A method and system for monitoring and evaluating the electrical performance of a terminal block for a new energy vehicle

Abstract

The application provides a terminal table electrical performance monitoring and evaluation method and system for new energy vehicles, and relates to the technical field of performance evaluation. The method comprises the following steps: building a benchmark calibration library, determining a pre-control mode of an electrical performance inspection device, mapping and configuring the benchmark calibration library according to the pre-control mode, building an adaptive operation management model, reading a target calibration task, matching and determining an automatic operation management mechanism, then determining device operation data, obtaining monitoring data and evaluation data, and finally performing automatic operation control analysis and feedback management. The application mainly solves the problems of low efficiency and low precision of traditional detection methods, the inability to monitor the running status of the device in real time, the inability to quantitatively evaluate the performance of the terminal table, and the inability to timely feedback according to the device inspection. Through real-time monitoring of the electrical performance of the terminal table and evaluation of the stability and reliability of the performance, the safety and performance of new energy vehicles are effectively guaranteed.

Description

Technical Field

[0001] This application relates to the field of performance evaluation technology, specifically to a method and system for monitoring and evaluating the electrical performance of terminal blocks used in new energy vehicles. Background Technology

[0002] With increasing global emphasis on environmental protection and energy transition, new energy vehicles have become a crucial transportation option. Compared to traditional gasoline-powered vehicles, new energy vehicles offer advantages such as energy saving, emission reduction, and environmental friendliness, aligning with the requirements of sustainable development. However, the development of new energy vehicles has also brought about higher demands on the electrical performance of their key components. Terminal blocks, as vital connection components in the electrical systems of new energy vehicles, are responsible for the transmission of power and signals between key components such as batteries, motors, and controllers. Their electrical performance directly affects the operational efficiency and safety performance of new energy vehicles. Therefore, effective monitoring and evaluation of the electrical performance of terminal blocks used in new energy vehicles has become a critical requirement for the development of the new energy vehicle industry.

[0003] However, in the process of implementing the technical solution of the invention in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0004] Traditional testing methods are inefficient and inaccurate, unable to monitor equipment operation in real time, unable to quantitatively evaluate terminal block performance, and unable to provide timely feedback based on equipment inspection results. Summary of the Invention

[0005] This application mainly addresses the problems of traditional testing methods being inefficient and inaccurate, unable to monitor equipment operation in real time, unable to quantitatively evaluate the performance of terminal blocks, and unable to provide timely feedback based on equipment inspection results.

[0006] In view of the above problems, this application provides a method and system for monitoring and evaluating the electrical performance of terminal blocks for new energy vehicles. Firstly, this application provides a method for monitoring and evaluating the electrical performance of terminal blocks for new energy vehicles. The method includes: based on the terminal block specification type, performing analysis and classification based on verification index dimensions, and building a benchmark verification library, the benchmark verification library containing performance label maps; determining the pre-control mode of the electrical performance inspection equipment, including an automation mode and a human-machine interaction mode, the automation mode relying on a programmable logic controller (PLC); for the pre-control mode, performing mapping and configuration based on the benchmark verification library, building an adaptive operation and management model, the adaptive operation and management model establishing a channel connection with the PLC; reading the target verification task, transmitting it to the adaptive operation and management model, and matching and determining the automated operation and management mechanism; based on the PLC, executing operation and control management based on the automated operation and management mechanism in the electrical performance inspection equipment, determining equipment operation data, the equipment operation data including workstation monitoring data and performance evaluation data; and performing automated operation and control analysis and feedback management based on the equipment operation data.

[0007] Secondly, this application provides a monitoring and evaluation system for the electrical performance of terminal blocks used in new energy vehicles. The system includes: a benchmark verification library construction module, which analyzes and assigns benchmark verification libraries based on terminal block specifications and verification index dimensions, and stores performance label maps; a pre-control mode determination module, which determines the pre-control mode of the electrical performance testing equipment, including an automation mode and a human-machine interaction mode, wherein the automation mode relies on a programmable logic controller (PLC); and an adaptive operation and management model construction module, which maps and assigns the pre-control mode based on the benchmark verification library. The system includes: an adaptive operation and management model (O&M) established with a channel connection to the programmable controller (PLC); an O&M mechanism matching module for reading target verification tasks, transmitting them to the adaptive O&M model, and matching and determining an automated O&M mechanism; an equipment operation data determination module for performing O&M management based on the PLC within the electrical performance inspection equipment, and determining equipment operation data, including workstation monitoring data and performance evaluation data; and an automated O&M and feedback module for performing automated O&M analysis and feedback management based on the equipment operation data.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] This application provides a method and system for monitoring and evaluating the electrical performance of terminal blocks used in new energy vehicles, relating to the field of performance evaluation technology. The method includes: building a benchmark verification library, determining the pre-control mode of the electrical performance inspection equipment, mapping and configuring the benchmark verification library for the pre-control mode, building an adaptive operation and management model, reading the target verification task, matching and determining the automated operation and management mechanism, then determining the equipment operation data, acquiring monitoring data and evaluation data, and finally performing automated operation and control analysis and feedback management.

[0010] This application primarily addresses the shortcomings of traditional testing methods, such as low efficiency and accuracy, inability to monitor equipment operation in real time, inability to quantitatively evaluate terminal block performance, and inability to provide timely feedback based on equipment inspection findings. By enabling real-time monitoring of the electrical performance of terminal blocks and evaluating their stability and reliability, it provides strong assurance for the safety and performance of new energy vehicles.

