collected by the weighing unit and the preset feeding quantity is less than the preset deviation value. Then the correction action is terminated and the feeding quantity is locked, and the subsequent electrolyte raw material mixing and homogenization process is started.

[0055] In one feasible embodiment, in order to achieve efficient advancement of R&D tasks according to process sequence, the scheduling device 101 may include: The task orchestration module is used to break down the R&D requirements of the target battery into cell preparation indicators, electrolyte performance indicators, and testing dimension indicators. It selects and combines suitable functional modules according to the battery model, and decomposes the R&D process into multiple process tasks according to the process sequence, as the R&D task sequence. The resource allocation module is used to allocate corresponding functional module resources, intelligent transfer robot 102 resources, and workstation resources to the R&D task sequence based on the operating status of each functional module and the working capacity of the intelligent transfer robot 102. The priority management module is used to set the execution priority of each R&D task in the R&D task sequence based on R&D needs or R&D timeliness requirements.

[0056] In this embodiment, the scheduling device 101, by setting up a task orchestration module, a resource allocation module, and a priority management module, realizes the refined breakdown of battery electrolyte R&D tasks, intelligent allocation of resources, and priority control of task execution. This makes the orchestration of the R&D process more in line with the target battery model and R&D needs, improves resource utilization efficiency, and can control the task execution rhythm according to the actual R&D needs, further improving the intelligent scheduling level and overall operating efficiency of the R&D system.

[0057] In this embodiment, the task orchestration module can first break down the R&D requirements of the target battery into cell preparation indicators, electrolyte performance indicators, and testing dimension indicators. Then, combined with the process characteristics of the battery model, it can screen and assemble suitable functional modules. Finally, according to the process sequence of electrolyte R&D, the overall R&D process is decomposed into multiple orderly process tasks to form a directly executable R&D task sequence, ensuring that the R&D tasks are highly matched with the process requirements.

[0058] Furthermore, in this embodiment, the resource allocation module accurately allocates corresponding functional module resources, intelligent transfer robot 102 resources, and workstation resources to each process task in the R&D task sequence based on the real-time operating status of each functional module and the operational capabilities of the intelligent transfer robot 102, thereby achieving reasonable scheduling and efficient utilization of each resource. The priority management module can flexibly set the execution priority of each R&D task in the R&D task sequence according to the importance of R&D needs or the timeliness requirements of R&D, allowing core R&D tasks and tasks with high timeliness requirements to be executed first, ensuring the efficient achievement of R&D goals.

[0059] In one feasible embodiment, in order to avoid R&D stagnation due to equipment or process abnormalities and to improve the anti-interference capability and continuous operation stability of the R&D process, the scheduling device 101 may also include an abnormality handling module. The exception handling module is used to monitor the operating status of each functional module, the operation status of the intelligent transfer robot 102, and the execution progress of the R&D process in real time. When a functional module failure, an abnormal operation of the intelligent transfer robot 102, or a deviation in the execution of the process is detected, the corresponding resources are reallocated to the R&D task sequence and the R&D task sequence is adjusted.

[0060] This embodiment adds an anomaly handling module to the scheduling device 101 to achieve real-time monitoring and dynamic anomaly control of the entire R&D process. When equipment or processes malfunction, it quickly reallocates resources and adjusts task sequences to prevent R&D process stalls, ensuring the continuity and stability of electrolyte experimental R&D, thereby improving the system's scheduling capabilities and anti-interference capabilities. Specifically, the anomaly handling module can monitor the real-time operating status of each functional module in the modular experimental device 103, the operational status of the intelligent transfer robot 102, and the actual execution progress of each R&D process, accurately capturing various anomalies such as functional module failures, robot operation abnormalities, and process execution deviations.

[0061] Furthermore, when the above-mentioned anomalies are detected, the anomaly handling module can be configured to immediately trigger the emergency dispatch mechanism. Based on the current availability of each resource, it can reallocate suitable functional modules, intelligent transfer robot 102, and workstation resources to the R&D task sequence. At the same time, it can flexibly adjust the process execution sequence and operation path of the R&D task sequence in combination with the anomaly type and R&D progress, so as to ensure that the R&D process can be quickly resumed after the anomaly is resolved, and minimize the impact of the anomaly on R&D efficiency.