[0011] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0013] Figure 1 This application provides a schematic flowchart of a method for monitoring and evaluating the electrical performance of terminal blocks used in new energy vehicles.

[0014] Figure 2 This application provides a method for monitoring and evaluating the electrical performance of terminal blocks used in new energy vehicles, which includes a flowchart illustrating the method for mapping and generating the automated operation and management mechanism.

[0015] Figure 3 This application provides a method flowchart for generating performance evaluation data in a method for monitoring and evaluating the electrical performance of terminal blocks for new energy vehicles.

[0016] Figure 4 This application provides a schematic diagram of the structure of a monitoring and evaluation system for the electrical performance of terminal blocks used in new energy vehicles.

[0017] Explanation of reference numerals in the attached diagram: 10, Module for building the benchmark verification library; 20, Module for determining the pre-control mode; 30, Module for building the adaptive operation and management model; 40, Module for matching the operation and management mechanism; 50, Module for determining equipment operation data; 60, Module for automated operation control and feedback. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] This application primarily addresses the shortcomings of traditional testing methods, such as low efficiency and accuracy, inability to monitor equipment operation in real time, inability to quantitatively evaluate terminal block performance, and inability to provide timely feedback based on equipment inspection findings. By enabling real-time monitoring of the electrical performance of terminal blocks and evaluating their stability and reliability, it provides strong assurance for the safety and performance of new energy vehicles.

[0020] To better understand the above technical solution, the following will provide a detailed description of the solution in conjunction with the accompanying drawings and specific implementation methods:

[0021] Example 1

[0022] like Figure 1 The present invention discloses a method for monitoring and evaluating the electrical performance of terminal blocks used in new energy vehicles. The method is applied to a monitoring and evaluation system for the electrical performance of terminal blocks used in new energy vehicles, the system being communicatively connected to electrical performance testing equipment. The method includes:

[0023] Based on the terminal block specifications and types, an analysis and classification based on the verification index dimensions are conducted to build a benchmark verification library, which contains performance label charts.

[0024] Specifically, based on the terminal block specifications, an analysis and classification based on verification index dimensions is conducted to establish a benchmark verification library. This library contains performance label maps. First, the specifications of the terminal blocks need to be determined, including their size, shape, material, and color. Then, analysis and classification based on verification index dimensions are performed. According to the terminal block specifications, the required testing index dimensions can be determined, such as conductivity, insulation, withstand voltage, and environmental adaptability. By testing and analyzing these indicators, the performance and quality of the terminal blocks can be evaluated. A benchmark verification library is established based on the analysis and classification results to store and manage all terminal block samples requiring testing. This library can be classified and stored according to different specifications, index dimensions, and performance levels. Finally, a performance label map is established based on the benchmark verification library to label and evaluate the performance of each terminal block. This map can include information from multiple dimensions, such as model, specifications, index parameters, and quality level, to facilitate subsequent querying and analysis. Through the above steps, a benchmark verification library can be established based on the dimension analysis of verification indicators according to the terminal block specification type, and equipped with a performance label map, thereby realizing the effective monitoring and evaluation of the electrical performance of terminal blocks used in new energy vehicles.

[0025] The pre-control mode of the electrical performance testing equipment is determined, including an automation mode and a human-machine interaction mode, wherein the automation mode is based on a programmable controller;

[0026] Specifically, the pre-control mode of the electrical performance testing equipment is determined, including an automated mode and a human-machine interaction mode. The automated mode relies on a programmable logic controller (PLC). Control requirements are determined as follows: First, the control requirements of the electrical performance testing equipment need to be clearly defined, including the testing process, safety protection, and fault handling. A control mode is selected: Based on the control requirements, either an automated mode or a human-machine interaction mode can be selected as the pre-control mode. The automated mode mainly relies on the PLC to achieve automated control and testing. A control program is designed: Based on the control requirements and the selected control mode, a control program can be designed to achieve automated control of the equipment. The control program can be written using the PLC's programming language, including the implementation of functions such as the testing process, safety protection, and fault handling. Human-machine interaction is implemented: In the human-machine interaction mode, interactive operation between humans and the equipment needs to be implemented. This can be achieved through devices such as operation panels and touch screens, allowing operators to manually control and adjust the equipment. Through the above steps, the pre-control mode of the electrical performance testing equipment, including an automated mode and a human-machine interaction mode, can be determined. The automated mode relies on a PLC to achieve effective control and testing of the equipment. This will help improve the testing efficiency and accuracy of the electrical performance of terminal blocks used in new energy vehicles, providing strong protection for the safety and performance of new energy vehicles.