[0062] In one feasible embodiment, in order to improve the automation and accuracy of material transfer between modules and reduce transfer errors, the intelligent transfer robot 102 may include: The positioning and navigation module is used to complete path planning and perform obstacle avoidance in real time as the intelligent transfer robot 102 moves; The mobile chassis drive module is used to drive the intelligent transfer robot 102 to move between various functional modules based on path planning; The gripping and handling execution module is used to grip, transfer, and place battery cells, materials, and experimental containers.

[0063] In this embodiment, the intelligent transfer robot 102 achieves autonomous movement, precise navigation, and stable transport of materials and battery cells by incorporating a positioning and navigation module, a mobile chassis drive module, and a grasping and handling execution module. The positioning and navigation module plans the path of the intelligent transfer robot 102 between the functional modules and monitors the surrounding environment in real time during robot movement to achieve precise obstacle avoidance, ensuring optimal transport paths and safety during movement. The mobile chassis drive module provides the robot with the power to move precisely between the functional modules based on the path planned by the positioning and navigation module. The grasping and handling execution module can stably grasp, precisely transport, and place battery cells, various experimental materials, and experimental containers at designated points, completing the transfer of materials and battery cells between the functional modules.

[0064] In one feasible embodiment, in order to achieve systematic recording of R&D data and traceability of the R&D process, the system may also include a data management device. The data management device is used to collect and store process data, system status data, and battery performance test results generated during system operation.

[0065] This application embodiment adds a data management device to achieve unified collection and structured storage of various types of data during system operation, improves the traceability system of R&D data, and enhances the reproducibility of R&D experimental results. Furthermore, the data management device can comprehensively collect various types of data generated during system operation, including process parameters of each functional module's execution steps, system status data of the scheduling device 101 and the intelligent transfer robot 102, and result data output by the battery performance testing module—all R&D data across the entire chain. Simultaneously, the data management device classifies, associates, and structures all collected data, binding data such as electrolyte formulations, preparation processes, cell preparation parameters, and performance test results. This achieves unified management and rapid retrieval of R&D data, forming a complete R&D data closed loop, facilitating subsequent data traceability, process analysis, and iterative optimization of R&D results.

[0066] In one feasible embodiment, to improve the validity and traceability of data, the data management device may include: The data acquisition module is used to collect in real time the operating parameters of each functional module, process execution data, equipment fault and abnormal information, and battery performance test results. The data alignment and traceability module is used to associate electrolyte formula information, process conditions of each R&D process, system status data, and battery performance test results data one by one, and establish an association mapping relationship identified by formula name and cell name. The data storage module is used to classify and store the association mapping relationships in a structured form, and to perform data deduplication and consistency verification.

[0067] In this embodiment, the data management device is functionally refined by setting up a data acquisition module, a data alignment and traceability module, and a data storage module. This enables accurate acquisition, correlation mapping, and standardized storage of data throughout the entire R&D process, constructing a traceable and structured R&D data system. This provides accurate and complete data support for process optimization and result analysis in electrolyte R&D.

[0068] Furthermore, the data acquisition module can collect operating parameters, process execution data, equipment fault and anomaly information, and various battery performance test results in real time for each functional module, achieving comprehensive data collection across the entire R&D process. The data alignment and traceability module links electrolyte formulation information, process conditions for each R&D step, system status data, and battery performance test results one-to-one, establishing a unique mapping relationship using formulation name and cell name as identifiers, enabling end-to-end data traceability from formulation to test results. The data storage module categorizes and stores the above mapping relationships in a structured format, while also performing deduplication and consistency checks on the data, facilitating rapid retrieval of R&D data.