[0027] For the pre-control mode, mapping and configuration based on the benchmark verification library are performed to build an adaptive operation and management model, and the adaptive operation and management model establishes a channel connection with the programmable controller;

[0028] Specifically, for the pre-control mode, mapping and configuration based on the benchmark verification library can be performed to build an adaptive operation and management model. This adaptive operation and management model establishes a channel connection with the programmable controller (PLC). Establishing a mapping relationship: The information in the benchmark verification library is mapped and associated with the pre-control mode. Specifically, based on the performance label map of each terminal block, it can be matched and associated with the corresponding control program and detection process. Configuring the operation and management model: Based on the mapping relationship, an adaptive operation and management model can be built to achieve automated control and detection of terminal blocks with different performance labels. The adaptive operation and management model can automatically adjust the control program and detection process according to different performance labels to achieve precise control and detection of different terminal blocks. Establishing a channel connection: A channel connection is established between the adaptive operation and management model and the PLC to achieve information exchange and interaction. Through the channel connection, the adaptive operation and management model can receive control signals from the PLC, process and execute them. Through the above steps, mapping and configuration based on the benchmark verification library can be performed for the pre-control mode to build an adaptive operation and management model, and a channel connection can be established with the PLC to achieve information exchange and interaction. This will help improve the testing efficiency and accuracy of the electrical performance of terminal blocks used in new energy vehicles, providing strong protection for the safety and performance of new energy vehicles.

[0029] The target verification task is read and transmitted to the adaptive operation and management model to match and determine the automated operation and management mechanism;

[0030] Specifically, the process involves: reading the target verification task, transmitting it to the adaptive operation and management model, matching and determining the automated operation and management mechanism, and then: Reading the target verification task: Information about the target verification task, including the performance indicators of the terminal blocks to be tested, the testing process, and safety protection requirements, is read from the relevant systems or equipment. Transmission to the adaptive operation and management model: The information of the target verification task is transmitted to the adaptive operation and management model. This model can identify and parse the task information and perform corresponding matching and configuration according to the task requirements. Matching and determining the automated operation and management mechanism: Based on the information of the target verification task and combined with data and knowledge in the benchmark verification library, the adaptive operation and management model matches and determines the corresponding automated operation and management mechanism. This mechanism may include the selection of control programs, the execution of testing processes, and the activation of safety protection measures. Execution of automated operation and management: After determining the automated operation and management mechanism, the adaptive operation and management model can automatically execute the corresponding control programs and testing processes. Through these steps, the target verification task can be read, transmitted to the adaptive operation and management model, and the automated operation and management mechanism matched and determined, thereby efficiently completing the testing and evaluation of the electrical performance of terminal blocks for new energy vehicles.

[0031] Based on the programmable controller, operation and control management based on the automated operation and management mechanism is performed in the electrical performance inspection equipment to determine the equipment operation data, which includes workstation monitoring data and performance evaluation data.

[0032] Specifically, based on programmable logic controllers (PLCs), automated operation and control management is implemented in electrical performance testing equipment to determine equipment operation data, including workstation monitoring data and performance evaluation data. Automated operation and control management: According to the automated operation and control mechanism, corresponding control programs and testing processes are executed based on the PLC. Through precise control and monitoring of the equipment by the PLC, automated operation and control management of the electrical performance testing equipment is achieved. Determining equipment operation data: During automated operation and control management, equipment operation data can be acquired and determined in real time. This data includes workstation monitoring data and performance evaluation data. Workstation monitoring data reflects the equipment's operating status and the testing progress of each workstation; performance evaluation data reflects the electrical performance indicators and quality evaluation results of the terminal blocks. Workstation monitoring data: Through the PLC, real-time monitoring of each workstation can be achieved. Monitoring data includes the operating status, testing progress, and abnormal situations of each workstation. This data can be used to monitor the equipment's operating status in real time and promptly detect and handle abnormal situations. Performance evaluation data: During the automated operation and control management process, the electrical performance of the terminal blocks is tested and evaluated. Performance evaluation data includes the electrical performance indicators and quality assessment results of the terminal blocks. This data can be used to quantitatively evaluate the performance of the terminal blocks, providing a basis for subsequent quality control and decision-making. Through the above steps, automated operation and control management of electrical performance inspection equipment based on programmable logic controllers (PLCs) can be achieved, and equipment operation data, including workstation monitoring data and performance evaluation data, can be determined. This data can be used to monitor the equipment's operating status in real time, quantitatively evaluate the performance of the terminal blocks, and provide strong support for subsequent quality control and decision-making.

[0033] Based on the equipment operation data, automated operation control analysis and feedback management are performed.

[0034] Specifically, based on equipment operation data, automated operation control analysis and feedback management can be performed. Data processing and analysis involves processing and analyzing the acquired equipment operation data. This includes cleaning, organizing, and converting workstation monitoring data and performance evaluation data. Automated operation control analysis is also possible based on this data. For example, by analyzing workstation monitoring data, equipment operating efficiency can be assessed, and potential faults or anomalies can be predicted. By analyzing performance evaluation data, the electrical performance of terminal blocks can be quantitatively evaluated, providing a basis for quality control and decision-making. Feedback management is also possible based on the results of automated operation control analysis and model building. Adjustments and optimizations can be made to the equipment's operating status, testing procedures, and the electrical performance of terminal blocks based on the analysis results and model predictions. For example, if a workstation's testing efficiency is found to be low, the control program or testing process of that workstation can be adjusted to improve its efficiency. Real-time monitoring and adjustment are also crucial, requiring real-time monitoring of the equipment's operating status and the electrical performance indicators of the terminal blocks during feedback management. By monitoring and analyzing real-time data, anomalies can be detected and addressed promptly, ensuring stable equipment operation and accurate test data. These steps enable automated operation control analysis and feedback management based on equipment operation data, further improving the testing efficiency and accuracy of electrical performance of terminal blocks used in new energy vehicles, and providing strong support for the safety and performance of new energy vehicles.