[0069] In this embodiment, a data interaction and export unit can be added to the data management device. The unit is configured with a standardized MES acquisition interface to achieve data interoperability with external systems and support multi-dimensional querying and comparison of R&D data by formula ID, cell ID, batch number, etc., and can achieve structured summary export.

[0070] The battery electrolyte experimental R&D system provided in this application, through the coordinated operation of the modular experimental device 103, the intelligent transfer robot 102, and the scheduling device 101, achieves high efficiency, flexibility, and automation in battery electrolyte experimental R&D. Specifically, the scheduling device 101 analyzes the R&D requirements and battery model of the target battery to determine the functional module selection and configuration scheme and generate an R&D task sequence. This ensures that the selection of functional modules and the execution of the R&D process accurately match the actual R&D needs, avoiding redundant processes and wasting equipment resources, improving the R&D focus and equipment utilization rate. Simultaneously, the standardized R&D task sequence makes the R&D process more standardized, solving the problem of chaotic connections in traditional R&D processes. Modularization... The experimental device 103 is equipped with multiple selectable functional modules, which can be flexibly combined and matched according to different battery models and R&D needs. This breaks the limitation of fixed equipment on the R&D of multiple battery models, significantly improves the flexibility of the R&D system, and reduces process switching and system investment costs. The intelligent transfer robot 102 automatically transfers battery cells, materials and experimental containers between functional modules according to the R&D task sequence, replacing the traditional manual transfer method. This not only eliminates the errors introduced by manual operation and improves the consistency and reproducibility of experimental results, but also improves the automation level and operating efficiency of the R&D process, reduces the safety risks caused by human intervention, realizes the connection of R&D procedures, effectively shortens the electrolyte R&D cycle, and improves the overall R&D efficiency.

[0071] Furthermore, this application embodiment improves the adaptability of the R&D system to different battery electrolyte R&D needs and the standardization of process execution by clearly defining the functional modules of the modular experimental device 103 and the specific R&D procedures for each functional module; by adding an electrolyte characterization module and completing electrolyte property characterization before battery performance testing, pre-performance testing of the electrolyte is achieved; by comparing the characterization results with preset thresholds through the scheduling device 101, high-throughput pre-screening of electrolyte formulations is achieved, avoiding invalid formulations from entering subsequent battery testing procedures, reducing R&D material and time costs, and improving R&D efficiency; by monitoring and recording key data during the immersion treatment, the sufficiency and consistency of electrolyte immersion in the cell are ensured, improving the cell preparation quality; by monitoring the feed amount and correcting deviations through the weighing module, precise control of electrolyte raw material feed is achieved, improving the accuracy and stability of electrolyte preparation. The system achieves several key improvements: First, by prioritizing tasks and optimizing resource allocation, it ensures efficient progress of R&D tasks according to the process timeline. Second, by monitoring R&D status in real time and reallocating resources and adjusting task sequences in case of anomalies, it enhances the anti-interference capability and continuous operational stability of the R&D process. Third, by defining the core modules and transfer process of the intelligent transfer robot 102, it achieves precise path planning, obstacle avoidance, and material grasping and handling, improving the automation and accuracy of material transfer between modules and reducing transfer errors. Fourth, by adding a data management device and collecting and storing data from the entire R&D process, it achieves systematic recording of R&D data and traceability of the R&D process. Fifth, by defining the functional modules and data processing flow of the data management device, it achieves the correlation mapping, structured storage, and verification of R&D data, establishing a correspondence between electrolyte formulations, process conditions, and test results, thus improving the effectiveness and traceability of the data.

[0072] To make the embodiments of this application easier to understand, this application also provides a specific application scenario embodiment, which can be referred to. Figure 2 , Figure 2 This is a structural example diagram of a battery electrolyte experimental research and development system provided in an embodiment of this application. Specifically, it may include a scheduling device 101, an intelligent transfer robot 102, a modular experimental device 103, and a data management device 204. The scheduling device 101 includes a comparison module, a first execution module, a second execution module, a task orchestration module, a resource allocation module, a priority management module, and an exception handling module. The comparison module is used to receive the electrolyte property characterization results and compare the electrolyte property characterization results with the preset electrolyte property thresholds; The first execution module is used to trigger the battery performance testing module to perform performance testing on the battery under test when the electrolyte property characterization results meet the preset electrolyte property threshold. The second execution module is used to mark the corresponding electrolyte formula as to be compounded or eliminated and terminate the process if the electrolyte property characterization results do not meet the preset electrolyte property threshold. The task orchestration module is used to break down the R&D requirements of the target battery into cell preparation indicators, electrolyte performance indicators, and testing dimension indicators. It selects and combines suitable functional modules according to the battery model, and decomposes the R&D process into multiple process tasks according to the process sequence, as the R&D task sequence. The resource allocation module is used to allocate corresponding functional module resources, intelligent transfer robot resources, and workstation resources to the R&D task sequence based on the operating status of each functional module and the operational capabilities of the intelligent transfer robot. The priority management module is used to set the execution priority of each R&D task in the R&D task sequence based on R&D needs or R&D timeliness requirements. The exception handling module is used to monitor the operating status of each functional module, the operation status of the intelligent transfer robot, and the execution progress of the R&D process in real time. When a functional module failure, an abnormal operation of the intelligent transfer robot, or a deviation in the execution of the process is detected, the corresponding resources are reallocated to the R&D task sequence and the R&D task sequence is adjusted. The intelligent transfer robot 102 includes a positioning and navigation module, a mobile chassis drive module, and a grasping and handling execution module. The positioning and navigation module is used to complete path planning and perform obstacle avoidance in real time as the intelligent transfer robot moves; The mobile chassis drive module is used to drive the intelligent transfer robot to move between various functional modules based on path planning; The gripping and handling execution module is used to grip, transfer, and place battery cells, materials, and experimental containers; The modular experimental device 103 includes at least one of the following modules: a dry cell preparation module, an electrolyte preparation and post-injection treatment module, a battery performance testing module, and an electrolyte characterization module. The dry cell preparation module is used to perform the forming, stacking or winding of the positive and negative electrodes, complete the connection and welding of the tabs or current collectors, pre-package the cell structure, and dry or pre-treat the cell to obtain a dry cell. The electrolyte preparation, injection, and post-processing module includes a wetting state determination unit, a re-wetting unit, a weighing unit, a feed rate comparison unit, and a correction unit. The wetting state determination unit is used to monitor and record one or more monitoring data such as pressure change, processing time, and cell quality change in real time during vacuum or negative pressure wetting process, so as to determine the wetting state of electrolyte in dry cell based on the monitoring data. The re-wetting unit is used to perform vacuum or negative pressure wetting treatment again when the wetting state does not meet the preset standard state. The weighing unit is used to obtain the actual feed amount of solid and liquid raw materials; The feed rate comparison unit is used to compare the actual feed rate with the preset feed rate. The correction unit is used to correct the feeding action based on the preset deviation value when the actual deviation value between the actual feed amount and the preset feed amount reaches the preset deviation value, so that the actual deviation value is less than the preset deviation value. The battery performance testing module is used to perform one or more of the following tests on the battery under test: rate performance test, long cycle life test, internal resistance or impedance test, and high and low temperature test, to obtain the battery performance test results. The electrolyte characterization module is used to perform one or more tests on the prepared electrolyte, including conductivity testing, viscosity testing, infrared spectroscopy testing, and Raman spectroscopy testing, to obtain the electrolyte property characterization results. The data management device 204 includes a data acquisition module, a data alignment and traceability module, and a data storage module; The data acquisition module is used to collect in real time the operating parameters of each functional module, process execution data, equipment fault and abnormal information, and battery performance test results. The data alignment and traceability module is used to associate electrolyte formula information, process conditions of each R&D process, system status data, and battery performance test results data one by one, and establish an association mapping relationship identified by formula name and cell name. The data storage module is used to classify and store the association mapping relationships in a structured form, and to perform data deduplication and consistency verification.