[0035] Furthermore, the method of this application performs analysis and attribution based on the dimension of the verification index, and the method includes:

[0036] Terminal blocks are categorized and integrated to determine multiple terminal block categories, including standard terminal blocks, RF coaxial terminal blocks, and high-speed signal terminal blocks, and these categories are updatable.

[0037] For the multiple terminal block categories, extract and identify the main performance indicators based on the standard terminal block, and construct a main tag map, wherein the main performance indicators include contact resistance, insulation resistance and dielectric strength;

[0038] Extract and identify electrical performance indicators based on the RF coaxial terminal block, and construct a tag map;

[0039] Extract and identify electrical performance indicators based on the high-speed signal terminal block, and construct a binary tag map;

[0040] The main label graph, the first-term label graph, and the second-term label graph are mapped and associated, and common-inference resolution is performed to generate a performance label graph.

[0041] Specifically, terminal blocks are categorized and integrated to identify multiple categories, including standard terminal blocks, RF coaxial terminal blocks, and high-speed signal terminal blocks, with updatable features. For these categories of terminal blocks, electrical performance indicators can be extracted and identified according to the following steps to construct corresponding tag maps, and coreference resolution can be performed to generate performance tag maps. Extraction and identification of main performance indicators for standard terminal blocks: Main performance indicators for standard terminal blocks may include contact resistance, insulation resistance, and dielectric strength. These indicators are the main factors for evaluating the electrical performance of standard terminal blocks and can be extracted and identified using appropriate testing equipment and methods. Construction of main tag maps: Based on the extracted main performance indicators of standard terminal blocks, main tag maps can be constructed. The main tag map is a tag map based on main performance indicators, used to identify and evaluate the electrical performance of standard terminal blocks. Extraction and identification of electrical performance indicators for RF coaxial terminal blocks: Electrical performance indicators for RF coaxial terminal blocks may include impedance, frequency response, and insertion loss. These indicators can be extracted and identified using appropriate testing equipment and methods. Constructing a Label Map: Based on the extracted electrical performance indicators of RF coaxial terminal blocks, a label map can be constructed. A label map is a map with the electrical performance indicators of RF coaxial terminal blocks as its dimension, used to identify and evaluate the electrical performance of RF coaxial terminal blocks. Extracting and Identifying Electrical Performance Indicators of High-Speed ​​Signal Terminal Blocks: The electrical performance indicators of high-speed signal terminal blocks can include signal transmission rate, signal quality, timing accuracy, etc. These indicators can be extracted and identified using appropriate testing equipment and methods. Constructing a Two-Item Label Map: Based on the extracted electrical performance indicators of high-speed signal terminal blocks, a two-item label map can be constructed. A two-item label map is a map with the electrical performance indicators of high-speed signal terminal blocks as its dimension, used to identify and evaluate the electrical performance of high-speed signal terminal blocks. Mapping and Associating the Main Label Map, One-Item Label Map, and Two-Item Label Maps: By mapping and associating the main label map, one-item label map, and two-item label maps, the electrical performance indicators of terminal blocks of different categories can be linked to form a holistic performance label map. Coreference resolution: During the mapping and association process, the same electrical performance indicator may be mentioned multiple times or named differently but represent the same meaning. To eliminate the impact of this coreference phenomenon on the performance label map, coreference resolution is required. Through coreference resolution, identical or similar electrical performance indicators can be grouped into the same category, ensuring the consistency and accuracy of the performance label map. Performance label map generation: After mapping and association and coreference resolution, a final performance label map is generated. This map integrates the electrical performance indicators of standard terminal blocks, RF coaxial terminal blocks, and high-speed signal terminal blocks, and is used to comprehensively evaluate the electrical performance of terminal blocks used in new energy vehicles. Through the above steps, terminal blocks can be classified and integrated, multiple terminal block categories can be identified, and corresponding electrical performance indicators can be extracted and identified for each category.By constructing a main label map, a single-label map, a double-label map, and performing coreference resolution, a comprehensive performance label map is finally generated for a comprehensive evaluation of the electrical performance of terminal blocks used in new energy vehicles.

[0042] Furthermore, such as Figure 2 As shown, the method of this application matches and determines the automated operation and management mechanism. The method includes:

[0043] Identify the target verification task, determine the target type, traverse the performance label map in the benchmark verification library, and determine the target verification label;

[0044] Based on the target verification label, adaptive debugging is performed according to the pre-control mode to determine the periodic operation and control mechanism;

[0045] A regulatory mechanism based on the aforementioned cycle operation control mechanism is determined, and the automated operation management mechanism is generated by mapping it.