[0073] Figure 3 This is a flowchart illustrating an experimental development method for battery electrolytes provided in an embodiment of this application. Figure 3 As shown, this method is applied to a battery electrolyte R&D system, which includes a modular experimental device, an intelligent transfer robot, and a scheduling device. The modular experimental setup includes multiple functional modules that can be selected and configured as needed; The method may include: S301: The scheduling device analyzes the R&D requirements and battery model of the target battery, determines the selection and configuration scheme of the functional modules, and generates a matching R&D task sequence based on the selection and configuration scheme. S302: Intelligent transfer robot automatically transfers battery cells, materials and experimental containers between various functional modules in the selected configuration scheme according to the R&D task sequence; S303: The modular experimental device executes the corresponding R&D procedures in dry cell preparation, electrolyte preparation and injection, and battery performance testing according to the R&D task sequence.

[0074] This application embodiment relies on the collaborative operation of a modular experimental device, an intelligent transfer robot, and a scheduling device to achieve modular configuration, automated connection, and standardized execution of the R&D process. This effectively improves R&D efficiency, reduces errors caused by human intervention, and ensures the consistency and reproducibility of experimental results. In this method, the scheduling device first accurately analyzes the R&D requirements and battery model characteristics of the target battery. Based on this, it selects suitable modules from multiple functional modules of the modular experimental device and determines the selection and configuration scheme. Then, according to the process sequence of electrolyte R&D, it breaks down the overall R&D process into an ordered sequence of R&D tasks, clarifying the execution requirements and transfer nodes of each module.

[0075] Then, after receiving the R&D task sequence issued by the scheduling device, the intelligent transfer robot autonomously moves between various functional modules, accurately realizes the automated grabbing, transfer and placement of battery cells, various experimental materials and experimental containers, replaces manual labor to complete the material transfer between processes, realizes the continuous connection of the R&D process, and ensures the smoothness of the connection between each process and the matching of the rhythm.

[0076] Finally, the modular experimental device, based on the instructions of the research and development task sequence, coordinates the selected functional modules to execute the corresponding research and development procedures, and completes the core research and development links such as dry cell preparation, electrolyte preparation and injection, and battery performance testing as needed. Each functional module operates independently and cooperates in an orderly manner, and can be flexibly combined according to research and development needs to adapt to the process requirements of different battery models and research and development goals, so as to achieve efficient completion of electrolyte experimental research and development.

[0077] This application embodiment achieves high efficiency, flexibility, and automation in battery electrolyte experimental research and development through the coordinated operation of modular experimental devices, intelligent transfer robots, and scheduling devices. Specifically, the scheduling device analyzes the research and development requirements and battery model of the target battery to determine the selection and configuration scheme of functional modules and generate a research and development task sequence. This ensures that the selection of functional modules and the execution of the research and development process accurately match actual research and development needs, avoiding redundant procedures and wasting equipment resources, improving the relevance of research and development and equipment utilization. Simultaneously, the standardized research and development task sequence makes the research and development process more standardized, solving the problem of chaotic connections in traditional research and development processes. The modular experimental device is configured with multiple modules that can be deployed as needed. The selected functional modules can be flexibly combined and matched according to different battery models and R&D needs, breaking the limitation of fixed equipment on the R&D of multiple battery models, significantly improving the flexibility of the R&D system, and reducing process switching and system investment costs. The intelligent transfer robot automatically transfers battery cells, materials and experimental containers between functional modules according to the R&D task sequence, replacing the traditional manual transfer method. This not only eliminates the errors introduced by manual operation and improves the consistency and reproducibility of experimental results, but also improves the automation and operating efficiency of the R&D process, reduces the safety risks caused by human intervention, realizes the connection of R&D procedures, effectively shortens the electrolyte R&D cycle, and improves the overall R&D efficiency.

[0078] Figure 4 This is a schematic diagram of the structure of a battery electrolyte experimental research and development device provided in an embodiment of this application.

[0079] The experimental research and development equipment for battery electrolytes may include a processor 401 and a memory 402 storing computer program instructions.