[0046] Specifically, the process involves: Identifying the target verification task: Parsing and identifying the received target verification task to extract key information, such as the performance indicators of the terminal block to be tested, the testing process, and safety protection requirements. Determining the target type: Based on the key information of the target verification task, determining the target type. For example, the target type could be a standard terminal block, an RF coaxial terminal block, or a high-speed signal terminal block. Traversing the performance tag map in the benchmark verification library: Based on the target type, traversing the corresponding performance tag map in the benchmark verification library. This map contains information such as the electrical performance indicators of that type of terminal block and its corresponding testing process and parameters. Determining the target verification label: From the traversed performance tag map, determining the target verification label based on task requirements and testing standards. This label will serve as the basis for subsequent automated operation and management. Adaptive debugging based on the pre-control mode: Combining the target verification label, adaptive debugging is performed based on the pre-control mode. This process may require adjustments and optimizations to the control program and testing process to ensure the efficiency and accuracy of automated operation and management. Determining the periodic operation and control mechanism: Based on the debugging results, determining the periodic operation and control mechanism based on the pre-control mode. This mechanism will determine details such as the cycle and execution time of automated operation and management. It will then establish a regulatory mechanism based on the cycle control mechanism: to ensure the normal operation and accuracy of automated operation and management, a regulatory mechanism based on the cycle control mechanism needs to be established. This mechanism will monitor the execution of automated operation and management and make adjustments and optimizations as needed. Finally, the established cycle control mechanism and regulatory mechanism will be mapped into the automated operation and management model to generate the corresponding automated operation and management mechanism. This mechanism will automatically execute the electrical performance testing and quality control tasks of the terminal blocks according to the preset cycle and regulatory strategy. Through these steps, the entire process from identifying the target verification task to generating the automated operation and management mechanism can be realized. The generated automated operation and management mechanism will automatically execute the electrical performance testing and quality control tasks of the terminal blocks according to the preset cycle and regulatory strategy, thereby improving testing efficiency and accuracy, and providing strong protection for the safety and performance of new energy vehicles.

[0047] Furthermore, the method of this application determines a regulatory mechanism based on the said periodic operation control mechanism and maps it to generate the said automated operation management mechanism. This method includes:

[0048] Identify multiple workstation nodes based on the aforementioned automated operation and management mechanism;

[0049] Based on the multiple workstation nodes, determine the node tolerance range for constraining the dynamic operation control deviation.

[0050] Map the node tolerance range with the periodic operation control mechanism to generate the automated operation management mechanism;

[0051] If the node's tolerance range is not met, a dynamic warning instruction is generated.

[0052] Specifically, the process involves: 1) Identifying multiple workstation nodes based on the automated operation and management mechanism: Based on the requirements of the automated operation and management mechanism and the equipment layout, identify multiple workstation nodes that need to be monitored and controlled. These nodes can be different parts of the equipment or different stages of the testing process. 2) Determining node tolerance ranges for dynamic operation and control deviations based on multiple workstation nodes: Based on the characteristics and operational requirements of each workstation node, determine the node tolerance ranges for dynamic operation and control deviations. This range is typically determined based on factors such as equipment performance indicators, testing accuracy requirements, and safety protection standards. 3) Mapping node tolerance ranges to the periodic operation and control mechanism: Map the determined node tolerance ranges to the periodic operation and control mechanism to ensure that the automated operation and management mechanism can monitor and control the dynamic operation and control deviations of each workstation node in real time during execution, keeping them within the set node tolerance ranges. 4) Generating the automated operation and management mechanism: Develop the operating rules and control strategies for multiple workstation nodes based on the automated operation and management mechanism. This mechanism includes the constraints of the periodic operation and control mechanism and the node tolerance ranges, used to optimize and control the automated operation and management process. Dynamic alarm command generation: During operation, if the dynamic control deviation of a certain workstation node exceeds the set node tolerance range, a corresponding dynamic alarm command is generated. This command can be used to remind operators to pay attention to abnormal situations and make corresponding adjustments and repairs, ensuring the normal operation of the equipment and the smooth progress of automated operation and management. Through the above steps, the operation monitoring and control of multiple workstation nodes based on the automated operation and management mechanism can be realized, and corresponding dynamic alarm commands can be generated according to the dynamic control deviation of the nodes. This mechanism helps to improve the efficiency and accuracy of automated operation and management, ensuring the accurate completion of electrical performance testing and quality control tasks for terminal blocks used in new energy vehicles.

[0053] Furthermore, such as Figure 3 As shown, the method of this application obtains performance evaluation data, and the method includes:

[0054] Configure performance verification requirements, wherein the performance verification requirements are mapped to each performance label;

[0055] As the automated operation and management mechanism operates, a step-by-step judgment based on the performance verification requirements is performed simultaneously.

[0056] If the workstation's verification results do not meet the mapped performance verification requirements, perform quality anomaly visualization and generate a non-conforming identifier;

[0057] The performance evaluation data is generated by integrating the verification data throughout its entire lifecycle.