[0080] Specifically, the processor 401 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0081] Memory 402 may include mass storage for data or instructions. For example, and not limitingly, memory 402 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 402 may include removable or non-removable (or fixed) media, or memory 402 may be non-volatile solid-state storage. Memory 302 may be internal or external to the integrated gateway disaster recovery device.

[0082] Memory 402 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0083] The processor 401 reads and executes computer program instructions stored in the memory 402 to achieve... Figure 3 The experimental development method of the battery electrolyte in the illustrated embodiment.

[0084] In one example, the battery electrolyte experimental research and development equipment may also include a communication interface 403 and a bus 404. For example, Figure 4 As shown, the processor 401, memory 402, and communication interface 403 are connected through bus 404 and complete communication with each other.

[0085] The communication interface 403 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0086] Bus 404 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not as a limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 404 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0087] Furthermore, in conjunction with the battery electrolyte experimental development method in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the battery electrolyte experimental development methods in the above embodiments.

[0088] This application also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the battery electrolyte experimental development methods described in the above embodiments.

[0089] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0090] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0091] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0092] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0093] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A battery electrolyte experimental research and development system, characterized in that, include: The scheduling device is used to analyze the R&D requirements and battery model of the target battery, determine the selection and configuration scheme of the functional modules, and generate a matching R&D task sequence based on the selection and configuration scheme. Intelligent transfer robot, used to automatically transfer battery cells, materials and experimental containers between various functional modules in the selected configuration scheme according to the R&D task sequence; A modular experimental device, comprising multiple functional modules that can be selected and configured as needed, is used to perform corresponding R&D procedures in dry cell preparation, electrolyte preparation and injection, and battery performance testing according to the R&D task sequence.

2. The battery electrolyte experimental development system according to claim 1, characterized in that, The modular experimental device includes at least one of the following: a dry cell preparation module, an electrolyte preparation and post-injection treatment module, and a battery performance testing module; The dry cell preparation module is used to perform the forming, stacking or winding of the positive and negative electrodes, complete the connection and welding of the tabs or current collectors, pre-package the cell structure, and dry or pre-treat the cell to obtain a dry cell. The electrolyte preparation, injection, and post-processing module is used to perform solid and liquid raw material feeding, electrolyte raw material mixing and homogenization to obtain electrolyte, inject the electrolyte into the dry cell and perform vacuum or negative pressure wetting treatment, perform battery packaging and post-processing, and obtain the battery to be tested. The battery performance testing module is used to perform one or more of the following tests on the battery under test: rate performance test, long cycle life test, internal resistance or impedance test, and high and low temperature test, to obtain the battery performance test results.

3. The battery electrolyte experimental development system according to claim 2, characterized in that, The modular experimental apparatus also includes an electrolyte characterization module; The electrolyte characterization module is used to perform one or more tests on the prepared electrolyte, including conductivity testing, viscosity testing, infrared spectroscopy testing, and Raman spectroscopy testing, to obtain the electrolyte property characterization results.

4. The battery electrolyte experimental development system according to claim 3, characterized in that, The scheduling device includes: The comparison module is used to receive the electrolyte property characterization results and compare the electrolyte property characterization results with a preset electrolyte property threshold. The first execution module is used to trigger the battery performance testing module to perform performance testing on the battery under test when the electrolyte property characterization result meets the preset electrolyte property threshold. The second execution module is used to mark the corresponding electrolyte formula as to be reconstituted or eliminated and terminate the process when the electrolyte property characterization result does not meet the preset electrolyte property threshold.

5. The battery electrolyte experimental development system according to claim 2, characterized in that, The electrolyte preparation, injection, and post-processing module includes: The wetting state determination unit is used to monitor and record one or more monitoring data such as pressure change, processing time, and cell quality change in real time during vacuum or negative pressure wetting process, so as to determine the wetting state of electrolyte in dry cell based on the monitoring data. The re-wetting unit is used to perform vacuum or negative pressure wetting treatment again if the wetting state does not meet the preset standard state.