[0058] Specifically, the system includes the following steps: **Configure Performance Verification Requirements:** Based on the performance indicators and testing standards of terminal blocks for new energy vehicles, configure corresponding performance verification requirements. These requirements should be mapped to specific performance labels to ensure the accuracy and reliability of the verification results. **Simultaneous Step-by-Step Judgment Based on Performance Verification Requirements:** During the operation and control management process of the automated operation and management mechanism, a step-by-step judgment based on performance verification requirements is performed simultaneously. This judgment process compares and analyzes the verification results of the current workstation node with the mapped performance verification requirements to determine whether the requirements are met. **Quality Anomaly Visualization and Non-Compliance Identification:** If the verification results of a workstation node do not meet the mapped performance verification requirements, quality anomalies are visualized using specific charts or indicators to identify the anomalies. Simultaneously, a non-compliance identification is generated to mark the non-compliance status of the workstation node for subsequent processing and improvement. **Full-Cycle Integration of Verification Data:** Full-cycle integration of verification data from all workstation nodes is performed, including qualified test data and abnormal data that do not meet performance verification requirements. This data will be used to generate performance evaluation data to assess the electrical performance indicators of the terminal blocks and the efficiency and accuracy of the testing process. Performance evaluation data generation: By integrating calibration data throughout its entire lifecycle, performance evaluation data is generated. This data reflects whether the electrical performance indicators of the terminal blocks meet the requirements, as well as the efficiency and accuracy of the testing process. This data can be used to improve production processes, optimize quality control, and evaluate equipment performance. Through these steps, operation monitoring and control of multiple workstation nodes based on an automated operation and management mechanism can be achieved, and corresponding dynamic alarm commands can be generated based on the dynamic operation and control deviation of the nodes. Simultaneously, by integrating calibration data throughout its entire lifecycle and generating performance evaluation data, a better understanding of the electrical performance indicators of the terminal blocks and the actual situation of the testing process can be achieved, providing strong support for subsequent quality control and improvement.

[0059] Furthermore, in the method of this application, after obtaining the performance evaluation data, the method includes:

[0060] The monitoring and testing environment, combined with the limitations of equipment technology, is used to determine the assessment influencing factors, which are identified by characteristic values.

[0061] A comprehensive evaluation of the aforementioned influencing factors was conducted to determine the deviation coefficient.

[0062] Determine whether the deviation coefficient meets the threshold standard; if not, generate a result compensation instruction.

[0063] Based on the result compensation instruction, compensation data based on the deviation coefficient is determined, and the performance evaluation data is compensated and calibrated.

[0064] Specifically, the process involves monitoring the calibration environment and considering equipment limitations to determine evaluation influencing factors. These factors, such as ambient temperature, humidity, equipment wear, and tool precision, can be identified through real-time monitoring and analysis of the environment. They directly or indirectly affect the calibration results. Characteristic values ​​are also crucial: each influencing factor should possess corresponding characteristic values ​​that describe and quantify its impact. For example, the range of ambient temperature variation can be a characteristic value, and equipment wear can be described by specific parameters or indicators. A comprehensive evaluation of these factors is then conducted to determine deviation coefficients. This may involve weighting, correlation, or regression analyses of each factor to determine its deviation coefficient from the calibration results. Finally, a threshold standard is set to determine if the deviation coefficient meets the required criteria. If the deviation coefficient exceeds the threshold, it indicates a potential significant error or inaccuracy in the calibration results. Finally, a result compensation instruction is generated if the deviation coefficient does not meet the threshold standard. This instruction indicates the need for compensation calibration of performance evaluation data to correct errors caused by environmental changes or equipment limitations. Based on the result compensation instruction, compensation data based on the deviation coefficient is determined: According to the generated result compensation instruction and the value of the deviation coefficient, the corresponding compensation data can be determined. This data will be used to compensate and calibrate the performance evaluation results to ensure the accuracy and reliability of the evaluation results. Compensation and calibration of performance evaluation data: Based on the determined compensation data, the performance evaluation results are compensated and calibrated. This may involve operations such as data correction, interpolation, or recalculation to ensure that the performance evaluation results more accurately reflect the actual electrical performance of the terminal block. Through the above steps, the evaluation influencing factors can be determined by monitoring the verification environment and considering equipment limitations. By comprehensively evaluating these influencing factors and determining the deviation coefficient, corresponding result compensation instructions are generated. Based on these instructions, compensation data based on the deviation coefficient can be determined, and the performance evaluation results can be compensated and calibrated. This effectively improves the accuracy and reliability of the performance evaluation results, providing strong support for subsequent quality control and improvement.

[0065] Furthermore, the method of this application performs automated operation control analysis and feedback management, and the method includes:

[0066] Identify the equipment operation data, perform automated early warning management of the equipment operation status, and generate fault files;

[0067] Perform memory storage and deletion management on the faulty files;

[0068] The system identifies the equipment's operational data and, if it is in an automation over-limit state, generates a human-machine interaction command.

[0069] Upon receiving human-computer interaction commands, the human-computer interaction mode is activated, allowing personnel to manually manage the process through a visual interface.

[0070] Specifically, the system identifies equipment operation data, performs automated early warning management of equipment operation status, and generates fault files: Through corresponding sensors and monitoring systems, it monitors equipment operation data in real time, including parameters such as speed, temperature, and pressure. When these data are abnormal, the system automatically issues an early warning and records the relevant fault information in the fault file. The system manages the storage and deletion of fault files: It automatically saves the generated fault files and manages their storage according to set storage rules. Simultaneously, to ensure efficient use of storage space, the system also deletes old and no longer needed fault files according to set deletion rules. The system identifies equipment operation data and generates human-machine interaction commands if the equipment is in an automated over-limit state: During equipment operation, the system continuously monitors the equipment's operation data. Once the data exceeds the set automated control range, the system automatically generates a human-machine interaction command. Upon receiving the human-machine interaction command, the system activates the human-machine interaction mode, allowing manual management through a visual interface: When the human-machine interaction command is sent to the system, the system automatically activates the human-machine interaction mode, displaying the relevant equipment operation data and fault information on a visual interface. Operators can then perform manual management through the interface, such as adjusting equipment parameters, pausing or stopping the equipment, etc. Through the above steps, automated early warning management of equipment operating status can be achieved, and manual operation can be initiated in human-machine interaction mode as needed. This mechanism helps to promptly detect and handle equipment faults, reduce the risk of accidents, and improve the reliability and safety of equipment. Simultaneously, by managing the storage and deletion of fault files, equipment fault information can be effectively saved and managed, providing support for subsequent fault analysis and prevention.

[0071] Example 2

[0072] Based on the same inventive concept as the aforementioned embodiment of a method for monitoring and evaluating the electrical performance of a terminal block for new energy vehicles, such as... Figure 4 As shown, this application provides a monitoring and evaluation system for the electrical performance of terminal blocks used in new energy vehicles. The system includes:

[0073] The benchmark verification library construction module 10 is based on the terminal block specification type, and performs analysis and classification based on the verification index dimension to build a benchmark verification library. The benchmark verification library contains performance label charts.

[0074] The pre-control mode determination module 20 is used to determine the pre-control mode of the electrical performance testing equipment, including an automation mode and a human-machine interaction mode, wherein the automation mode is based on a programmable controller.

[0075] An adaptive operation and management model building module 30 is used to map and configure the benchmark verification library based on the pre-control mode to build an adaptive operation and management model. The adaptive operation and management model is connected to the programmable controller via a channel.

[0076] Operation and management mechanism matching module 40, which is used to read the target verification task, transmit it to the adaptive operation and management model, and match and determine the automated operation and management mechanism;

[0077] The equipment operation data determination module 50 is based on the programmable controller and performs operation control management based on the automated operation and management mechanism in the electrical performance inspection equipment to determine the equipment operation data, which includes workstation monitoring data and performance evaluation data.

[0078] The automated operation control and feedback module 60 performs automated operation control analysis and feedback management based on the equipment operation data.

[0079] Furthermore, the system also includes:

[0080] The performance tag map generation module is used to classify and integrate terminal blocks, determine multiple terminal block categories, including standard terminal blocks, RF coaxial terminal blocks, and high-speed signal terminal blocks, and is updatable. For each terminal block category, it extracts and identifies the main performance indicators based on the standard terminal blocks to construct a main tag map, wherein the main performance indicators include contact resistance, insulation resistance, and dielectric strength. It also extracts and identifies the electrical performance indicators based on the RF coaxial terminal blocks to construct a single tag map. Furthermore, it extracts and identifies the electrical performance indicators based on the high-speed signal terminal blocks to construct a double tag map. Finally, it maps and associates the main tag map, the single tag map, and the double tag map, performs coreference resolution, and generates the performance tag map.

[0081] Furthermore, the system also includes:

[0082] The dynamic warning instruction generation module is used to identify the target verification task, determine the target type, traverse the performance label map in the benchmark verification library, and determine the target verification label; combine the target verification label to perform adaptive debugging based on the pre-control mode, and determine the periodic operation and control mechanism; determine the supervision mechanism based on the periodic operation and control mechanism, and map and generate the automated operation and management mechanism.

[0083] Furthermore, the system also includes:

[0084] An automated operation and management mechanism generation module is used to determine multiple workstation nodes based on the automated operation and management mechanism; based on the multiple workstation nodes, determine the node tolerance range for constraining dynamic operation and control deviation; map the node tolerance range to the periodic operation and control mechanism to generate the automated operation and management mechanism; if the node tolerance range is not satisfied, generate a dynamic alarm instruction.

[0085] Furthermore, the system also includes:

[0086] The performance evaluation data generation module is used to configure performance verification requirements, which are mapped to various performance tags. Simultaneously, a step-by-step judgment based on the performance verification requirements is performed along with the operation and control management of the automated operation and management mechanism. If the workstation verification result does not meet the mapped performance verification requirements, quality anomaly visualization is performed and a non-conforming identifier is generated. The entire lifecycle of verification data is integrated to generate the performance evaluation data.

[0087] Furthermore, the system also includes:

[0088] The compensation calibration module is used to monitor the verification environment and, in conjunction with the limitations of the equipment technology, determine the evaluation influencing factors, wherein the evaluation influencing factors are identified by characteristic values; comprehensively evaluate the evaluation influencing factors to determine the deviation coefficient; determine whether the deviation coefficient meets the threshold standard, and if not, generate a result compensation instruction; based on the result compensation instruction, determine the compensation data based on the deviation coefficient, and perform compensation calibration on the performance evaluation data.

[0089] Furthermore, the system also includes:

[0090] The human-machine interaction command generation module is used to identify the equipment operation data, perform automated early warning management of the equipment operation status, and generate fault files; perform storage and deletion management of the fault files; identify the equipment operation data, and if it is in an automated over-limit state, generate human-machine interaction commands; upon receiving the human-machine interaction commands, start the human-machine interaction mode, and perform manual management by personnel through a visual interface.

[0091] Through the detailed description of the aforementioned method for monitoring and evaluating the electrical performance of terminal blocks for new energy vehicles, those skilled in the art can clearly understand the monitoring, evaluation, and protection system for the electrical performance of terminal blocks for new energy vehicles in this embodiment. As the system disclosed in the embodiment corresponds to the device disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to in the method section.