6. The battery electrolyte experimental development system according to claim 2, characterized in that, The electrolyte preparation, injection, and post-processing module includes: The weighing unit is used to obtain the actual feed amount of the solid raw material and the liquid raw material; The feed rate comparison unit is used to compare the actual feed rate with the preset feed rate. The correction unit is used to correct the feeding action based on the preset deviation value when the actual deviation value between the actual feed amount and the preset feed amount reaches the preset deviation value, so that the actual deviation value is less than the preset deviation value.

7. The battery electrolyte experimental development system according to claim 1, characterized in that, The scheduling device includes: The task orchestration module is used to break down the R&D requirements of the target battery into cell preparation indicators, electrolyte performance indicators, and testing dimension indicators. It selects and combines suitable functional modules according to the battery model and decomposes the R&D process into multiple process tasks according to the process sequence, which serve as the R&D task sequence. The resource allocation module is used to allocate corresponding functional module resources, intelligent transfer robot resources, and workstation resources to the R&D task sequence based on the operating status of each functional module and the operational capabilities of the intelligent transfer robot. The priority management module is used to set the execution priority of each R&D task in the R&D task sequence based on the R&D needs or R&D timeliness requirements.

8. The battery electrolyte experimental development system according to claim 7, characterized in that, The scheduling device also includes an exception handling module; The anomaly handling module is used to monitor the operating status of each functional module, the operation status of the intelligent transfer robot, and the execution progress of the R&D process in real time. When a functional module failure, an abnormal operation of the intelligent transfer robot, or a deviation in the execution of the process is detected, the corresponding resources are reallocated to the R&D task sequence, and the R&D task sequence is adjusted.

9. The battery electrolyte experimental development system according to claim 1, characterized in that, The intelligent transfer robot includes: The positioning and navigation module is used to complete path planning and perform obstacle avoidance in real time as the intelligent transfer robot moves; A mobile chassis drive module is used to drive the intelligent transfer robot to move between various functional modules based on the path planning. The grasping and handling execution module is used to grasp, transfer and place the battery cell, the material and the experimental container.

10. The battery electrolyte experimental development system according to claim 1, characterized in that, The system also includes a data management device; The data management device is used to collect and store process data, system status data, and battery performance test results generated during the operation of the system.

11. The battery electrolyte experimental development system according to claim 10, characterized in that, The data management device includes: The data acquisition module is used to collect in real time the operating parameters of each functional module, process execution data, equipment fault and abnormal information, and battery performance test results. The data alignment and traceability module is used to associate electrolyte formula information, process conditions of each R&D process, system status data, and battery performance test results data one by one, and establish an association mapping relationship identified by formula name and cell name. The data storage module is used to classify and store the association mapping relationship in a structured form, and to perform data deduplication and consistency verification.

12. A method for experimental development of battery electrolyte, characterized in that, The method is applied to a battery electrolyte research and development system, which includes a modular experimental device, an intelligent transfer robot, and a scheduling device. The modular experimental device includes multiple functional modules that can be selected and configured as needed; The method includes: The scheduling device analyzes the R&D requirements and battery model of the target battery, determines the selection and configuration scheme of functional modules, and generates a matching R&D task sequence based on the selection and configuration scheme. The intelligent transfer robot automatically transfers battery cells, materials, and experimental containers between various functional modules in the selected configuration scheme according to the R&D task sequence. The modular experimental device executes the corresponding R&D procedures in dry cell preparation, electrolyte preparation and injection, and battery performance testing according to the R&D task sequence.

13. A battery electrolyte experimental research and development device, characterized in that, The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the experimental development method for battery electrolyte as described in claim 12.

14. A computer storage medium, characterized in that, The computer storage medium stores computer program instructions, which, when executed by a processor, implement the experimental development method for battery electrolyte as described in claim 12.

15. A computer program product, characterized in that, Includes a computer program, which, when executed, implements the experimental development method for battery electrolyte as described in claim 12.

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