[0092] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring and evaluating the electrical performance of terminal blocks used in new energy vehicles, characterized in that, The method is applied to a monitoring and evaluation system for the electrical performance of terminal blocks used in new energy vehicles. The system is communicatively connected to electrical performance testing equipment. The method includes: Based on the terminal block specifications and types, an analysis and classification based on the verification index dimensions are conducted to build a benchmark verification library, which contains performance label charts. The pre-control mode of the electrical performance testing equipment is determined, including an automation mode and a human-machine interaction mode, wherein the automation mode is based on a programmable controller; For the pre-control mode, mapping and configuration based on the benchmark verification library are performed to build an adaptive operation and management model, and the adaptive operation and management model establishes a channel connection with the programmable controller; The target verification task is read and transmitted to the adaptive operation and management model to match and determine the automated operation and management mechanism; Based on the programmable controller, operation and control management based on the automated operation and management mechanism is performed in the electrical performance inspection equipment to determine the equipment operation data, which includes workstation monitoring data and performance evaluation data. Based on the equipment operation data, automated operation control analysis and feedback management are performed; The method for determining an automated operation and management mechanism through matching includes: Identify the target verification task, determine the target type, traverse the performance label map in the benchmark verification library, and determine the target verification label; Based on the target verification label, adaptive debugging is performed according to the pre-control mode to determine the periodic operation and control mechanism; A regulatory mechanism based on the aforementioned cycle operation control mechanism is determined, and the automated operation management mechanism is generated by mapping it.

2. The method as described in claim 1, characterized in that, The method for performing analysis and attribution based on the dimensions of the verification indicators includes: Terminal blocks are categorized and integrated to determine multiple terminal block categories, including standard terminal blocks, RF coaxial terminal blocks, and high-speed signal terminal blocks, and these categories are updatable. For the multiple terminal block categories, extract and identify the main performance indicators based on the standard terminal block, and construct a main tag map, wherein the main performance indicators include contact resistance, insulation resistance and dielectric strength; Extract and identify electrical performance indicators based on the RF coaxial terminal block, and construct a tag map; Extract and identify electrical performance indicators based on the high-speed signal terminal block, and construct a binary tag map; The main label graph, the first-term label graph, and the second-term label graph are mapped and associated, and common-inference resolution is performed to generate a performance label graph.

3. The method as described in claim 1, characterized in that, The method for determining a regulatory mechanism based on the aforementioned periodic operation control mechanism and mapping it to generate the automated operation management mechanism includes: Identify multiple workstation nodes based on the aforementioned automated operation and management mechanism; Based on the multiple workstation nodes, determine the node tolerance range for constraining the dynamic operation control deviation. Map the node tolerance range with the periodic operation control mechanism to generate the automated operation management mechanism; If the node's tolerance range is not met, a dynamic warning instruction is generated.

4. The method as described in claim 1, characterized in that, The method for obtaining performance evaluation data includes: Configure performance verification requirements, wherein the performance verification requirements are mapped to each performance label; As the automated operation and management mechanism operates, a step-by-step judgment based on the performance verification requirements is performed simultaneously. If the workstation's verification results do not meet the mapped performance verification requirements, perform quality anomaly visualization and generate a non-conforming identifier; The performance evaluation data is generated by integrating the verification data throughout its entire lifecycle.

5. The method as described in claim 4, characterized in that, After obtaining the performance evaluation data, the method includes: The monitoring and testing environment, combined with the limitations of equipment technology, is used to determine the assessment influencing factors, which are identified by characteristic values. A comprehensive evaluation of the aforementioned influencing factors was conducted to determine the deviation coefficient. Determine whether the deviation coefficient meets the threshold standard; if not, generate a result compensation instruction. Based on the result compensation instruction, compensation data based on the deviation coefficient is determined, and the performance evaluation data is compensated and calibrated.

6. The method as described in claim 1, characterized in that, This method involves automated operation control analysis and feedback management, including: Identify the equipment operation data, perform automated early warning management of the equipment operation status, and generate fault files; Perform memory storage and deletion management on the faulty files; The system identifies the equipment's operational data and, if it is in an automation over-limit state, generates a human-machine interaction command. Upon receiving human-computer interaction commands, the human-computer interaction mode is activated, allowing personnel to manually manage the process through a visual interface.

7. A monitoring and evaluation system for the electrical performance of terminal blocks used in new energy vehicles, characterized in that, The system is used to perform a monitoring and evaluation method for the electrical performance of a terminal block for new energy vehicles as described in any one of claims 1-6, the system comprising: The benchmark verification library construction module is based on the terminal block specification type, and performs analysis and classification based on the verification index dimension to build the benchmark verification library, which contains performance label charts. A pre-control mode determination module is used to determine the pre-control mode of the electrical performance testing equipment, including an automation mode and a human-machine interaction mode, wherein the automation mode is based on a programmable controller. For the pre-control mode, mapping and configuration based on the benchmark verification library are performed to build an adaptive operation and management model, and the adaptive operation and management model establishes a channel connection with the programmable controller; The target verification task is read and transmitted to the adaptive operation and management model to match and determine the automated operation and management mechanism; Based on the programmable controller, operation and control management based on the automated operation and management mechanism is performed in the electrical performance inspection equipment to determine the equipment operation data, which includes workstation monitoring data and performance evaluation data. Based on the equipment operation data, automated operation control analysis and feedback management are performed.

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